Download Research Setup for Special Purpose Permanent Magnet

Czech Technical University in Prague
Faculty of Mechanical Engineering
Department of Instrumentation and Control Engineering
Habilitation thesis
Research Setup for Special Purpose Permanent Magnet
Synchronous Machines
Ing. Martin Novák, Ph.D.
Field of habilitation – Automatic control of machines and processes
2012
Prague
Acknowledgements
I would like to express many thanks to a special person, prof. Ing. Jaroslav Novák
CSc. for his unending, continuous and very generous support during all the years we have
been working together. I also thank the head of division of electrical engineering prof. Ing.
Ivan Uhlíř DrSc. and the head of Department of instrumentation and control engineering doc.
Ing. Jan Chyský CSc. for theirs support and all my other colleagues for theirs advices. Finally
many thank to my family for theirs support and understanding and for tolerating all the late
evenings and weekends spend on those projects described here. Thank you all.
2
Table of contents
1.
Introduction ....................................................................................................................... 10
2.
Review of current technology state................................................................................... 13
3.
Origin of the projects ........................................................................................................ 21
4.
Modeling of synchronous motor ....................................................................................... 23
4.1.
5.
Real PMSM model parameter identification ............................................................. 28
Measurement of rotor position .......................................................................................... 33
5.1.
Direct position measurement by means of A/D converter ........................................ 35
5.2.
Indirect position measurement with comparison and D/A converters ...................... 35
5.3.
Measurement method based on phase error estimation ............................................. 36
6.
Measurement of power in impulse powered circuit .......................................................... 42
7.
Construction of power inverter ......................................................................................... 51
8.
Control of PMSM ............................................................................................................. 56
8.1.
Control of instantaneous current values .................................................................... 56
8.2.
Field oriented control of PMSM................................................................................ 63
8.3.
High-speed PMSM for an electric turbocharger........................................................ 66
8.4.
Control for a micro turbine power generator ............................................................. 69
9.
FPGA Controller implementation ..................................................................................... 73
10.
Sensor-less control ........................................................................................................ 83
10.1.
Stator and rotor flux linkage estimation................................................................. 83
10.2.
PI compensator based estimation ........................................................................... 86
10.3.
High frequency signal injection ............................................................................. 87
11.
Thesis contributions, conclusions and future work ....................................................... 89
12.
References ..................................................................................................................... 93
12.1.
External references on thesis subject ..................................................................... 93
12.2.
List of co-authored papers related to thesis ........................................................... 99
12.3.
Own patents and utility designs ........................................................................... 101
12.4.
List of co-authored papers on other topics ........................................................... 102
3
List of figures
Fig 4.1 – Permanent Magnet Synchronous Motor [40] ............................................................ 23
Fig 4.2 - d-q axis PMSM equivalent circuit diagram ............................................................... 25
Fig 4.3 – Simulink controller model ........................................................................................ 27
Fig 4.4 - Measurement of PMSM stator inductance ................................................................ 28
Fig 4.5 – Schematic diagram for PMSM stator inductance measurement ............................... 29
Fig 4.6 – DSP Controller PMSM startup with Vdc = 500 V, _Iqreq = 9 A ............................. 30
Fig 4.7 – Comparison between measured (blue, solid line) and modeled PMSM deceleration
(red, dashed) ............................................................................................................................. 31
Fig 5.1 – Block diagram for speed and position measurement with reference marks [nm62] 33
Fig 5.2 – Block diagram for speed and position measurement with reference marks and
demodulation [nm62] ............................................................................................................... 34
Fig 5.3 - Indirect position measurement with comparison and D/A converters [nm32] .......... 36
Fig 5.4 - R/D converters autonomous universal card [nm32].................................................. 37
Fig 5.5 - R/D converter schematic diagram – measuring circuit ............................................. 38
Fig 5.6 - Used resolver for autonomous universal card [nm32]............................................... 39
Fig 5.7 – Resolver card (top) with attached DSP (bottom) ...................................................... 39
Fig 5.8 – Schematic diagram of the improved resolver card ................................................... 41
Fig 6.1 – Measured response of LA55P current sensor ........................................................... 43
Fig 6.2 – Measured response of LV25P voltage sensor ........................................................... 43
Fig 6.3 – Power measurement unit – Sensor inputs ................................................................. 47
Fig 6.4 – Power measurement unit – CPU, programming and debugging............................... 47
Fig 6.5 – Power measurement unit – Current loop outputs ...................................................... 48
Fig 6.6 –Power measurement unit ............................................................................................ 50
Fig 7.1 – Experimental power inverter for small voltages ....................................................... 51
Fig 7.2 – Experimental power inverter for micro-turbine generator – control part ................. 52
Fig 7.3 – Experimental power inverter for micro-turbine generator – power module ............. 53
Fig 7.4 – Prototype of the experimental power inverter for micro-turbine generator .............. 54
Fig 8.1 – Principle of PMSM field oriented control [nm29] ................................................... 57
Fig 8.2 - Phase current control structure [nm29] ..................................................................... 57
Fig 8.3 - On - off control - requested (red) and real (blue) values waveforms, f = 5Hz [nm29]
.................................................................................................................................................. 58
Fig 8.5 - Modified controller structure [nm29]........................................................................ 59
Fig 8.6 - Measured and desired motor currents for a step change in load [nm29] .................. 60
Fig 8.7 - Waveforms for proportional controller constant adaptation based on di/dt and ui ,
f=3,5Hz, torque and sense of rotation reversal - [nm24] ......................................................... 61
4
Fig 8.8 - Waveforms for magnetic flux weakening mode, f=55Hz - [nm24] .......................... 61
Fig 8.9 - Used controller structure for full magnetic flux mode (unframed) including proposed
form for magnetic flux weakening mode (framed) - [nm24]................................................... 62
Fig 8.10 - Phasor diagram in d-q coordinate system ................................................................ 63
Fig 8.11 - Block diagram of controller system......................................................................... 65
Fig 8.12 - High speed dynamometer with tested Synchronous motor - [nm19] ...................... 67
Fig 8.13 - Experimental IGBT inverter for high speed drive - [nm13] ................................... 67
Fig 8.15 - Current components id , iq , amplitudes of reference voltage and frequency
(revolutions) at no load starting up till 4200 rad/s at torque 0,44Nm with modulation index
correction- [nm13] ................................................................................................................... 68
Fig 8.16 - Block diagram of experimental system - [nm4] ...................................................... 69
Fig 8.17 High speed PMSM - [nm4] ....................................................................................... 70
Fig 8.18 - Coupled high-speed motor with automotive supercharger - [nm7] ........................ 71
Fig 8.19 - PMSM startup and deceleration - requested current iq = 1.6 A .............................. 71
Fig 8.20 - PMSM acceleration- requested current iq = 9.5 A .................................................. 72
Fig 9.1 – FPGA controller, resolver board, external inductance and tested motor .................. 73
Fig 9.2 – Detailed View of Analog Capture Circuit [72] ......................................................... 74
Fig 9.3 – Example FPGA <-> A/D converter communication ................................................ 75
Fig 9.4 –Resolver <-> FPGA communication [77] .................................................................. 75
Fig 9.5 – Block diagram of Park transform .............................................................................. 78
Fig 9.6 – Example of PI controller FPGA implementation...................................................... 79
Fig 9.7 –PWM FPGA implementation ..................................................................................... 80
Fig 9.8 –Block diagram of FPGA controller implementation .................................................. 82
Fig 10.1 - Space vector diagram - adapted from [21] .............................................................. 83
Fig 10.2 - Synchronous motor diagram of phasor for torque control ...................................... 84
Fig 10.3 - Block diagram of sensor-less control with angle and speed observer - adapted from
[19] ........................................................................................................................................... 86
List of tables
Tab. 4.2 - PMSM resistance and inductance ........................................................................... 29
Tab. 4.3 - PMSM model parameters ....................................................................................... 32
Tab. 6.1 – LEM LV 25-P voltage sensors manufacturer data [70] ......................................... 45
Tab. 6.2 – LEM LA 55-P current sensor manufacturer data [69] ........................................... 46
Tab. 6.3 - Selected PWM power measurement results obtained by different methods .......... 49
Tab. 9.1 - Device Utilization Summary .................................................................................. 81
5
List of abbreviations
A/D – Analog to Digital
ABS – Absolute
BLDC – Brushless DC motor
CIC Filter – Cascaded integrator-comb filter
CPU - Central processing unit
CSI – Current Source Inverter
D/A – Digital to Analog
DSP - Digital Signal Processor
DTC - Direct Torque Control
DVDD – Digital positive supply voltage
EKF - Extended Kalman Filter
emf – electromotive force
EPROM - Erasable Programmable Read-Only Memory
FEM - Finite Element Method
FOC – Field Oriented Control
FPGA - Field Programmable Gate Array
IGBT - Insulated gate bipolar transistor
IRC – Incremental Encoder
LPF – Low Pass Filter
MOSFET – Metal Oxide Semiconductor Field Effect Transistor
MSPS – Mega Samples per Second
PCB – Printed Circuit Board
PLL - Phase Locked Loop
PMSM - Permanent Magnet Synchronous Motor
PWM - Pulse Width Modulation
R/D – Resolver to Digital
rms – Root mean square
RPM – rotations per minute (this thesis uses SI units, all speeds have been recalculated to
rad/s except direct citations from references or manufacturers specifications)
SPI – Serial Peripheral Interface
SVPWM - Space Vector Pulse Width Modulation
VHDL - VHSIC Hardware Description Language
VHSIC - Very-High-Speed Integrated Circuits
VSI - Voltage Source Inverter
6
List of used symbols
B – friction damping coefficient [N/rad/s]
Bmat_m – peak flux density in stator core[T]
f – current frequency [Hz]
ia, ib , ic – instantaneous current value in phase a, b, c [A]
id, iq – instantaneous current value in d, q axes [A]
ihf_dq(t) – injected high frequency current [A]
In_rms – nominal rms value of current [A]
iα, iβ – instantaneous current value in α, β axes [A]
J – moment of inertia [kgm2]
Kair_friction – air friction viscous damping coefficient [N/rad2/s2]
l – length [m]
Laa , Lbb Lcc – self-inductance of winding a,b,c [H]
Lab , Lbc Lbc – mutual inductance of winding a,b,c [H]
Ld , Lq – inductance in d,q axes [H]
Lσ – leakage inductance [H]
nMAX – maximal speed [min-1]
nn – nominal speed [min-1]
P – power [W]
Pcore – stator core losses [W]
Pf_air – power of air friction losses [W]
pp – number of pole-pairs [-]
r – rotor radius [m]
Rs – stator resistance [Ω]
Tf_air – air friction torque [Nm]
TL – load torque - mechanical [Nm]
Tm – mechanical torque produced by the motor [Nm]
TN – nominal torque [Nm]
va(t), vb(t), vc(t) – instantaneous voltage value in phase a,b,c [V]
vd(t), vq(t) – instantaneous voltage value in d,q axes [V]
vhf_dq(t) – injected high frequency voltage[V]
vi(t) – back-emf voltage[V]
vin(t) – resolver excitation voltage [V]
vL(t) – instantaneous voltage on inductance L [V]
7
vout1 (t) – resolver voltage from winding 1 [V]
vout2 (t) – resolver voltage from winding 2 [V]
vR(t) – instantaneous voltage on resistance Rs [V]
β – torque angle [rad]
ϴ - rotor angular position [rad] = ϴr + β
ϴr - angle between magnetic axis of rotor and stator magnetic field from stator winding A
[rad]
λf – back-emf constant [V/min-1]
ρair – air density [kg/m3]
ϕ – last measured resolver position [rad]
Ψa , Ψb , Ψc
Ψd , Ψq
– flux linkage from winding a,b,c [Wb]
– flux linkage in d,q axes [Wb]
Ψm – peak value of permanent magnet flux linkage [Wb]
Ψma , Ψmb , Ψmc – permanent magnet flux linkage components in axes a,b,c [Wb]
ω – electrical angular speed [rad/s]
ωm – mechanical angular speed [rad/s]
ωr – angular frequency of resolver excitation signal [rad/s]
8
Abstrakt
Tato habilitační práce popisuje projekty z oblasti řízení vysokorychlostních
elektrických strojů, v rozsahu do 10 kW výkonu a otáček 4400 rad/s, na kterých jsem se
podílel při výzkumu pro účely automobilového a energetického průmyslu. Těžiště práce v
problematice řízení strojů je navázáno na řešení měření a přípravu výkonovou část měniče
frekvence. Z teoretického rozboru jsem došel k návrhu a realizaci vysoce výkonného
regulátoru synchronního stroje na bázi programovatelného hradlového pole umožňující
dosažení podstatně vyšší rychlosti, řádově několika desítek tisíc rad/s a z prakticky
naměřených hodnot jsem vypracoval ideje k řešení vysokorychlostního vektorově řízeného
bezsenzorového stroje, který ještě není ve světovém měřítku řešen.
Abstract
This habilitation thesis describes projects from the field of control of high speed
electrical machines that I have been working on in the past. The range of power is up to 10
kW and speed is up to 4400 rad/s. The projects are from the automotive and energy
production industry. The scope is in the solution of problems of high speed machine control,
preceded with problems of measurement of physical and electrical properties on the machine.
I am also describing a design of power inverter I have been working on. Based on theoretical
problem analysis I have prepared and designed a powerful controller based on Field
Programmable Gate Arrays allowing to achieve much higher speed, in the range of tenths of
thousand rad/s. From experimental results I am developing ideas of sensor-less vector control
of high speed motor not previously available.
9
Chapter 1. Introduction
1. Introduction
If we look on the development in the field of electrical machines we can see some
interesting moments. As in all areas of technology, the trend is to find more efficient
solutions. As in my work I will be describing projects with synchronous machines, I will
focus mainly on the field of machines with power in the order of some kW. Those machines
are mainly used as small traction machines or as supplementary machines in the automotive,
transportation or energy production industry.
From the historical perspective, we can see first the application of brushed DC
machines. They were used in all kinds of drives. They have the advantage of simple control of
speed and torque, but from the maintenance point of view, the brushes present some
disadvantage. The next evolutionary step that can be seen for the last two or three decades is
the replacement of DC machines with induction machines. Although they are used already for
a very long time, almost as long as DC machines, it was the development of frequency
inverters that allowed a relatively simple control of speed and torque. Compared to DC
machines, the induction machine offers lower maintenance due to the absence of brushes.
In the last years, a new trend is emerging. It is the usage of synchronous machines as
traction drives and auxiliary motors. They are also known for a long time. Initially,
synchronous machines were used mainly as electrical energy generators in power plants. In
those applications they had an excitation winding to create the magnetic flux. With the
development of permanent magnet synchronous machines, a new synchronous motor
application area was open. The permanent magnets from rare earth elements like Sm, Co, B
etc. allowed creating high magnetic flux in a restricted area. This allowed the construction of
powerful motors with small size. Compared to same power DC machine, an induction
machine is usually smaller and so is the synchronous machine compared to an induction
machine. The trend is clearly visible. Permanent magnet synchronous machines started to
emerge in traction applications and from this area to move also to other fields.
The area I will focus on is high speed permanent magnet machines. Although the
mechanical construction of such a machine presents significant challenges and many
questions and problems in this area are still unresolved I will focus on the control from the
electrical point of view. But let me first point out the significance of high speed machines,
theirs usage and theirs development for the future. There are already many applications for
high speed machines that the normal user is not aware of. Let me take an ordinary hand drill
as an example. For the reasons of constraints of size and weight the motor driving the drill is
not a DC or induction machine. It is a special kind of motor, a universal motor working with
high speed (2000 – 3000 rad/s). The speed is in this case around 1000 rad/s. This high speed
(and low torque) coming from the motor is then transferred to lower speed (and higher torque)
through a gear box. The advantage is obvious. A hand drill is small and powerful at the same
time.
The reason for creating smaller, high-speed machines is theirs much higher power
density. As it is shown in [51] “As an example, one large turbo compressor can be replaced
with 16 compressors, each with a volume of 1/64 of the conventional compressor, which
together has the same output power but requires only a quarter of the volume of the
conventional compressor. The diameter of the small units would be ¼ of the original one and
the rotational speed would therefore increase by a factor of at least 4….. Downscaling of a
macro turbo machine for constant specific speed and lower volume flow therefore leads to an
increase in rotational speed…. The overall volume of the electrical machines in the example
above is also ¼ of the original one.”
10
Chapter 1. Introduction
From this comes the idea to use high speed machines also in other applications with
size constraints. As it was shown in [58] “The target maximum speed of the motor is
240,000rpm. The rated output is 5kW but the motor dimensions are small enough; the stator
diameter is 60mm, core stuck size is 40mm and rotor diameter is only 20mm.”
Two main projects that I have been working on are the following. The first is an
electrically driven turbocharger, the second is a high speed generator driven with a turbine.
There is a high industrial demand for high-speed machines as can be seen in [31].
Applications such as micro gas turbines, compressors, blowers, pumps, hybrid electric
vehicles, turbo molecular pumps, machine tool spindles are mentioned. Some of them are a
556 kW, 3000 rad/s induction generator, 3300 kW, 1100 rad/s turbo compressor, 1000 kW,
1500 rad/s PMSM generator, 10 kW or 18000 rad/s induction motor.
Let me first describe briefly the electrically driven turbocharger I have been working
on. The purpose of a car turbocharger is to provide a sufficient air flow for the combustion
engine to improve the combustion process. An ordinary turbocharger is driven by exhaust
gases. The exhaust gases are powering a turbine which is powering a compressor producing
the compressed air. There is a direct dependency between the amount of exhaust gases and the
amount of produced compressed air. The more exhaust gas, the more compressed air. From
dynamic behavior point of view, the problem is a large time constant of this system. Imagine
the user wants to accelerate by stepping on the gas pedal. At first, nothing happens as it takes
some time to produce enough exhaust gas to accelerate the turbine and to produce enough
compressed air. This delay can be significant. On the other hand, there can also be a reversed
problem. When driving with high speed, the compressor can produce too much compressed
air that could be used to produce extra electrical energy. Therefore the idea of an electrically
driven turbocharger is to improve the dynamic of the system and to produce extra electrical
energy. The dynamics of an electrical motor is higher than that of a traditional turbine –
compressor system. The traditional system could either be entirely replace by an electrical, or
with regards to the current state of technology completed with a small electrical system. This
small system would “help” the mechanical system to shorten its response, and when surplus
mechanical energy is available to produce electrical energy from it. If we look at the
requirements and required parameters for the electrical machine we will see it is high speed.
The usual speed of a car turbocharger is between 10000 rad/s and 30000 rad/s. The electrical
machine industry is nowhere near this speed for the time being. Current fastest electrical
machines commercially available on the market have speeds around 10000 rad/s. The
experiments I have done were with a 2500 rad/s nominal speed permanent magnet
synchronous machine driven up to is maximal speed 4200 rad/s.
The second project I have been working on, the high speed generator, can be seen as
the reversed case of the turbocharger. The goal here is to produce electrical and thermal
energy. The idea seems to be simple. Take a source of mechanical energy, a turbine, turning
with high speed, connect it directly without a gear box with a generator and produce energy.
Such a generator could be used in households or as an emergency generator. The high speed
device promises small dimensions of the device. There is a growing application demand as
can be seen in e.g. [28] where various applications of high-speed machines such as peak
shaving, co-generation, remote power and premium power generation are mentioned. Also
applications for high power as in [29][30] are known. For small powers the technology is not
yet available.
11
Chapter 1. Introduction
The turbine can be driven by exhaust gases from a combustion chamber. The first
problem if I omit the combustion chamber represents the turbine itself. With regard to
robustness and maintenance of the generator, a logical solution is to use the turbine from an
automotive turbocharger. As those are mass produced, they will be relatively cheap and well
manufactured. The second problem is the electrical machine. Only few manufacturers are able
to produce a high speed permanent magnet machine. Then there is a problem to couple those
two machines together. The best solution would be to produce the rotor of the electrical
machine and the turbine on a same shaft.
Next challenge is to build a fast enough inverter. For high speeds, the switching
frequency has to be high to; let’s say at least around 20 kHz. Fortunately, such components
are available in these days.
The main problem I will focus on is the control of the high speed machine. If we look
at the required calculation speed of the controller, it will be very high. As results from the
experiments done, the usual digital signal processor (DSP) available for real time motor
control is barely able to run the control algorithm up to 42 000. Then its speed is not sufficient
any more. For this reason I have decided to develop an FPGA based controller.
Last but not least, there is a problem with rotor position sensing. The controller
requires the rotor position to be able control the machine. The limit for our machine is 4200
rad/s, the resolver sensor is unable to support more. Therefore, I will focus also on a review of
sensor-less position estimation.
According to the review of current state, such applications of high speed machines are
demanded in the industry. Theirs development would present a significant improvement in
many areas. The proof is this is e.g. paper [23] where and automotive high-speed fuel cell
compressor with rated parameters 12 kW, and speed 2000 to 12000 rad/s is presented. This
paper does not give any detailed description of the used components or other parameters, it is
more advertising. However it proves that such applications are currently being developed in
the industry and are demanded. It also gives the insight into problems in the area that still
need solving. Another application emerging in the industry is the power production with highspeed generators. A significant contribution in high-speed motor design is in paper [26]. It is
the design of a 100 W, 52000 rad/s generator.
12
Chapter 2. Review of current technology state
2. Review of current technology state
High speed machines are an emerging subject. They have the potential to make
devices smaller, more efficient and less polluting. Although much progress has been done in
the last years in this area, there are yet many unresolved problems and unknowns. In this
chapter I am summarizing some articles concerning control of high speed machines. I have
used those articles as a startup point for my work.
Paper [14] is describing a development of a high-speed PMSM controller and
experimental results. The authors first describe in general the possibilities of PMSM control
and the application for which they are developing the controller - centrifugal compressor drive
for a reverse Brayton cryo-cooler. The parameters of the used motor are: 4-pole PMSM, 100
W, 10000 rad/s, 28 V. The controller is based on a TI TMS320LF2407A Digital Signal
Processor. As it is clear from the paper, there is in fact only an open loop control, without a
feedback from the motor to the controller. The authors use a classic V/f control to achieve the
desired speed. From the power electronics point of view, a Space Vector Pulse Width
Modulation is used (SVPWM). Next the authors discuss the topology of the inverter, a usual
MOSFET triple half bridge. In the conclusions, experimental results for speed 5000 rad/s are
presented as phase currents waveforms. Also an analysis of harmonics components is given.
The authors show that the highest harmonic component is the fifth with amplitude of about 6
percent of the first harmonics. I see the biggest disadvantage of this presented approach in the
absence of any feedback. The PMSM is high speed, but only open loop control is used. On the
other hand, the absence of feedback causes that it is possible to use a relatively slow DSP.
Article [15] describes the construction of a super high-speed PMSM. The motor
should be used to drive a cryogenic cooler at 77 K with the following parameters: 2kW,
20000 rad/s. The motor structure including used materials and dimensions is given. The
PMSM has a two pole structure as this allows achieving maximal speed for lower voltage
frequency. The stator is a slot less version with laminated low loss silicon steel to minimize
cogging torque and eddy current losses. The rotor magnetic flux is created with Sm-Co
permanent magnets achieving tangential flux density around 0.05 T and normal flux density
around 0.5 T. To assure protection against centrifugal forces, the permanent magnet is placed
inside a hollow titanium shaft. The prototype was tested with ceramic ball bearings up to the
speed 20000 rad/s. The controller is based on a TMS320F2407A Digital Signal Processor and
is working in open loop with V/f control.
Paper [16] shows a controller design for super high-speed PMSM. The motor is used
to drive a centrifugal compressor of a cryo-cooler. Although it is said in the paper that motor
parameters are given in a table, the table is missing in the paper. Therefore only the speed of
the motor can be found to be 20000 rad/s for a 2-pole motor and 10000 rad/s for a 4-pole
motor. As the 2-pole motor was still under development, the authors have tested the algorithm
with the 4-pole version. They have made experiments up to 8700 rad/s. The controller is
based on a TMS320LF2407A Digital Signal Processor; a 16bit fixed point DSP. The used
control algorithm is an open loop V/f control. The used modulator is SVPWM as according to
the authors it generates less harmonic distortion and provides a more efficient use of power
supply voltage. A detailed description of the SVPWM algorithm is given as well of the
modified V/f profile. The motor is started from zero speed with a fixed frequency first and
then switched to the V/f profile. The rated frequency of the device is 3333 Hz with a very
small stator reactance at the rated frequency of 0.03358 Ω and stator resistance of 0.06 Ω. The
content of higher harmonics is small, 5.88 percent for 5th harmonic component.
13
Chapter 2. Review of current technology state
A very high speed application is described in [17]. The described system is running at
52000 rad/s, 1 kW, 400 V, 1 pole-pair. First a detailed description of advantages of highspeed motors is given. Then the considerations of a mechanical design are given. The rotor of
the machine is created with a hollow titanium shaft with sleeve diameter 10 mm. Calculations
of centrifugal stress is given. Then the electromagnetic design especially a finite element
analysis of the machine is done. Loss analysis is also presented. The copper losses are
calculated to be 14.5 W at rated speed and power. Then a description of the power electronics
is given. The power inverter is a variable DC link inverter, a 3 times half bridge topology with
a DC-DC converter in the DC link. The switching frequency is 100 kHz where the
fundamental frequency for rated speed is 8.3 kHz. Also the values of components are given in
the paper. The controller is based on a Microchip dsPIC30F5016 Digital Signal Processor and
is using a sensor-less rotor position estimation based on stator-flux zero crossing detection
with a discrete integrator and comparator circuit. Rotor position and speed calculation is then
done on the DSP. "Since all considered applications need only low dynamics of the speed
control, simple torque control via the dc current is sufficient, which allows for a single, nonisolated shunt current measurement. The current reference is set by the speed controller"
[17]. If high dynamics would be required, this approach would not be sufficient. Finally the
description of the hardware and experimental results are shown. The presented test results
with the real machine have been carried out up to speed 7500 rad/s.
In paper [18] a method of precision speed observer with neural networks is presented.
The used PMSM has a power of 400 W, rated torque 1.3 Nm. The motor speed is not given,
but can be calculated to 300 rad/s. Therefore it is not a high speed PMSM, but the presented
idea could be possibly extended to high-speed. First a classical model of PMSM is defined.
Then a new space state model is presented. The space state model uses the derivative of
angular velocity and the difference of angular velocity and speed reference as two state
variables. A known load torque is supposed. It is estimated by a load torque observer with a
moving average filter. The angular speed, angular speed reference, q-axis current and
difference between the angular speed and reference are then fed to a back-propagation neural
network. The output of the network is the phase current. This is then added to the requested
speed from PI speed controller and fed to a PWM inverter. The algorithm is implemented on a
TMS320C31 Digital Signal Processor with additional FPGA circuits. The primary purpose of
this method is to improve position control in precision applications like milling machines,
CNC machines, assembly robots, high speed hard disks etc. According to the presented
simulation and experimental results, the proposed algorithm shows very good results in
maintaining position control. Compared to the other tested algorithm, it shows the steadies
response. With a more powerful hardware it could be implemented also in high speed
applications.
Paper [21] presents the design and analysis of a high-speed brushless DC motor for
centrifugal compressor. The design procedure including calculations is presented. The motor
parameters are 50 kW, 70000 rad/s. The motor is designed as a 2 pole machine with
diametrically magnetized permanent magnet. The permanent magnet is retained with CarbonFiber/Epoxy sleeve. After the initial design description the authors calculate various losses of
the motor to improve efficiency. The dominant losses are copper losses and stator core losses
(1778 and 1243 W). Other losses are almost an order of magnitude smaller. A comparison
between the analytical result and FEM calculation is given with a good agreement. Although
this paper does not handle the motor control, I have included it here as it shows ways for a
future development in the field of high-speed machines.
14
Chapter 2. Review of current technology state
A ready application is presented in paper [23]. It describes a high-speed automotive
fuel cell compressor. The rated parameters are 12 kW, 2000 to 12000 rad/s. This paper does
not give any detailed description of the used components or other parameters, it is more
advertising. However it proves that such applications are currently being developed in the
industry and are demanded.
A novel rotor position measurement method is presented in paper [24]. The motor
speed is 52000 rad/s. Other motor parameters are not given in the paper. First many
advantages of high-speed motors are described. According to the authors, a high-speed motor
can provide high-power and the size of the motor can be reduced significantly. Therefore they
see much future for high-speed motors in the field of turbo compressors, air-to-power
systems, micro gas turbines, drills and milling spindles. A problem in this field is to measure
precisely the rotor position. The bearings in this application are magnetically levitated ones
and need to maintain a very precise position. The air gap is 200 μm, so the sensor has to
measure with precision of some μm. The described sensor uses the evaluation of transversal
magnetic flux from an excitation coil through the rotor to a sensing coil. It works like a
transformer with variable mutual inductance. The sensing coil signal is evaluated by filtering
in a FPGA with a CIC filter. A description of sensor design and test results is given in the
paper. No data about the motor controller system is provided, but it is doubtful that a feedback
system is used for those speeds. More probable is open loop control with V/f algorithm.
The construction of a 100 W, 52000 rad/s is presented in paper [26]. The purpose is
the development of a mezoscale permanent magnet generator. The authors first give a brief
description of the advantages of high-speed machines and theirs properties. It is the high
power density. According to the paper it is around 0.6 mNm/cm3. The presented motor with
torque 1.9 mNm has the volume of 3.5 cm3. A detailed description of component selection i.e.
bearings, permanent magnets and all other components is given. The fundamental frequency
in the stator at rated speed is 8.3 kHz. An open loop control algorithm is used. There are two
machines on the same shaft with identical construction. One is used as a motor, the second as
a generator. Some motor components have been modeled with FEM. According to the
presented test results there is a good agreement between the simulations and measured results.
The authors have done the tests for speed 5200 rad/s with a variable frequency generator with
current 2.5 A and frequency 833 Hz. This paper gives a very good description of experiments
and results and presents a significant research.
Control of a high-speed PMSM motor is described in paper [27]. It shows the
calculation of an optimal V/f profile. The specific PMSM has rated speed 5200 rad/s, 28 V, 4
pole, 5 A. Based on this motor parameters the authors provide means to optimal V/f profile
calculation. The normal linear V/f profile cannot be used, as according to the authors the
stator resistance is always higher that reactive impedance in the operating range. At rated
speed 5200 rad/s the stator resistance is 0.06 Ω whereas the reactance impedance is 0,01679
Ω. The designed profile is quite non-linear; the criteria of optimality are not given in the
paper. Although the paper speaks about control, an open loop is used and no feedback is
provided to measure the real rotor speed. For this reasons only a low system dynamic can be
expected.
Paper [28] presents the development of a high-speed PMSM generator with a micro
turbine. Various applications of high-speed machines such as peak shaving, co-generation,
remote power and premium power generation are mentioned. First a brief description of highspeed PMSM construction is given followed by the mathematical model. The motor rated
parameters are 60 kW, 6100 rad/s, 550 V, 63 A, 2 pole. Also other motor parameters required
for modeling are given. The system was simulated in Matlab, Power System Blockset. Only
15
Chapter 2. Review of current technology state
basic system characteristics are considered in the model and only dynamic behavior is
studied. The presented tests have been done in the speed range 200 to 6100 rad/s. The
simulation results are shown to be in agreement with experimental results. The PMSM was
loaded with resistive load during tests. No details about the used controller system are given,
and it is not clear whether it used a feedback loop or open loop.
A general review of current state-of-the art technology of high-speed PMSM is given
in [31]. Applications such as micro gas turbines, compressors, blowers, pumps, hybrid electric
vehicles, turbo molecular pumps, machine tool spindles are mentioned. This is more an
overview paper that a detailed paper, but it provides valuable information about current
applications. Some of them are a 556 kW, 3000 rad/s induction generator, 3300 kW, 1100
rad/s turbo compressor, 1000 kW, 1500 rad/s PMSM generator, or 10 kW 18000 rad/s
induction motor. The authors also mention that a smaller device - for power around 1 kW and
speed 18000 rad/s is more difficult to build that a larger device. From the paper it is obvious
that there is a high industry demand for high-speed machines and theirs applications.
Paper [32] summarizes the potentials and limits of high speed PMSM. It mentions the
interest in high speed motors as a means to remove mechanical gears and to improve
reliability. Some comparison with the universal motor is also given. The authors then handle
the different properties of the motor such as the choice of permanent magnet material,
permanent magnet demagnetization, stator losses, rotor losses, thermal limitations and
control. Some applications are also shown together with calculation and simulation results.
Also information of advantages, disadvantages and available circuits for motor control are
presented. Basically square wave current is preferred in the paper in place of sinusoidal
current due to the simplicity of the control algorithm and the possibility to implement easier
sensor-less control by measuring the voltage of the non-energized winding. This paper gives
some important and interesting general considerations for PMSM design and control.
Results of a construction of a high-speed machine are presented in [33]. The rated
motor parameters are 14 kW, 1200 rad/s. The motor is for a fuel cell powered hybrid electric
vehicle. The motor has to run in a wide speed range 100 - 1200 rad/s and with variable DC
bus voltage from 180 - 400 V. The paper describes the design of the motor, including
magnetics, rotor dynamics, mechanical analysis, DC bus design, controller design and thermal
management. There are no further details about the control algorithm other that it uses a PI
speed controller. As the motor is running with a relatively low speed compared to today's
speeds, I assume that an ordinary DSP controller system is used.
Testing of a high-speed generator is described in paper [34]. The tested target
application is a micro turbine generator whereas the paper describes tests with two identical
machines without the turbine. One machine is used as a motor, the second as a generator. The
rated parameters are 110 kW, 7000 rad/s, 500 V. The stator core outer diameter is 135 mm,
stator core length 160 mm, rotor outer diameter 66 mm. From the dimensions and power I
have calculated the power density to about 20 kW/cm3. In a real application it is clear that this
would be significantly lower, but it is impressive nevertheless. The paper contains a detailed
analysis of the motor losses i.e. air friction, iron losses, bearing losses, stator winding losses.
Then the description of the test set-up is done. The measurement of losses has been done
calorimetrically. Also the estimate of measurement accuracy is shown. The experiments were
done after a steady state was reached, according to the authors this was after about 30
minutes. The calculated efficiency is around 96 percent. No details about the motor controller
system or power inverter are given. The paper contains detailed measurement results of heat
flow of cooling water, oil and air used in the system for cooling and lubrication. From those
charts it is visible that the steady state assumption is valid. In general, this paper proves that a
16
Chapter 2. Review of current technology state
high-speed, high-power machine can be build. It is unfortunate, that no more details about
future development and whether it was really tested with a turbine could not be found.
A novel approach for a direct torque control is presented in paper [49]. The direct
control algorithm consists in a calculation of a simplified mathematical model of PMSM and
calculation of torque and flux. The presented algorithm has the advantage over standard direct
torque algorithms. It uses a constant fixed switching frequency and minimizes flux ripple and
electromagnetic compatibility problems this way. A detailed description of the algorithm is
given in the paper. Simulation and experimental results are shown and they are in a good
agreement.
Implementation and experimental investigation of PMSM control is the scope of paper
[50]. It summarizes open- and closed-loop control schemes up to speed 6000 rad/s. First a
description of the experimental system is given. The used controller is a Motorola DSP
56005. According to the authors the ratio of the PWM switching frequency to the
fundamental frequency of the motor has to be kept at 10 or more. Moreover, high-speed
PMSM have usually very small stator resistance and inductance and this makes it difficult to
control the stator current. The used digital controller uses a control period of 30 μs. First a
constant V/f mode is described; the used V/f curve is presented. Then a current mode is used.
From the testing the authors show the development of a hybrid mode. The motor is first
started in current mode and then a V/f is used. The experimental results show a good quality
control up to speed 10000 rad/s. For sensor-less control, a self-tuning flux observer is used.
Paper [51] presents a miniature 52000 rad/s electrically driven turbo compressor. The
machine is a two stage turbo compressor tested for speeds up to 60000 rad/s with maximal
pressure ratio of 2.3 and mass flow 0.5 g/s. The power is around 100 W. The described
application is a fuel cell system. A detailed description of the system is given. The paper
describes the electrical design of the machine, of the inverter, and the mechanical design
including FEM calculations. The turbo compressor uses high-speed ball bearings and stator
magnetic field frequency of 8.3 kHz. Amorphous iron is used in the stator to minimize stator
losses; litz-wire is used to minimize skin effect. The inverter is controlled in six-step or block
commutation mode changing switches state after 120 electrical degrees. Stator voltages are
measured for a sensor-less position estimation. As it is shown in the paper, for those speeds,
air friction becomes a significant part of the losses. For the described motor, air friction losses
are 8 W whereas bearing losses are 5 W for one bearing; 10 W for two bearings. As the air
friction losses and bearing losses are of comparable magnitude, they have to be considered in
the design as well. As bearing life-time is the main issue in this design, the authors consider
the usage of other bearing types in the future. The description of the control algorithm is not
given but it is most probably an open loop control system.
Paper [52] presents a power electronics interface for a 100 W, 52000 rad/s gas turbine.
The rms value of phase voltage is 11 V, phase voltage fundamental frequency 8.3 kHz. The
electronics is created with MOSFETs. The rms value of rated supply phase current is 3 A and
peak phase voltage 16 V. A comparison between various power converter topologies is
shown. The compared topologies are PWM voltage source inverter (VSI) with fixed dc
voltage, current source inverter (CSI) and two other topologies. The currents are controlled by
the BLDC motor control method = rectangular phase currents. From the comparison it is clear
that the VSI with block commutation is the best method for this system.
Description of a high-speed drive system is also given in [53]. It is a generator/starter
for gas micro turbine. The power is 100 W and speed 52000 rad/s with rated torque 2 mNm.
Two machines are coupled here to form an experimental setup. One is working as a motor, the
other as a generator. The authors state that a mechanical coupling at 52000 rad/s is not
17
Chapter 2. Review of current technology state
feasible. A calculation of losses including stator core losses, stator winding losses, air friction
losses is given. The total estimated efficiency of the machine is around 96 % when air friction
losses are not considered and 86 % when they are. From this it can be seen that air friction
losses play a very important role in high-speed machinery. They are almost the same size as
bearing losses (8 W air friction vs. 10 W bearing losses) in this case. The losses have been
measured from deceleration of the machine from 60000 rad/s. From the paper it is clear that
efficiency of the machine is much dependent of the allocation of losses to either the electrical
drive system or the application.
Paper [54] shows the design of a 100 W, 52000 rad/s electrical generator. The main
described problems are losses due to the high frequency in stator core and windings, the
bearing technology, the rotor dynamics and rotor design. The machine is a two pole PMSM.
Fundamental frequency is 8.3 kHz at rated speed. The paper gives a detailed analysis of stator
winding losses, stator core losses, mechanical stresses and a description of the test bench. The
motor is driven open-loop with impressed three phase current of 2.5A and adjustable
frequency. A voltage source inverter with external inductances is used.
An ultrahigh-speed low power system is shown in [55]. It is a 100 W, 52000 rad/s
system. It features low motor inductance and high fundamental frequency. The main
application is for a portable power unit. The output voltage is from 28 to 42 V. First, various
inverter topologies are compared, then the electrical machine design is described. Bearings
technologies are discussed and are found to be the main limit of today’s high speed machines.
Finally a comparison of simulated and measured results is given and found to be in good
agreement.
Control of PMSM is also shown in [56]. The rated motor parameters are 200 rad/s,
Vdc 300 V, 10 Nm, pp = 2. It is therefore a low speed motor. Nevertheless, it contains a good
description of PMSM model and space vector modulation. The proposed controller is a field
oriented controller with space vector modulation. The results are obtained with simulation in
Matlab, no experimental results are shown.
Paper [57] gives a comparison between V/f and position sensor-less control of PMSM.
The main described drawbacks of V/f control is the open-loop mechanism. It is also difficult
to obtain high performance control with varying motor parameters. The analysis is done for a
surface magnetic motor. The proposed control is in a special γδ frame. A model description in
this frame is given. Next stabilization control is shown. The rated motor parameters are 1.5
kW and 360 rad/s. It is therefore a low speed motor. The experiments show acceleration and
step responses of the motor. The conclusion of the paper is that V/f control is suitable for
simple variable speed applications like fans, pumps whereas sensor-less field oriented control
is more suitable for applications requiring high dynamics like cranes or high performance
drives. On the other hand, FOC requires a much more complex and faster controller that V/f.
A trial production of a high-speed PMSM is shown in paper [58]. The machine is a 2
pole, 5 kW, 24000 rad/s machine. The machine has very small dimensions, stator diameter 60
mm, core stuck size 40 mm and rotor diameter 20 mm. The rated voltage is 200 V. The
controller system is a TMS 320C32 Digital Signal Processor. The control is an open-loop V/f
algorithm with sampling frequency 20 kHz. The motor was tested up to 15000 rad/s. At the
end the authors discuss further developed and improvements, mainly bearing types to achieve
the desired speed.
18
Chapter 2. Review of current technology state
The next paper [59] is from the same authors, so the parameters are the same, 5 kW,
24000 rad/s. Again a V/f control method is used. The motor was operated up to 18000 rad/s
unloaded and to 13200 rad/s loaded. The controller is in this case a TMS320C6701 floating
point DPS with sample period of 20 kHz. The PMSM and inverter system is simulated in
Matlab; no experimental results are shown in the paper.
The possibilities of sensor less control are described in the next papers:
An interesting approach for sensor-less control is presented in paper [21]. It is a Direct
Torque Control (DTC) based controller. The presented application is a PMSM micro-turbine
generator. The motor parameters are 6100 rad/s, 105 kW, 660 V, 1-pole pair. Also the internal
motor parameters like resistances and reactances are given. Two different approaches of
sensor-less rotor speed and position estimators are given. Both algorithms use the
mathematical model of PMSM. The first is based on the estimation of stator flux linkage
vector angle; the second is based on the estimation of rotor flux linkage vector. A detailed
mathematical development of the position estimator is given for both approaches. As it is
clear from the results only the estimator based on rotor flux linkage vector angle can be used.
The stator based estimator shows very high fluctuations of speed and torque and cannot
therefore be used. On the other hand, the rotor based estimator shows promising results. There
is a good estimation of motor speed. As it is usual for sensor-less control there is a problem
for low motor speed, for motor startup. The obtained results show some promises for high
speed motor control. However the presented results, although they have been obtained with
parameters of a real motor, have been tested in simulation only. In a practical application, the
results could be quite different due to non-linearity and parameter changes with speed.
Paper [19] presents a sensor-less vector control of high speed PMSM. The motor
parameters are 2 poles, 131 kW, 7000 rad/s, 360 V, 17,9 Nm, 237 A. The used excitation
frequency is 1200 Hz with inverter switching frequency of 15 kHz. The controller is using
SVPWM. The control algorithm is implemented on a TMS320V33-150 Digital Signal
Processor. According to the authors, the algorithm takes 20 μs to calculate. First a method of
rotor position sensing with three Hall sensors is presented. The position between the sensors
is interpolated from last measured speed. Then a description of sensor-less approach is given.
The sensor-less algorithm is activated from 1200 rad/s, the motor is started with a predefined
V/f profile. The authors have tested the proposed algorithm experimentally up to speed 6000
rad/s.
Another approach to sensor-less control is presented in paper [20]. It is capable to
work from zero or low speed. It uses high frequency voltage injection into the PWM signal.
The injected signal is going through the PMSM and is demodulated with a frequency
estimator. “The rotor position is estimated from machine inductance variations due to
saturation and geometrical effects “[20]. As the PMSM inductance is varying with rotor
position, this variation is used to estimate rotor position. The injected carrier frequency is
between 600 Hz and 2 kHz in paper [20]. For a high speed motor, the injected frequency
would have to be higher. The nominal motor speed in the paper is 600 rad/s. The PWM
frequency is not given in the paper. "The interaction of the high frequency injected voltage
with saliency of the machine produces a resultant high frequency current modulated by the
rotor frequency [20]."
Similar sensor-less techniques are discussed in paper [25]. Two basic techniques are
described. The first is back-EMF estimation; the second is the so called EKF (Extended
Kalman Filter) technique. The back-EMF method is well known among those skilled in the
art so I will not discuss it here.
19
Chapter 2. Review of current technology state
The EKF method uses a space state model of PMSM. “The line voltages of the motor
and the load torque are the vector input variable of the system. The speed and the rotor
position are the two magnitudes to be estimated, and with the motor current, they constitute
the state vector. The motor currents will be the only observable magnitude that constitutes the
output vector “[25]. The EKF observer uses  reference frame to estimate the required
parameters. A more detailed description is not given in the paper. However, this approach
could be also probably used for a high-speed motor. The condition is a powerful hardware
such as an FPGA that I have used for controller implementation.
From the above made review of current state it is clear, that the problems of highspeed machines, theirs control, measurement, modeling and sensors-less control are studied
both at the universities and in the industry. The applications are wide ranging from
turbochargers, micro-turbine power generators, hybrid vehicles, fuel cells, spindles to cryocoolers or co-generation units. The motivation for high-speed machine development is mainly
the high power density of such machines. Following the current state review I see that
problems within the field of measurement, modeling and mostly control of high-speed
machines are currently present. In the field of modeling, the current models for standard low
speed machines do not take into account parameters like eddy current losses, bearing losses,
air friction etc. that can be significant for high-speed machines. In the field of control
algorithms, high-speed machines are controller without any feedback with V/f. For this
reason, they have lower dynamic response compared as if they would be controller with field
oriented control algorithms. All the present applications are controlled with a DSP that does
not allow the application of FOC for high-speed machines as it has high computational power
demands. Last but not least, there is a problem with the measurement of rotor position for
high speed. For high speeds, the employment of a position sensor is no more practical, as it
limits the maximal speed and complicates construction of the machine. The solution could be
sensor-less control, but it requires the calculation of a simplified mathematical model of the
machine. For those reasons it is also limited for high speed and current versions of controllers
of high-speed machines are working with an open loop V/f control. It is the goal of this thesis
to find at least partial solutions for those problems.
20
Chapter 3. Origin of the projects
3. Origin of the projects
The origin of the herein described projects lies within the needs coming from the
automotive and energy production industry. Several years ago, I was invited to join the Josef
Božek Research Centre of Engine and Automotive Engineering headed by prof. Macek, a
Czech Technical University in Prague based research project. Within this Centre, I was
working in the field of electrical machines. The focus was mainly, although not exclusively,
on the permanent magnet synchronous machines, theirs applications and control.
A little bit later (2007) I was invited to join another research project, The
Development of Environmental - Friendly Decentralized Power Engineering headed by prof.
Hrdlička, the dean of the Faculty of Mechanical Engineering. In this project I am working on
the development of a high-speed micro-turbine generator with a high-speed permanent
magnet machine. This research project is currently running and is supposed to finish at the
end of 2013.
From the needs of those projects we have identified several areas to work on. In
principle one of them was a high-speed machine; the other was a special purpose synchronous
machine, the electric power splitter. Those projects required a substantial amount of
development work in the field of hardware, software, control system and modeling. I have
been working on the selected issues of those problems. Those developed solutions are the
scope of this thesis.
For the purposes of algorithm testing, verification and control system design, I have
been working on a simulation model of a high-speed permanent magnet synchronous motor.
Apart from the traditional motor properties considered in ordinary low speed model, it was
required to add some specific issues for high-speed machines. It was also required to identify
the parameters of a real high-speed permanent magnet motor that was used for our
experiments. This project is described in the chapter 4. Modeling of synchronous motor
For the successful development of a high-speed motor controller system, it was first
required to prepare a suitable test setup. I also took part on this test setup preparation. The
work started with a selection and preparation of a PMSM rotor position measurement system.
For all PMSM control algorithms, the information about instantaneous rotor position is
essential for a control system. Although there were also some sensor-less estimator at the
time, theirs function was not reliable for high-speed machines and required a high amount of
computational power. For this reason, we have started with a position sensor approach. More
than one method were examined for rotor position sensing, including direct, indirect and
phase error methods. From the made experiments, it was clear, that the phase method
provides much advantage. Based on this, I have designed a special rotor measurement unit,
described in chapter 5. Measurement of rotor position
Next step was the design and development of a special measurement unit to measure
voltage, currents and power in PWM circuits. Standard devices available on the market did
not allow measuring those parameters of our circuits in an economical way. My experience
with this research is described in chapter 6. Measurement of power in impulse powered circuit
An important research and design was made in the field of a power inverter for highspeed machines. The currently available power inverters do not allow various control
algorithm testing, they are proprietary devices of the manufactures and no modification is
allowed. For this reason we have developed a power inverter platform that allowed the testing
21
Chapter 3. Origin of the projects
of all our algorithms. My experience with the design of the power inverter for high-speed
machines is presented in chapter 7. Construction of power inverter
After the test setup was completed, I have been working on various problems of
control of high-speed machines. Our team explored several ways of control, including control
of instantaneous current values or field oriented control. The results are shown in chapter 8.
Control of PMSM.
As our experiments were done, during the years, it became slowly clear that if higher
speeds would be required, a different controller system would have to be developed. The
digital signal processor used was not fast enough to provide field oriented control for highspeed machines. It became clear that no available DSP has enough calculation power for a
really high-speed machine and field oriented control. For this reason I have developed a
unique, novel and innovative controller based on FPGA that solves those problems. The
development of this novel controller is described in chapter 9 FPGA Controller
implementation.
After the development of the FPGA high-speed motor controller, one problem of highspeed motor control is solved, but others previously not so significant problems come into
mind. For high-speed machines the employment of rotor position sensor is problematic. For
this reason I have also made a research of sensor-less rotor position estimation methods. They
are all model based and require a calculation of the simplified machine model in real time.
Due to short calculation time for high-speed machine control, its employment was previously
not possible in DSP system for high-speed machines and field oriented control. Thanks to my
novel FPGA platform controller, enough calculation power is available for them. A selection
of some sensor-less rotor position estimation methods suitable for FPGA implementation is
therefore presented in chapter 10. Sensor-less control.
All the herein presented results have been published mainly on international IEEE
conferences in many papers that I have either authored or co-authored. Those are shown in
chapter 12.2 List of co-authored papers related to thesis. I have in total authored or coauthored more than 30 papers on the thesis subject and more than 60 other papers on related
subjects.
22
Chapter 4. Modeling of synchronous motor
4. Modeling of synchronous motor
For the purposes of FPGA controller implementation and verification I have created a
Simulink model of PMSM. The model was used during the designing phase of the controller
for algorithm verification, range checking, parameter setting etc. The model is based on the
information published in [37] - [41].
The herein described model is based on the following assumptions and simplifications:

The magnetic circuit is considered linear, without hysteresis, the values of inductances
are considered constant, not dependent of current

Magnetic and electric skin effects are neglected

The rotor resistance is considered

Air friction and bearing losses are considered

The permanent magnet flux linkage is considered constant
The PMSM model is based on the drawing on Fig 4.1 [40]. The a, b, c axes are the
axes of stator windings, the d axis is chosen in the direction of permanent magnet flux, the q
axis is perpendicular to d axis while 90° ahead of the d axis. The PMSM rotor is drawn with
saliency, although the actual motor I have been using had non salient poles. For non-salient
pole machines, the model can be simplified more, but I have preferred to derive a more
general model. The angle of rotor q-axis with respect to a-axis is denoted as . The d-q
reference frame is rotating with speed ω = d/dt.
Fig 4.1 – Permanent Magnet Synchronous Motor [40]
23
Chapter 4. Modeling of synchronous motor
The PMSM model is based on the electrical properties of the stator windings and on
theirs interaction with the rotor. The electrical dynamic equations of the phase voltages va, vb,
vc are
va (t )  Rs 
d a
dt
(4.1.1)
vb (t )  Rs 
d b
dt
(4.1.2)
vc (t )  Rs 
d c
dt
(4.1.3)
where Rs is PMSM stator winding resistance and Ψa, Ψb, Ψc are corresponding flux linkages
for phase a,b,c.
Under the assumption that mutual inductances Lab = Lba and peak flux linkage of the
permanent magnet is Ψm (with components a, b, c) the flux linkages Ψa, Ψb, Ψc in (4.1.1) (4.1.3) are
 a  Laaia  Labib  Lacic  ma
(4.1.4)
 b  Labia  Lbbib  Lbcic  mb
(4.1.5)
 c  Lacia  Lbcib  Lccic  mc
(4.1.6)
Flux linkages, voltages and currents can now be transformed from the three phase
stator coordinate system to the rotor fixed d-q coordinate system using transformation
matrices [40]. The symbol S in those matrices represents voltages, fluxes or currents - Park
transformation
cos    cos    120  cos    120    Sa 
 Sq 
 S   2 / 3  sin  sin   120 sin   120   S 
  



  b 
 d 

  Sc 
 S0 
1/ 2
1/ 2
 1/ 2
(4.1.7)
where S0 is a zero vector, in a balanced three phase system Sa+Sb+Sc = 0
The inverse transformation (inverse Park transformation) is
sin   
1  Sq 
 Sa   cos   
 S    cos   120 sin   120 1  S 


  d
 b  
 Sc  cos    120  sin    120  1  S0 
(4.1.8)
Using transformations (4.1.7) and (4.1.8) the voltage equations in d-q reference frame become
vq  Rsiq 
vd  Rs id 
d q
  d
(4.1.9)
d d
  q
dt
(4.1.10)
dt
where
 q  Lqiq
 d  Ld id   m
(4.1.11)
24
Chapter 4. Modeling of synchronous motor
Or in complex vector format
v  Rs i 
d
 j  vR  vL  vi
dt
(4.1.12)
Hence the voltage model of PMSM can also be expressed by combining (4.1.9) and (4.1.11)
vq  Rs iq  Lq
diq
vd  Rs id  Ld
did
  Lqiq
dt
dt
  Ld id   m
(4.1.13)
(4.1.14)
where ω is electrical angular speed (not mechanical).
This model is shown in an equivalent circuit diagram on Fig 4.2.
Fig 4.2 - d-q axis PMSM equivalent circuit diagram
The mechanical torque produced by the PMSM is
Tm 
3
p p   miq   Ld  Lq  id iq 
2 
(4.1.15)
25
Chapter 4. Modeling of synchronous motor
The above described electrical model is completed with a mechanical model
Tm  TL 
K
J d B

  air _ friction  2
p p dt p p
pp
(4.1.16)
where TL is torque caused by the load, J is moment of inertia, B is damping constant,
Kair_friction is damping caused by air friction and pp is number of pole-pairs. The air friction is
viscous and can be calculated by equations in [42].
Rotor mechanical speed and rotor angle is
m 

(4.1.17)
pp
  t    m dt
(4.1.18)
Hence from (4.1.13) and (4.1.16) space state model of PMSM is
L
did  Rs
1

id  q iq  vd
dt
Ld
Ld
Ld
diq
dt

(4.1.19)
 Rs
L

1
iq  d id   vq  m 
Lq
Lq
Lq
Lq
(4.1.20)
2
2
p B
p K
p
d 3 p p
3 pp

 miq 
Ld  Lq  id iq  p   p air _ friction  2  p TL (4.1.21)

dt 2 J
2 J
J
J
J
For simplicity, the space state model can also be rewritten in a matrix form
dX
 A  X  Bu  N1  X    X T  N 2  X
dt
(4.1.22)
where A is system matrix, B is input matrix, N1 and N2 are nonlinear coupling
matrices

1

 did    Rs
0
0 
0
0 


 dt 
L
 i   Ld
  vd 

  d
d



 
di

R

1
 q
i   0
s
m

0
0



  vq  
q
 dt 
Lq
Lq    
Lq

 T 


 
 L
   
2
 d  
 pp 
 pp F 
3 pp

0

0
0
m
 dt 

J 

2 J
J 
(4.1.23)
Lq


2
0


3 pp
 0
L
T 0
L

L
0


d
 i 
d
q

 id 
id  
2 J
 d
  Ld
 



0 0   iq     iq  0
0
0
  iq 
L


q

  
  
p p K air _ friction   
 
 0

0
0

0 0


J




Based on (4.1.23) I have created PMSM model and model of the whole system on Fig 4.3.
26
Fig 4.3 – Simulink controller model
27
Chapter 4. Modeling of synchronous motor
4.1.
Real PMSM model parameter identification
To set correctly the PMSM model it was necessary to estimate some model
parameters. Some of them could be determined directly from the manufacturer’s data while
others required some experiments.
The motor parameters from the motor nameplate according to manufacturer are
Tab. 4.1 - PMSM nameplate data
Motor type:
2AML406B-090-10-170
Manufacturer:
Vdc = 560 V
nn = 25 000 min-1 , nmax = 42 000 min-1
In_rms = 11 A
K_E = 7,3 V/ kRPM
Tn = 1,2 Nm
SN: 1111VS781549
VUES Brno
To estimate stator winding resistance Rs I have used Ohm's method with a Diametral
Q130R50D power supply, 2x Pro's kit digital multimetr MT1232.
The stator winding inductance was measured from the time constant  of a transient
characteristics with oscilloscope GDS-806C with probe GTP-060A. The current was sensed
on a resistor with known resistance R, and inductance L = R was calculated. An example of
this measurement is on Fig 4.4. The experiment was done in accordance with the schematic
diagram on Fig 4.5.
Fig 4.4 - Measurement of PMSM stator inductance
28
Chapter 4. Modeling of synchronous motor
Fig 4.5 – Schematic diagram for PMSM stator inductance measurement
As stator inductance is a function of current, the measurement was done up to the
nominal current and a little above it. The inductance is changing somewhat with current as it
was expected.
The obtained results are the following
Tab. 4.2 - PMSM resistance and inductance
R ( mΩ )
210 (for I = 1 A)
L (μH)
800 (for I = 1 A)
1100 (for I = In = 11 A)
The permanent magnet flux linkage  m is calculated from the back-emf constant
provided from the motor nameplate
K_E = 7,3V/kRPM
m 
vi

  m  0, 072
Wb
(4.1.24)
Motor’s moment of inertia was calculated from a motor startup on Fig 4.6. In this
experiment the motor was unloaded and powered with a given current Iq = 9 A until field
weakening started. The system was controlled with the herein described DSP controller. The
start time was 0,4 s and the reached speed was 572 Hz (3600 rad/s). The startup current 9 A
corresponds to torque 0,98 Nm. Considering the relatively high current and torque,
mechanical losses were neglected in the calculations [nm5].
29
Chapter 4. Modeling of synchronous motor
Fig 4.6 – DSP Controller PMSM startup with Vdc = 500 V, _Iqreq = 9 A
Moment of inertia is
J T
t
0, 4
 0,98 
 0,11103

2  572
 kgm2 
(4.1.25)
As can be seen from the model, air friction losses are considered. This is important for
high-speed machines as the losses caused by air friction can have the same size as friction
losses in bearings.
According to information from [53], where speed was 52000 rad/s, friction losses
caused by air friction were 8 W, whereas bearing losses were 10 W for two bearings. In this
application the motor had power 100 W, the friction and bearing losses represented almost 20
percent of the losses.
As the machine used for this research has maximal speed 4200 rad/s, it can be
expected that air friction losses will be much lower. The reason for this is that according to
[53] power losses caused by air friction are given
Pf _ air  c f air 3r 4l
(4.1.26)
Where cf is friction coefficient, ρair is density of air at given temperature and pressure,
ω is rotor angular mechanical speed, r is rotor radius and l is rotor length.
Air friction torque is then
Tf _ air  c f air 3r 4l / 
(4.1.27)
And therefore the friction torque is a function of ω2 as it is used in the model.
30
Chapter 4. Modeling of synchronous motor
The viscous friction coefficient itself is dependent on the size of air gap and air flow in
the air gap given by Reynolds and Taylor numbers. Unfortunately, none of those parameters
could not be measured or determined precisely analytically.
For this reason an attempt was made to at least estimate bearing and air friction with
an experiment. It consists of accelerating the motor to maximal speed and turning off the
inverter. The rotor will spin down naturally. The deceleration of the rotor is measured as a
function of time. From (4.1.21) it is obvious that when the motor is un-powered and unloaded,
its mechanical speed will decrease with losses until a complete halt. This is described by the
following dynamic equation
pp B
p K
d

  p air _ friction  2
dt
J
J
(4.1.28)
It has to be noted here that this equation does not represent all losses in the motor.
The solution of (4.1.28) is
B    0
 t  
Be
 Bt 


 J 
 K air _ friction    0   K air _ friction    0   e
 Bt 


 J 
(4.1.29)
Equation (4.1.29) was used to find coefficients B and Kair_friction from experimentally measured
PMSM rotor deceleration. The search was done with a least square method in Matlab.
Fig 4.7 – Comparison between measured (blue, solid line) and modeled PMSM deceleration (red, dashed)
31
Chapter 4. Modeling of synchronous motor
The comparison on Fig 4.7 is a best match that could be achieved by varying just
parameters B and Kair_friction . As can be seen, the match is not very good. The reason is that
other losses in the motor have been neglected. One is the loss caused by eddy currents. As the
permanent magnet is rotating, it induces currents to the stator windings and stator iron. Also
there is an interaction between the permanent magnet and those currents. Stator core losses
could be determined by the Steinmetz equation [65],[66]

Pcore  Cm  f   Bmat
_m
(4.1.30)
Where Cm, α and β are material constant, Bmat_m is peak flux density and f is frequency of the
current. It can be seen that losses are a function of frequency i.e. rotational speed. The
function is nonlinear. Unfortunately this calculation is impossible as the stator material is not
known for our motor.
Another loss that has been neglected is reluctance loss - the interaction between the
permanent magnet and stator iron. This effect seems to be significant for lower rotor speeds.
Considering those simplification, the presented fit can be considered an approximate
model. The model parameters determined in this chapter are summarized in
Tab. 4.3 - PMSM model parameters
Model parameter
Value and units
R ( mΩ )
210 [mΩ]
L (μH)
1100 [μH]

0.072 [Wb]
m
note
for I = In = 11 A
J
0.11 . 10-3 [kgm2]
B
8.2 . 10-5 [kg/s]
Kair_friction
1,3 . 10-10 [kg/s]
Very small, could be significant for
higher speeds
In this chapter I have shown the specifics of high-speed machine modeling. Compared
to standard low speed machine models, more parameters have to be taken into consideration
like air friction or bearing losses. For high-speed machines, especially ones with lower power
rating, around 100 W those losses can represent around 20 percent of the rated power and it is
not possible to neglect them any longer in mathematical modeling. For medium power high
speed machines, those losses can be neglected only when the speed is relatively low or the
lower model precision is sufficient. To improve model precision more parameters like eddy
current losses, reluctance torque etc. could be also taken into consideration.
32
Chapter 5. Measurement of rotor position
5. Measurement of rotor position
For a good quality control of synchronous machine, a precise measurement of rotor
position is essential. Although some possibilities exist to estimate the position without a
sensor, they have many drawbacks and disadvantages. For this reason, I will focus only on the
usage of sensors in this chapter.
To measure instantaneous angular speed or angular position, one possibility is to use
some kind of marks on the rotor and to measure theirs time of passage. The passage of marks
can be registered with a Hall or inductance sensor. Under the assumption of a suitable ratio
between the mark size and the sensor size, it can be shown that the sensor output signal is
sinusoidal [nm62]. The period of this signal can be measured with a counter. The counter
value is inversely proportional to speed as with increasing rotor speed, the time between
individual marks is decreasing. The rotor position can be measured when a reference mark
e.g. one per revolution is employed and its passage is sensed. One possibility is also the
removal of one mark and the sensing of the missing mark by comparing the time of passage
of all parks with an average passage time. An example of such marks is shown on Fig 5.1.
Fig 5.1 – Block diagram for speed and position measurement with reference marks [nm62]
The signal can also be processed directly by employing a demodulation procedure. As
I have shown in my previous work, the phase demodulation is providing the highest amount
of information for this king of processing [nm62]. The signal can be measured with an
inductance or Hall sensor, sampled with an A/D converter and passed through a band pass
filter to the demodulator. The second sensor in the block diagram is used to sense the passage
of the one per revolution reference mark and measures average speed. This is used to set the
correct frequency of the band-pass filter, demodulator and low-pass filter. This second sensor
can also be replaced with the sensing of the missing mark and used to calculate the average
speed. After demodulation, it is then low pass filtered and transformed from the time domain
to angular position or speed domain. This can be seen on Fig 5.2. This method has been
successfully implemented and is able to measure even very small changes of speed.
33
Chapter 5. Measurement of rotor position
Fig 5.2 – Block diagram for speed and position measurement with reference marks and demodulation [nm62]
The method described in the previous paragraph can be used when the rotor is
equipped with some construction part that can be used as the marks. When this is not the case,
a separate speed or position sensor has to be employed and coupled to the motor. In some
cases such a sensor is already an integral part of the machine.
If we look at the available sensors for rotor position measurement of synchronous
machine, we have several choices. A common and precise way is to use an incremental
encoder (IRC). The advantage is high precision, and support for evaluation of sensors output
signal in most industrial controller hardware. But for the low robustness of the sensor and
limited speed for high-speed applications, this is not a common type for industrial traction
drives. A more common sensor is a resolver. It is composed of one primary winding on the
rotor and two secondary windings on the stator. The rotor winding is powered with an AC
excitation signal, with frequency in range 5-20 kHz. The two secondary windings are
perpendicular to each other and a voltage is induced into them. When the induced voltage in
one winding is maximal, the second winding has minimal voltage and vice versa. Therefore
by measuring two secondary voltages, one can measure the position of the rotor [1][2].
The resolver input voltage is sinusoidal, usually with frequency between 5-20 kHz
vin (t )  Vin  sin(r t )
(5.1.1)
Where V is the voltage amplitude and r is its angular frequency.
The output voltage has two components, one from the first secondary winding and the
second from the second secondary winding.
vout1 (t )  Vout1  sin(r t )  sin()
(5.1.2)
vout 2 (t )  Vout 2  sin(r t )  cos()
(5.1.3)
Where  is the measured position of rotor and V are corresponding amplitudes of output
voltage.
34
Chapter 5. Measurement of rotor position
As can be seen from equations (5.1.2) and (5.1.3) the dependence of voltage on rotor
position  is non-linear, it is sinusoidal. It is required to evaluate both signals as it is not
possible to determine the correct position in the whole range 0 - 360 ° by measuring only one
signal. In the measurement system, usually linearization is performed in a form of table stored
in a memory. This gives us the advantage of a linear dependence that is usually preferable.
There are several methods to evaluate the resolver signal; I will present some of them we have
used in our projects and published papers about them [nm32][nm33][nm34].
5.1.
Direct position measurement by means of A/D converter
The simplest method to evaluate resolver output signal is the sampling with an A/D
converter. It requires only an A/D converter and two comparators. The first comparator
compares the resolver input signal with a fixed level, synchronizes the events and starts the
A/D conversion. By this procedure, all signals are sampled in the same time with regard to the
input signal. The A/D converter samples one resolver output signal and is started by /WR
signal coming from the comparator. As the resolver output signal is an symmetric AC signal
with both positive and negative voltages and the A/D converter input is able to measure only
positive voltages in range 0-5 V, the voltage is shifted by 2,5 V by a Zener diode. The second
comparator measures the second resolver output voltage. Both the comparator and A/D
converter output signals are used as an address to a look-up table stored in EPROM. For the
reasons of size of the memory, only a 7 bit look-up table was created. This gives the
resolution of 128 positions per one revolution. The sampling frequency could cause problems
for higher speeds. So this described solution was used only for low speeds and for initial
algorithm testing [nm32].
5.2.
Indirect position measurement with comparison and D/A
converters
A more complicated version of position measurement using indirect evaluation
and D/A converters is shown on Fig 5.3. It requires four comparators, two analog multipliers,
two D/A converters and a microprocessor. The position is measured continuously and
relatively. The output is a form of two square wave signals on ports P1 and P2. The waveform
of the signal is the same as for incremental encoder. Values on ports n+1 and n-1 are
proportional to the next and previous values of position with regard to the last measured
position. Those values are converted to analog values with D/A converters and multiplied
with analog multipliers with the resolver output signal. When a next position is achieved, the
corresponding comparator switches and gives the microprocessor signal to recalculate a new
position. The comparator REF gives the microprocessor information about positive or
negative wave of the resolver input signal. The comparator ABS gives information of output
voltage polarity. This is used to obtain the initial absolute position after power up. The
absolute position after power up is available on port D8.
The advantage of the described system is higher precision that in the previous case.
The system was tested with excitation frequency 10 kHz with 8 bit microprocessor and D/A
converters with good results. For better quality control of permanent magnet synchronous
motor a 12 bit version with precision comparators would be required. However, the problem
is higher complexity. It requires two D/A converters and four comparators.
35
Chapter 5. Measurement of rotor position
Fig 5.3 - Indirect position measurement with comparison and D/A converters [nm32]
Those components are standard components and available. The problematic part is the
analog multiplier. It is expensive and limited in maximal frequency. Two analog multipliers
are required for this connection. For those reasons, the herein described method was tested,
but at the end another method using phase error estimation was chosen.
5.3.
Measurement method based on phase error estimation
This method is based on equations (5.1.1) -(5.1.3). The equations can be extended into
vout1 (t )  Vout1  sin(r t )  sin()  cos( )
(5.3.1)
vout 2 (t )  Vout 2  sin(rt )  cos()  sin( )
(5.3.2)
Where  is the last measured position.
After the equations (5.3.1) and (5.3.2) are subtracted, the final result is obtained
vout1 (t )  vout 2 (t )  V  sin(r t )  (sin()  cos( )  cos()  sin( )) 
 V  sin(r t )  sin(   )
(5.3.3)
For simplicity, this equation assumes voltages Vout1 and Vout2 to have the same value V.
This described method is used in a commercial resolver to digital (R/D) integrated
circuit AD2S1200. This circuit was used for construction of a 12 bit R/D converter that I have
helped developing. The schematic diagram of the unit can be found on Fig 5.5. The created
unit is on Fig 5.4 together with the used resolver on Fig 5.6.
This card is composed of the power source, the main R/D circuit and a current
amplifier to amplify the resolver’s excitation voltage. This circuit uses the internal oscillator
to synchronize the evaluation circuit. The circuits maximum output current is 100µA so it
needs amplification by an external amplifier. The maximal input current of the used resolver
is 50mA with rms voltage value 7V and frequency of 10 kHz.
The described unit in Fig 5.6 was the initial version of the measurement system where
the feasibility of the design was tested. This unit is now placed in the department’s laboratory
of electric machines on a synchronous motor where it is used by students. The next version
36
Chapter 5. Measurement of rotor position
that I have prepared was designed directly for a Ti TMS320F2812 DSP controller. This
controller was used for the PMSM control algorithm that will be described later on.
The last version of the resolver card has some adaptations for the DSP controller. First
it has galvanic power supply insulation as this was required for safety reasons and to improve
the protection of the DSP against distortions. This is achieved by the use of DC/DC
converters. It also allows powering the resolver board directly from the DSP power supply.
Next is the availability of A B signal. The usual resolver circuit output is absolute position
information within the range of one revolution. This is read during DSP initialization and then
on request. As the experiments have shown, this approach is slow and the controller would
not have a sufficient time for control. For this reason, the absolute position is read only on
request and a relative signal A B is used. The A B signal is acting like a standard IRC output
signal. For signal amplification and separation an inverter is used. The signal is then available
in a separate connector P2. Also the output of error signal LOT and DOS is now available on
a separate connector J2 together with all required signal for a direct stack-up of the resolver
board on the DSP board.
Fig 5.4 - R/D converters autonomous universal card [nm32]
37
Fig 5.5 - R/D converter schematic diagram – measuring circuit
38
Fig 5.6 - Used resolver for autonomous universal card [nm32]
Fig 5.7 – Resolver card (top) with attached DSP (bottom)
39
This board was made in two pieces; they are in the Laboratory of electric machines of
Department of Instrumentation and Control Engineering at the Faculty of Mechanical
Engineering, Czech Technical University in Prague. The design of the resolver card is shown
in Fig 5.8. The real device with attached DSP controller is on Fig 5.7.
The results of research where this card has been used were published in [nm19] [nm20].
In this chapter I have explored methods for PMSM rotor position and speed
measurement. I have developed, build and tested an electronic device for evaluation of
resolver signal with 4096 position per one revolution. This device was further used in the
development of an experimental setup with high-speed PMSM. The developed unit provides
means of parallel and serial communication to accommodate both the DSP and FPGA
controller systems described in this thesis. It also provides error signal to diagnose the current
state of the resolver and to detect errors. It is able to work up to speed 6000 rad/s. The results
were published in [nm32][nm33][nm34].
40
Fig 5.8 – Schematic diagram of the improved resolver card
41
Chapter 6. Measurement of power in impulse powered circuit
6. Measurement of power in impulse powered circuit
The measurement of electric power in PWM circuits is one of the key issues for highspeed machines. In impulse powered circuits like it is the case of PMSM control, an important
issue is the correct measurement of voltage, current and power. After working on the
problems of rotor position measurement, I have also been working on a measurement system
allowing measuring correctly the voltage, current and power of pulse width modulated
signals. This chapter is a digest of published papers [nm30], [nm49], [nm67].
In power electronic devices mainly PWM is used. The switching frequencies are in the
range from 1 kHz up to 20 kHz. The output voltage is generated as narrow rectangular voltage
with sharp edges with high du/dt. The high pulse front steepness is given by the short
switching time of inverters output transistors. The switching time is in the order of 0,1μs to
1μs. The output voltage is therefore damaged with higher harmonic components. The output
currents of frequency inverters are generally filtered by the load inductance and the first
harmonic of the current is more visible than the first harmonic of the voltage. Also in some
cases a sinusoidal filter can be used.
The usage of some measurement instruments calibrated for sinusoidal or DC powered
circuits is limited in PWM circuits with regard to these high harmonic components in current
and especially in voltage. Generally the most accurate devices for this purpose are based on
thermal principle. These instruments are however less available, more expensive and are more
sensitive to overload. Analog electro dynamical wattmeters are mostly used for mains voltage
frequency of 50 Hz, but theirs frequency range is often higher. Electrodynamic wattmeters
have usually the maximal frequency below 5 kHz, but they have a high current consumption.
Shielded electrodynamic wattmeters are usually limited by a maximal frequency of 1 kHz.
Ferodynamic wattmeters are usually limited to frequency of 10 kHz. In the present time,
analog wattmeters also become less and less available and become more expensive. However,
if they are available, they can be generally used also in PWM circuits, but without the
accuracy given by the manufacturer. Other disadvantage can also be the absence of an
electrical or data output is this is desired by the user.
Commercially available cheap electronic wattmeters for sinusoidal voltages and
currents are generally unusable for PWM circuits as they have an insufficient sampling
frequency.
The purpose of this chapter is to show a possibility for measurement of power in
PWM circuits in steady states using simple microprocessor devices or control units where
power measurement is a supplemental function. The main goal is not high accuracy, but
mainly the robustness and implementation of the method on standard components used in
motor control applications where electrical or data outputs have to be available. The described
instruments and methods serve as support for PWM circuits’ tests.
As it was previously stated, the goal is to measure power in PWM circuits using
standard robust components used in control applications. Power is in digital circuits normally
calculated from voltage and current samples. In feedback control systems, traditionally,
galvanic isolated voltage and current sensors with Hall probes are used. In our devices,
sensors from the company LEM proved competent. For current and voltage measurement in
low voltage circuits, with power up to 15kW, we are using LA55P current sensors and LV25P
voltage sensors.
42
Chapter 6. Measurement of power in impulse powered circuit
The nominal current for current transducer LA55P is 50A, measuring range is ±70A.
The most important parameter for this type of measurement is bandwidth. According to
manufacturer data, 1dB attenuation is for frequency 200 kHz. With regard to the filtration
effect of load inductance and sufficient frequency range of the transducer, the output signal
can be generally used directly to represent the current.
Voltage transducers LV25P, however, have a different behavior than the current
transducer. Step response for an input voltage step from 0V to 30V was measured. Serial
transducer resistance was 100kΩ and sensing resistance of the secondary side was 286Ω. The
measured time delay is 30 μs which is in agreement with the manufacturer data (40μs). The
measured step responses of the current and voltage sensors are on Fig 6.1 and Fig 6.2.
Fig 6.1 – Measured response of LA55P current sensor
Fig 6.2 – Measured response of LV25P voltage sensor
43
Chapter 6. Measurement of power in impulse powered circuit
Voltage transducer LV25P is generally used to measure the input voltage of inverters
or choppers. For these applications, where the voltage is DC and filtered with large
capacitors, the usage of this transducer presents no problems. In circuits with PWM, however,
these transducers cannot be used to measure the instantaneous voltage value as it is in
principle filtered by the transducer. Nevertheless, with some signal processing and with some
limitations, this sensor can be used with microprocessor circuits for semiconductor inverter
control to measure output power.
The microprocessor is sampling voltage and currents with a sampling frequency Δt
and calculates the power from it. The equations are well known.
For a correct and accurate digital power measurement, a high sampling frequency
according to the Shannon sampling theorem has to be used. In circuits with PWM, where
voltage and currents are sensed with Hall transducers with electronic compensation, there is
however a high probability that this condition will not be fulfilled. Then, situations can
happen where the measured power for two measuring periods will be different even if the
circuit parameters remain the same. The cause is limited transducer bandwidth and possible
current and voltage distortion by the transducer. The mean power value can nevertheless be
calculated by averaging several periods of the fundamental voltage or current harmonic
component.
Basically, the mean power value is calculated as an average of several mean values for
one signal period. In PWM circuits this is usable for most steady state power calculations in
inverters or choppers. It is the expression of a known fact, that electrical power is created only
by corresponding current and voltage harmonic components. For this reason, in PWM
circuits, as the currents are significantly filtered with load inductance, practically only the
fundamental current harmonic is present and therefore also only the fundamental voltage
harmonic occurs in the power calculation.
Using the previous description I have developed, for the purposes of our laboratory
technical background, for the purposes of research and also for the usage in teaching classes,
simple microprocessor modules for power measurement. They allow measuring the mean
value of power and rms voltage and current values. The input values are one voltage and one
current. Current is measured by means of a LA55P current transducer, voltage by means of a
LV25P voltage transducer. These sensors were selected mainly as they are very robust. The
measurement module provides the output of the measured power, voltage and current as a
current signal from 4 – 20mA or optionally as a serial RS232 line. The modules use one cheap
microcontroller of type C8051F300 from Silabs. The sampling period is 2μs (for both
channels together). The module was calibrated for sinusoidal voltages and currents.
The manufacturer data of the voltage transducer LEM LV 25-P are summarized in
Tab. 6.1, data for LEM LA55-P current sensor are summarized in Tab. 6.2.
The schematic of the module is show on
Fig 6.3, Fig 6.4 and Fig 6.5. The input part with voltage and current sensors is together
with a preamplifier on
Fig 6.3, the main CPU with programming and debugging is on Fig 6.4 and the output
part with 4 – 20 mA current loops is on Fig 6.5. The omitted part here is the power supply and
the RS232 serial line. The real device is then shown on Fig 6.6.
The following part describes some selected results from measurements with these
modules. The measurement was done with a frequency inverter powering an induction motor
loaded with DC dynamometer.
44
Chapter 6. Measurement of power in impulse powered circuit
These measurements allowed us to obtain a certain idea of the accuracy of power
measuring methods in PWM powered circuits. During the experiment, meter readings from
two independent analog wattmeters were compared along with data from the above described
modules, data from electronic wattmeter for sinusoidal voltages and data about output power
provided by the frequency inverter.
Tab. 6.1 – LEM LV 25-P voltage sensors manufacturer data [70]
Electrical data
IPN Primary nominal rms current
10 mA
IP Primary current, measuring range
0 .. ± 14 mA
RM Measuring resistance
RM min
RM max
with ± 12 V @ ± 10 mA max
30 Ω
190 Ω
@ ± 14 mA max
30 Ω
100 Ω
with ± 15 V @ ± 10 mA max
100 Ω
350 Ω
@ ± 14 mA max
100 Ω
190 Ω
ISN Secondary nominal rms current
25 mA
KN Conversion ratio
2500 : 1000
VC Supply voltage (± 5 %)
± 12 .. 15 V
IC Current consumption
10 (@± 15 V)+ IS mA
Accuracy - Dynamic performance data
XG Overall Accuracy @ IPN , TA = @ ± 12 .. ± 0.9 %
25°C
15 V
@ ± 15 V ± 0.8 %
(± 5 %)
L Linearity
< 0.2 %
tr Response time 2) @ 90 % of VP max 40 μs
45
Chapter 6. Measurement of power in impulse powered circuit
Tab. 6.2 – LEM LA 55-P current sensor manufacturer data [69]
Electrical data
IPN Primary nominal rms current
50 A
IP Primary current, measuring range
0 .. ± 70 A
RM Measuring resistance
RM
min RM max(TA = 70°C)
(TA
=
70°C)
with ± 12 V @ ± 50 A max
10 Ω
100 Ω
@ ± 70 mA max
10 Ω
50 Ω
with ± 15 V @ ± 50 A max
50 Ω
160 Ω
@ ± 70 mA max
50 Ω
90 Ω
ISN Secondary nominal rms current
50 mA
KN Conversion ratio
1 : 1000
VC Supply voltage (± 5 %)
± 12 .. 15 V
IC Current consumption
10 (@± 15 V)+ IS mA
Accuracy - Dynamic performance data
XG Overall Accuracy @ IPN , TA = @ ± 12 .. ± 0.9 %
25°C
15 V
@ ± 15 V ± 0.65 %
(± 5 %)
L Linearity
< 0.15 %
tra Reaction time to 10 % of IPN step
< 500 ns
tr Response time to 90 % of IPN step
< 1 μs
di/dt di/dt accurately followed
> 200 A/μs
BW Frequency bandwidth (- 1 dB)
DC .. 200 kHz
46
Chapter 6. Measurement of power in impulse powered circuit
Fig 6.3 – Power measurement unit – Sensor inputs
Fig 6.4 – Power measurement unit – CPU, programming and debugging
47
Chapter 6. Measurement of power in impulse powered circuit
Fig 6.5 – Power measurement unit – Current loop outputs
The used measuring components specification is the following:
Frequency inverter Siemens Master Drives VC, 3x400V, output current 10.2 A,
providing output power data PFM
Induction motor 3x380 V; 9,6 A; 4,4 kW; 50 Hz; 143 rad/s
P02: electrodynamic wattmeter Metra Blansko with accuracy class 0,2 – two
wattmeters connected by the Aaron method were used with the help of two current
transformers, accuracy class 0,2
P05: electrodynamic wattmeter Metra Blansko with accuracy class 0,5 – two
wattmeters connected by the Aaron method were used with the help of two current
transformers, accuracy class 0,2
PM: the above described microprocessor module with LA55P and LV25P transducers,
two modules were used connected by the Aaron method
The mechanical power on the motor shaft Pmech was calculated from the dynamometer
reading and from measured motor shaft speed. Tab. 6.3 summarize the obtained results. The
measurements were all done for the load of 25Nm and for different base harmonic frequency f
and different PWM switching frequency fPWM .
48
Chapter 6. Measurement of power in impulse powered circuit
Tab. 6.3 - Selected PWM power measurement results obtained by different methods
f[Hz]/fPWM[kHz] PFM[W] P02[W]
P05[W]
PM[W]
Pmech[W]
30/5
2737
2880
2880
2789
2002
30/8
2864
2910
2960
2765
1970
40/2
3549
3720
3920
3850
2803
40/5
3650
3750
3840
3617
2787
40/8
3711
3750
3760
3578
2755
40/10
3802
3780
3800
3453
2739
50/5
4461
4620
4760
4664
3604
As it is obvious from the results in Tab. 6.3 not even one measured value can be said
to be wholly accurate. Individual values were always compared with the rest of the measured
values from other methods and with the mechanical output power and efficiency. It can be
said that the rest of the measured data corresponds more or less with each other with some
variations. For the frequency of the basic fundamental component of the output current of 40
Hz, one can observe the influence of PWM switching frequency. Even if the load torque was
set to a constant value of 25Nm, while changing the PWM switching frequency the
mechanical output power of the motor was changing slightly due to the change in shaft speed.
It is probable that this is due to the fact that also the dead-times of the transistors wary for
different PWM switching frequencies. The more dead-times occur (meaning higher PWM
frequency) the more the rms value of the voltage is influenced. On the other hand, with rising
PWM switching frequency, the current is becoming more and more sinusoidal like and this
gives premises to lower losses of the motor and to higher efficiency. The results from the
microprocessor measuring module confirm this theory. By contrast to this fact, the efficiency
as calculated from the inverters reading is decreasing. This is due to the fact that the inverter
is in fact not measuring the power; it is merely calculated from idealized first harmonic
voltages without the effects of PWM and dead-time influence. For this reason, not even the
reading form the frequency inverter can be considered to be entirely accurate. We can
establish an agreement between the measured values, but with not a very high accuracy, over
5% in some cases. The correspondence between the power from the microprocessor module
and frequency inverter readings is dependent on the switching frequency, the wattmeter’s
readings have the habit to overestimate the real power, but again, this trend is not explicit.
49
Chapter 6. Measurement of power in impulse powered circuit
Fig 6.6 –Power measurement unit
From the presented analysis it is obvious that power measurement in PWM circuits is
not such a trivial matter as it may seem at the first glance when low cost and available
components have to be used. If higher accuracies need to be achieved, analog electro-dynamic
wattmeter’s calibrated for sinusoidal voltages and currents or simple electronic wattmeter
cannot be used. On the other hand, these devices are usable if the accuracy about 5% is
acceptable. If there is not a requirement for a data output, also analog electrodynamic
wattmeter can be used, considering the lower accuracy.
I have made in total around 10 power measurement units; they are used in our
laboratories.
This chapter presented my results from the field of measurement of voltage, current
and power in PWM powered circuits. A unique experimental device was designed, tested and
build in multiple exemplars. The device allows measuring all the required electrical
parameters of PWM circuits even for high frequencies necessary for high-speed machines. Its
construction allowed us to verify the employed sensor parameters before they were used in
the construction of an experimental power inverter for high-speed machines described in the
next chapter.
50
Chapter 7. Construction of power inverter
7. Construction of power inverter
For all here described experiments with the PMSM, it was required to design and build
a power inverter. The use of a commercial power inverter was not possible as it does not
allow different control algorithms. For this reason I have been working on a custom power
inverter. The initial choice was between FET and IGBT technology. The advantage of FET is
the possibility to achieve higher switching frequencies and lower switching losses in the
inverter. For high voltage applications, with the components available at the development
time, it was required to use IBGT’s. They allow voltages it the desired range around 600 V
for the cost of higher switching losses. This is a trade-off between device size, switching
frequency and losses.
For the purposes of testing with small voltages and currents I have created a small
power inverter module with FET transistors. This module is for voltages up to 50 V, currents
around 20 A. It allows the connection of a controller system. The control signals use optic
insulation from the power part as a protection of the microcontroller. The designed device can
be seen on Fig 7.1 . It was used with an induction motor for algorithm testing and is now in
the laboratory of microcontroller systems of our department.
Fig 7.1 – Experimental power inverter for small voltages
Next step was to design a bigger version of the power inverter for the PMSM. The
design parameters clear at the beginning of the design were power around 10 kW, voltage 600
V. It was also required to provide means to measure voltage and currents both on input and
output of the inverter so that efficiency can be evaluated.
I have created two units of those power inverters. They are located in the Laboratory
of electric machines of Department of Instrumentation and Control Engineering. I will
describe here only the inverter prepared for experiments with a high-speed micro-turbine
generator. In this description and figures, again the power supply is omitted.
51
Fig 7.2 – Experimental power inverter for micro-turbine generator – control part
52
Fig 7.3 – Experimental power inverter for micro-turbine generator – power module
53
Chapter 7. Construction of power inverter
The power inverter uses a Semicron SKHI61 Sixpack IGBT and MOSFET driver [35].
The rated parameters of this module are power supply voltage 15 V, no load supply current
200 mA, input-output turn-on propagation time 0,45 μs, input-output turn-off propagation
time 0,45 μs, error input-output propagation time 1,3 μs.
The inverter design with this module can be seen on Fig 7.2. The inputs to the inverter
are six signals TOP1, BOT1, TOP2, BOT2, TOP3, BOT3 from the DSP or FPGA controller.
Also an external error signal Error_In can be connected. For all input and output signal it is
possible to choose the voltage levels either 5 V or 15 V with jumpers JP1, JP2. The Error_In
signal is propagated thought the module to the _Err signal. This signal is inverted and level
converted to the Error_Out signal. This in turn is connected to the DSP or FPGA controller. It
signals a fault of the inverter. When this occurs, it is necessary to turn off all control signals
TOPx and BOTx and to turn them of again to restart the inverter.
This part also handles current signal processing from voltage and current sensors LEM
LV25-P and LEM LA 55-P. A relay K2 is available to control additional electronic circuits
from the DSP controller.
The outputs of the module are signals U, V, W that control the main IGBT switching
transistor module. The main transistor module on Fig 7.3 is a Semikron SKM 75 GD 123 D
module with rated parameters 1200 V, 75A [36] . From left to right it is composed of: current
sensor LEM LA 55-P, voltage sensor LEM LV25-P. They measure the input voltage and
current in the DC link. Between the input terminals and the IGBT module capacitors are
inserted to suppress electromagnetic disturbances coming from the DC link. The output of the
module is equipped with two current sensors LEM LA 55-P. This is sufficient for a load
without the connected neutral wire.
Fig 7.4 – Prototype of the experimental power inverter for micro-turbine generator
54
Chapter 7. Construction of power inverter
The real inverter that I have built is shown on Fig 7.4. The device was successfully
designed, developed, tested and applied. Results have been published in [nm13] - [nm16].
This chapter presents results from the research, development and design of an
experimental power converted for high-speed machines. The developed power inverter
allowed us to test various control algorithms with PMSM. Without this experimental power
converter or with a commercial power inverter, those tests would have been impossible as
commercial inverters are closed platforms. Our inverter allowed testing of various control
algorithms and various switching frequencies as well. It is a robust novel device and can be
used both in laboratories and in industrial applications.
55
Chapter 8. Control of PMSM
8. Control of PMSM
8.1.
Control of instantaneous current values
One of the first investigated approaches of control of PMSM was the control of
instantaneous values of phase currents. The advantage is the simplicity of the control
algorithm as no transformation calculations are required like it is the case of Field Oriented
Control. On the other hand, the controller has a sinusoidal reference variable in this case. This
presents challenges on controller design and settings.
In this chapter I will present some of the results of project based on instantaneous
current control I have been co-working on and give the references to co-authored paper in this
field.
Within the scope of Josef Božek Research Centre of Engine and Automotive
Engineering our projects [nm1] - [nm34] were focused on PMSM applications in the field of
1. Special purpose and auxiliary vehicles drives
2. Traction drives
3. Electric power splitter control in hybrid drives
At this time, we are focused on linear control structures for torque control. The PMSM
linear control structure is based on the rectangular coordinate system; the space current vector
is controlled to be coaxial with the induced voltage so a linear dependency of the torque on
the current amplitude can be achieved:
Tm 
3
p p   d iq   qid 
2
(7.1.1)
where pp is the number of pole pairs of the machine, d and q are flux linkages and id
and iq are current in the corresponding d-q axes.
If the motor is in full magnetic flux mode, the current component id = 0 and equation
(7.1.1) can be simplified into
Tm 
3
p p  q id
2
(7.1.2)
The situation in full magnetic flux mode is shown in the phasor diagram on Fig 8.1. In
this figure, also an electrical model of single phase winding of PMSM is shown. The
components RS and L1 are the resistance and inductance of stator winding. Voltage V1 is the
power supply voltage and Vi is the induced voltage. In the phasor diagram d is the magnetic
flux produced by the permanent magnets on the rotor.
56
Chapter 8. Control of PMSM
Fig 8.1 – Principle of PMSM field oriented control [nm29]
The phasor diagram shows the ideal situation that the controller is trying to achieve.
ˆ . In this
The ideal situation is that the current phasor Iˆ is perpendicular to the flux linkage 
d
case maximal torque is produced. The approach described here is using the control of
instantaneous values of phase currents to achieve this optimal state. Sinusoidal phase current
control linked with the rotor position eliminates the electronic commutation disadvantages
and does not require the coordinate conversion like it is the case with rectangular coordinate
system motor control used in traditional vector based motor control [nm29]. This simplifies
the controller structure. With regard to the application specific demands in transportation,
simplicity and robustness of the controller structure was preferred.
The used controller structure used initially for experiment is shown on Fig 8.2.
Fig 8.2 - Phase current control structure [nm29]
57
Chapter 8. Control of PMSM
The phase of current is derived from the actual rotor’s angle so that this current is
coaxial with the induced voltage at all times. The induced voltage position is uniquely given
by the actual rotor‘s position [nm29]. The controller places the current vector so that it is
perpendicular to the rotor magnetic flux. The two other phase currents are controller in a
similar manner with phase shift 120°. Both PI and on-off controllers were tested in this
project. The controller was connected to the above mentioned resolver card converting the
position information from resolver into digital form, distinguishing 4096 position per one
revolution. The card - microcontroller’s connection is assumed to transfer continuously the
position information in the form of common incremental encoder’s signals, this means in
relative form.
A selection of the results from [nm29] is shown here. The tests were done in unloaded mode
with following PMSM parameters: 550 W, 3000 1/min, 340V, 1,6A. The switching frequency
was 5 kHz.
Fig 8.3 - On - off control - requested (red) and real (blue) values waveforms, f = 5Hz [nm29]
As can be seen from the comparison between on - off and PI controller on Fig 8.3 and
Fig 8.4, the on - off controller shows higher errors between the measured and desired values.
This was to be expected. On the other hand its algorithm is much simple and does not have
such a high demands on computational power. For this reason it is a possible candidate for
high speed machines considered in the future.
Another important conclusion from this experiment was that although three controllers
should be required to control three currents, in the case of a balanced load and balanced
supply voltage, the structure can be simplified as uA + uB + uC = 0. This simplifies further the
controller and is shown as the final controller structure from paper [nm29] on Fig 8.5.
58
Chapter 8. Control of PMSM
Fig 8.4 - PI control requested (red) and real (blue) values waveforms, f = 50Hz [nm29]
Fig 8.5 - Modified controller structure [nm29]
The results of experiments on a different machine using the same control algorithms
were also published in [nm29]. In this case the machine was with a higher power, 4kW,
220V, 13A, 157 rad/s. Switching frequency was 5 kHz.
59
Chapter 8. Control of PMSM
Fig 8.6 - Measured and desired motor currents for a step change in load [nm29]
An example result from [nm29] is shown on Fig 8.6. A response of a PI controller
structure on the step change can be seen as the desired current I*, measured current Isact and
phase currents Ib* (desired) and Ibact (measured). As can be seen from Fig 8.6 the response
of the controller is measured for a step change from +8 to -8 A of current. A new steady state
is reached in around 8 ms.
As the controller controls sinusoidal properties, the control quality will depend on the
frequency of the signal and controller settings. The improvements of control quality can be
done by adapting the PI controller parameters based on actual PMSM speed. This was part of
a project we have presented in [nm24]. The controller structure from this paper is on Fig 8.9.
The controller was implemented on a TMS 320C240 Digital Signal Processor. The controller
structure is basically composed from two PI controllers for instantaneous values of phase
currents. The third controller calculates the maximal available current and allows flux
weakening mode. The controller parameters are adapted based on the time derivative of set
currents. Details are described in the paper [nm24]. Example results from the paper are on Fig
8.7 and Fig 8.8. Fig 8.7 shows the current and speed waveforms for the transition to the
braking mode and following a sense of rotation reversal from the initial speed approximately
57 rad/s. Fig 8.8 shows results of the tests without detailed optimization of controller settings.
Waveforms for flux weakening mode, current frequency 55 Hz are shown. From the
comparison it can be seen that even that the requested controller current Iset is sinusoidal, the
current controller follows well the desired input Iact. uR is the proportional voltage used as
input to PWM, ui is induced voltage in this figure.
The conclusion from all the experiments with direct control of phase current is that it
is much simpler that field oriented control from the hardware point of view. It therefore
allows using cheaper and simpler controller. On the other hand, the control quality is lower
that for field oriented control. Tests for speeds up to 4200 rad/s have been made confirming
this. For high-speed motors this seems to be an option if lower control quality is acceptable in
60
Chapter 8. Control of PMSM
the application and if a lower system dynamic is sufficient. For high dynamic applications,
field oriented control has to be used. This promises higher dynamics, but requires a much
more powerful hardware for the controller.
12
i/A/, *100 n/1/min/
8
4
|I|set
iact
0
0
0,5
1
1,5
2
2,5
3
3,5
*100 n
4
|I|act
-4
-8
-12
t/s/
i/A/, u/-/
Fig 8.7 - Waveforms for proportional controller constant adaptation based on di/dt and u i , f=3,5Hz, torque and
sense of rotation reversal - [nm24]
12
10
8
6
4
2
0
-2 0
-4
-6
-8
-10
-12
iset
iact
10
20
30
40
50
60
uR
ui
t/ms/
Fig 8.8 - Waveforms for magnetic flux weakening mode, f=55Hz - [nm24]
61
Fig 8.9 - Used controller structure for full magnetic flux mode (unframed) including proposed form for magnetic flux weakening mode (framed) - [nm24]
62
Chapter 8. Control of PMSM
8.2.
Field oriented control of PMSM
Field oriented control (FOC), sometimes called vector control, represents an
improvement of control quality of PMSM. As it is clear from the model of synchronous
machine described in previous chapters, control of PMSM can basically be done either by
controlling the instantaneous values of phase currents or by using vector control. Vector
control in principle changes both the magnitude and phase of the controlled currents. This
allows to decouple torque and flux (both are functions of current and frequency) and provides
faster transient responses [3]. This control structure, by achieving a very accurate steady state
and transient control, leads to high dynamic performance in terms of response times and
power conversion [4].
The principle of field oriented control is in recalculation of currents to an equivalent 2
phase machine with direct (d) and quadrature (q) axes for stator and rotor. The input values
for FOC are torque component (aligned with q co-ordinate) and flux (aligned with d coordinate). It is shown on Fig 8.10. As field oriented control is used in both the DSP and FPGA
implementation, I will describe briefly its principle here.
Fig 8.10 - Phasor diagram in d-q coordinate system
The following equations assume that the fixed stator reference frame  is positioned
so that the  axis coincides with phase current iU. This transform is called Clarke transform
[4].
i  iu
i 
(7.2.1)
1
 iv  iu 
3
(7.2.2)
63
Chapter 8. Control of PMSM
Under the assumption that a balanced 3 phase system is used where
iu  iv  iw  0
(7.2.3)
equations (7.2.1) and (7.2.2) will take the form
i  iu
i 
(7.2.4)
1
2
1
iu 
iv 
 iu  2iv 
3
3
3
(7.2.5)
As can be seen from equations (7.2.4) and (7.2.5), the transformation from the 3 phase
system into the 2 phase rectangular  can be done only by measuring two of three phase
currents. This  frame is fixed to the stator.
As later on an inverse Clarke transform will be required for the controller
implementation on both DSP and FPGA, let’s write the required equations directly here
vu  v
v v 
(7.2.6)
3  1 
v   v
2
2
(7.2.7)
vw  vu  vv
The values marked with a
corresponding controller.
(7.2.8)
*
are assumed to be new values calculated by the
Now that  components are known, it is necessary to recalculate them to the rotating
rotor reference frame. For this the rotor position has to be known. It can either be measured
with a sensor or estimated with a sensor-less algorithm. As it is clear from Fig 8.10, the
currents in d-q rotor frame are
id  i sin()  i cos()
(7.2.9)
iq  i cos()  i sin()
(7.2.10)
Where  is the rotor angular position and i and i are currents obtained by the
previous Clarke transform.
This described transformation (called Park transform) creates two currents, id and iq
dependent only on the instantaneous position of the rotor and not dependent on time. As then
the controller is controlling only a DC value the control quality and dynamics will be higher
that it is the case where an AC value would be controlled directly. The required machine
torque and eventually flux is controlled by controlling currents id and iq.
As again an inverse Park transform will be necessary for controller implementation,
let’s write the equations here.
v  vd cos()  vq sin()
(7.2.11)
v  vd sin()  vq cos()
(7.2.12)
where  is the rotor angular position, v*d, v*q are output voltages from the PI
controllers.
64
Chapter 8. Control of PMSM
Fig 8.11 - Block diagram of controller system
The general block diagram of a controller system that uses this approach is shown on
Fig 8.11. The block diagram is common for both DSP and FPGA implementations. It has two
parts. One is the power electronics, the second is the main controller. I have been working on
both controller design and on the design of power electronics in scope of our projects.
The input to the controller is the desired value of machine torque and flux. In case of
an induction machine the desired flux has to be non-zero. In case of PMSM the desired flux is
either zero for full magnetic flux mode or negative for flux weakening mode. The flux
weakening mode allows decreasing the magnetic flux of permanent magnets. This allows
reaching higher speed for the cost of lower achievable torque. As will be seen later, this
feature is much used for high speed machines.
From the block diagram on Fig 8.11 it can be seen that two phase currents iu and iv are
measured. They are recalculated to the i and i currents with the Clarke transform from with
equations (7.2.4) and (7.2.5). Together with the instantaneous rotor position  they are then
used to calculate the values of currents id and iq with equations (7.2.9) and (7.2.10). The
controller compares the difference between the desired value of torque/flux and values of
currents id and iq and produces the corresponding control actions. The outputs of the
controllers are voltages v*q and v*d. The inverse Park transform using equations (7.2.11) and
(7.2.12) produces voltages v* and v*. They are used as inputs to the inverse Clarke transform
block - equations (7.2.6) - (7.2.8). Output voltages v*u, v*v, v*w are used as inputs to the PWM,
this is connected to the power inverter driving the motor.
On the above described vector control principle, I have been participating on projects
with control of both low and high-speed PMSM. One was a project for control of high-speed
PMSM for an electric automotive turbocharger, the other the control of an electric power
splitter for hybrid vehicles.
65
Chapter 8. Control of PMSM
8.3.
High-speed PMSM for an electric turbocharger
The application described here is an electric turbocharger for automotive. The idea
was to test whether it is possible to drive a compressor for a turbocharger with a high-speed
PMSM and to improve system dynamics. Classical turbine driven compressors have relatively
low dynamic. The reason lies in the fact that after fuel addition it takes time to raise the
engine revolutions to make higher the exhaust of gas, to accelerate the turbocharger, to raise
pressure on the compressor and to apply it into inlet tube. The ideal compressor drive should
be therefore controlled with respect to the fuel quantity and engine revolutions. Its dynamics
should quickly follow the engine fuel control.
Turbo compressors are driven mostly by turbine today. Either an electric motor
mounted on the shaft between turbine and compressor can be added or a separate additional
compressor can be driven by special high-speed electric motor. In the first case the velocity of
the motor is the same as the velocity of the turbo compressor. In the second case it is possible
to match the optimal velocity for the compressor with the optimal velocity for the electric
motor.
The results presented here have been published in e.g. [nm13],[nm15],[nm16],[nm18]
[nm19],[nm20],[nm28].
A two pole high speed synchronous motor 2,9kW, 400V, 4200 rad/s, 0,7Nm with
permanent magnet rotor was used with a custom build IGBT converter that I have prepared.
The experimental setup is equipped with an induction dynamometer with rated parameters 2,3
kW, 350 V, 7300 rad/s, 0,3 Nm. Chokes in series with stator winding and inductance of
2,4mH were implemented to diminish stator current pulsation. Synchronous motor has two
pole resolver integrated to determine rotor position. Special electronic unit was developed to
supply the resolver with exciting signal 10 kHz and to evaluate the signals from the resolver.
The unit has 12 bits resolution and discriminates 4096 positions in one motor revolution. The
information on rotor absolute position is transferred via parallel bus after reset. Information
on relative rotor position is transferred in sensor signal form IRC. A DSP system with
TMS320F240 for torque control was used in experiments. Switching frequency was 5 kHz
and discrimination of 4096 positions in one motor revolution was used. The calculation power
of the used DSP has limited the motor revolutions on the testing place. It was possible to
control the motor up to 1200 rad/s with good results. Later a system with controller on base of
Digital Signal Processor TMS320F2812 was used for torque control in whole revolution
range 0 – 4200 rad/s.
The used high-speed motor together with a dynamometer is shown on Fig 8.12. It is now
placed in the laboratory of Department of Electric Drives and Traction on the Faculty of
Electrical Engineering of Czech Technical University in Prague. The custom build IGBT
power inverter in shown on
Fig 8.13. Inverter switching frequency 5 kHz was used in tests with the first control system.
Inverter switching frequency 10 kHz was used in tests with the second control system in
whole revolution range 0 – 4200 rad/s. Calculations in the control structure were performed
with frequency 15 kHz. The time reserve for calculation at PWM modulation with 10 kHz
was approximately 10-20%. To enlarge this reserve the reduction of program and
development support would be required.
66
Chapter 8. Control of PMSM
Fig 8.12 - High speed dynamometer with tested Synchronous motor - [nm19]
Fig 8.13 - Experimental IGBT inverter for high speed drive - [nm13]
67
Chapter 8. Control of PMSM
i [A], |U| [p.u.], f [Hz/100]
12
10
8
id [A]
6
iq [A]
4
|U| [p.u.]
2
f [Hz/100]
0
-2
0
0,5
1
1,5
2
2,5
3
-4
t [s]
i [A], |U| [p.u], f [Hz/100]
Fig 8.14 - Curves of current components id , iq , amplitude reference voltage and revolutions (frequency) during
no load starting up till 4200 rad/s at load torque changing suddenly from 0,11Nm to 0,44Nm - [nm13][nm19]
11
10
9
8
7
6
5
4
3
2
1
0
-1 0
-2
id [A]
iq[A]
|U| [p.u.]
f [Hz/100]
0,2
0,4
0,6
0,8
1
1,2
1,4
1,6
t[s]
Fig 8.15 - Current components id , iq , amplitudes of reference voltage and frequency (revolutions) at no load
starting up till 4200 rad/s at torque 0,44Nm with modulation index correction- [nm13]
A selection of the results is shown on Fig 8.15 and Fig 8.14. The former shows curves
measured at no load starting up till 4200 rad/s at torque 0,44Nm with modulation index
correction (iq=5,7A). Depicted are actual current components iq, id, revolutions in frequency
scale (Hz/100), amplitude of reference voltage introduced into PWM modulator in per unit
values (maximum=10). Fig 8.14 shows that with revolutions (that is with frequency) going up
the ripple of current components id , iq and reference voltage amplitude ripple is going up too.
That is caused by the fact that also the number of controller actions in one period of outgoing
first harmonic voltage from the converter is going down.
68
Chapter 8. Control of PMSM
8.4.
Control for a micro turbine power generator
This project was about building an experimental setup and testing a high-speed power
generator. It is one of the principles with good perspectives for micro energy generation with
a micro turbine. This solution uses a miniature gas powered turbine powered e.g. with natural
gas, biogas, gasoline etc. The turbine is coupled to a generator providing electrical energy.
The advantages over a classical piston based generator are significantly higher efficiency and
smaller dimensions for the same output power. They are also less sensitive for fuel impurities.
However there are also quite some technological challenges. The turbine is running at very
high speeds, usually over 5000 rad/s and with temperatures around 800 °C. To couple such a
turbine with an electrical generator normally means to use some transmission to reduce the
speed and only after the transmission to connect the generator. This however decreases
efficiency and produces mechanical problems. One solution is to connect the generator
directly to the turbine shaft. In this case the generator has to run at the same speed as the
turbine. One promising implementation of the generator is to use a PMSM controlled with an
inverter. There are some emerging PMSM allowing such high speeds. The main problems of
those PMSM are presently mainly the bearings and also the possible damage of permanent
magnets with higher temperatures. Although significant, these issues were however not the
scope of this project. This project focused on challenges of inverter control of a high speed
PMSM generator.
The experimental setup is placed in the laboratories of Department of Instrumentation
and Control Engineering, Faculty of Mechanical Engineering of Czech Technical University
in Prague. The results presented here have been published in [nm3],[nm4], [nm6]-[nm8].
As can be seen form the block diagram on Fig 8.16, the experimental system is
composed of several blocks. The power network voltage is rectified with a converter to DC
voltage. The inverter has to be able to transfer the energy not only from the power network,
but also back. For this reason a standard diode rectifier cannot be used, the structure has to
incorporate transistor switches. At the present time this block has not yet been implemented,
therefore it is dashed in the diagram.
Fig 8.16 - Block diagram of experimental system - [nm4]
69
Chapter 8. Control of PMSM
The DC voltage is supplying an IGBT inverter build for this purpose. The inverter is
using power module SKM75GD124D and IGBT/MOSFET driver SKHI61 both from
Semikron. For the purposes of control and efficiency measurement, the system is equipped
with current and voltage sensors in the DC intermediate circuit and on the three phase output
of the inverter. The inverter is connected to PMSM with the following parameters: type
2AML406B-S from VUES Brno, nominal voltage 560 V, nominal torque 1.2 Nm, nominal
current 11 A, nominal speed 2618 rad/s, maximal speed 4400 rad/s, maximal torque 7 Nm.
The motor is shown on Fig 8.17.
Fig 8.17 High speed PMSM - [nm4]
70
Chapter 8. Control of PMSM
Fig 8.18 - Coupled high-speed motor with automotive supercharger - [nm7]
PMSM start-up and deceleration
id (A/100), iq (A/100), Udc (V), omega (Hz)
800
600
400
200
Id (A)
Iq (A)
0
0
5
10
15
20
25
30
Udc (V)
omega (Hz)
-200
-400
-600
-800
time (s)
Fig 8.19 - PMSM startup and deceleration - requested current iq = 1.6 A
71
Chapter 8. Control of PMSM
PMSM acceleration with iq = 9.5 A
1200
id (A/100), iq (A/100), Udc (V), omega (Hz)
1000
800
600
Id (A)
400
Iq (A)
Udc (V)
200
omega (Hz)
0
0
0,1
0,2
0,3
0,4
0,5
0,6
-200
-400
-600
time (s)
Fig 8.20 - PMSM acceleration- requested current iq = 9.5 A
The coupled motor with an automotive turbocharger is shown on Fig 8.18. During
experiments with high speed motor startup time for an unloaded motor to 4400 rad/s was
measured.
This project is still currently running. Due to mechanical problems during motor turbocharger coupling the motor could be tested only in unloaded state. The coupling and
mechanical improvements of the experimental setup are currently being done at the time of
writing this text.
The conclusion from this chapter is that it is possible to control a high-speed PMSM
with a DSP by maintaining vector control. The calculation requirements are significant and
even for high speed DSP's available today, the limit for this type of control is not far. For our
4400 rad/s motor and TMS 320F2812, the limit was almost reached.
Another tested possibility is to control directly the instantaneous values of phase
currents. This was also researched in this chapter. The advantage of this approach is in lower
calculation power requirements as transformations are not required. On the other hand, the
requested value for the controller is not a constant value. It is sinusoidal and this creates
additional problems for controller setting. It was also shown that controller parameter
adaptation can be used to improve control quality. However, for high dynamic control, the
field oriented control has to be used.
For higher speeds or for induction motors where the motor model has to be calculated,
this DSP would not be sufficient. For those reasons I have decided to prepare a novel
development platform for high-speed machines. This platform is based on Field
Programmable Gate Arrays (FPGA) and should allow increasing significantly the speed limit
of vector control. At the same time it should also allow future development of control
algorithms for sensor-less control. Those algorithms are model based, so usually a simplified
motor model is calculated. This requires additional computation power. The goal is to achieve
at least 7300 rad/s with an induction motor. This is the plan for future projects. The platform
development is described in the following chapter.
72
Chapter 9.FPGA Controller implementation
9. FPGA Controller implementation
As experiments with the DSP controller implementation have shown a digital signal
processor is quite suitable for a field-oriented controller implementation. The described
experiments with high speed motor could be done up to the motors maximal speed of 4400
rad/s. The DSP had sufficient computational power for this speed, but for higher speed its use
could be problematic as it was running almost on the limit. As higher speeds are planed I have
decided to develop a novel field-oriented controller based on FPGA. The replacement of the
DSP by FPGA allows to remove the limitations caused by insufficient computational power
and to push the controller maximal speed to several ten thousands rad/s. It is clear that other
problems – most probably of mechanical nature – would arise. As for the moment we are not
equipped with a motor for such speeds, the controller has been tested only to the maximal
speed of our motor. But the limitation of the controller is now removed and it still provides
much computational power for other task e.g. motor mathematical model calculation for
sensor less control.
The controller is currently based on a Xilinx Spartan 3E development board with some
modifications I have done. The test bench with FPGA can be seen on Fig 9.1. It was first
necessary to add some input and output buffers to separate the FPGA from the power stage
and to convert voltage levels. As the FPGA is working with internal voltages 2,5 V , 1,2 V
and I/O voltage 3,3 V and the power inverter and resolver board are working with I/O 5,0V
level converters have been added.
The measured Iu and Iv currents from the LEM sensors have current output. The rms
value of current 50 A in sensor input corresponds to current 25 mA on the output (rms). As
the current can be both negative and positive as well and the development board converter is
working only with positive voltages in the range 0.4 – 2.9 V it was necessary to add an
amplifier and voltage converter.
Fig 9.1 – FPGA controller, resolver board, external inductance and tested motor
73
Chapter 9.FPGA Controller implementation
The amplifier TS27L2 [67] is shifting the voltage to the desired range. Current zero
corresponds to voltage 1.65 V for the amplifier. After the external amplifier there is a
programmable gain amplifier LTC 6912 [68] placed on the board. This is set to gain -10
during the initialization process.
The amplifier was calibrated with DC current from an external power supply to get the
dependence of conversion result on LEM current. As the TS27L2 amplifier is connected as an
inverting amplifier, the input voltage is inverted. The amplifier is not a rail-to-rail type, so the
output voltage can only be below a certain level, approximately Vcc – 0.5 V. Therefore the
negative input current is limited to approximately 11 A. This is the motor nominal current. On
the positive side, the amplifier limit is zero voltage so the limitation is higher. As this circuit
is not supposed to work with higher currents, those limitations are not an issue. The maximal
rms value of sensors current is 50 A. The external amplifier is powered directly from the
development board. Input current of 1 A corresponds to conversion results of approximately
760 decimal. The amplification and zero voltage of the external amplifier are adjustable. The
signal then goes to the A/D converter input. Channel 0 is used to measure Iu current and
channel 1 is measuring Iv current.
The A/D converter is a 1.5 MSPS device with simultaneous sampling on two input
channels. The conversion result is read through a serial interface. The communication
protocol is a nonstandard SPI like communication. The connection of the internal
programmable gain amplifier and A/D converter is on Fig 9.2.
Fig 9.2 – Detailed View of Analog Capture Circuit [72]
The result is a 14 bit signed 2´s complement number. So the result can be in the range
-8192 to +8191. An example of the FPGA <-> AD communication is shown on Fig 9.3. The
communication with the amplifier and A/D is hardware based an independent on other blocks
in the design as will be explained later. The conversion is started by the falling edge of the
AD_conv signal. The data from the A/D converter is coming on the SPI_MISO line and is
sampled on the falling edge of SPI_SCK. The sample rate is set by the SPI_CLK signal
frequency and is 2.7 MHz. This is a little below the A/D converter maximal sampling
frequency of 3.0 MHz.
74
Chapter 9.FPGA Controller implementation
Fig 9.3 – Example FPGA <-> A/D converter communication
The PMSM rotor position and speed is measured with the previously described
resolver card. In contrast to the DSP, the FPGA is using the parallel interface output from the
resolver chip as I was not limited by the number of input pins. The resolver signals are
separated from the FPGA by a level converter running on 5.0 V input and 3.3 V input. It was
required to do a slight modification on the previously described resolver board to
accommodate both DSP and FPGA. A pull down resistor was added to the SOE input and the
direct connection to DVDD disconnected. Also a pull up resistor was added to the RDVEL
signal. This modification assures that both DSP and FPGA controllers can be connected by a
simple change of wiring. The DSP and FPGA controller cannot work at the same time. When
DSP is used FPGA has to be disconnected and vice versa.
Fig 9.4 –Resolver <-> FPGA communication [77]
75
Chapter 9.FPGA Controller implementation
The resolver communication is based on the recommended timing. The meaning of the
signals is the following. The nSAMPLE signal starts the reading cycle. Data is read after the
nCS and nRD signals are on low level. The RDVEL signal selects between position or
velocity. Both are read from the resolver by the FPGA. The resolution is 12 bits, i.e. 360°
corresponds to 4096 positions. The FPGA uses 16 bits for the calculations. One reading cycle
takes 9.18 μs. I believe it should be possible to replace the entire resolver card by an FPGA
implementation in the future using direct digital synthesis.
The requested input is given by a rotary encoder from the development board. The
input is read independently on other blocks and debounced. There is a limiter on the rotary
encoder internal counter. It is allowed to count from 1 to 255 without overflow so sudden
torque, current or speed changes are eliminated.
The block diagram of the FPGA controller implementation is shown on Fig 9.8. It is
implemented in Xilinx ISE 13.3 as a schematic representation. The individual blocks are
manualy coded in VHDL. I have also considered the implementation in Xilinx System
Designer for DSP in Simulink, but as I have figured out during the experiments it is unable to
generate correctly the implementation constraints file when not in hardware co-simulation
mode.
The whole controller is composed of many blocks. I will start the description in the top
left corner. Unless otherwise noted, the hardware is clocked with a 50 MHz clock. The block
evaluate_error is used to guard the controller from hardware and software errors. The error
signal inputs, e.g. Iu or Iv are coming from the AD converter and contain measured value of
current Iu and Uv. When a maximal value is exceeded, the hardware is blocked and a reset is
required. This protects the motor from over currents. The same is true for currents Id, Iq and
for saturations in the controllers. Effort has been done to match the error numbers to error
numbers used in the DSP controller implementation. The reset has to be done by changing the
state of both switches SW0 and SW3 on the board from high to low and back. Then the error
is reset and the controller can continue.
The error output is connected to a Picoblaze embedded microprocessor. The
microprocessor is coded in VHDL and represents a good way of implementing sequential or
slow functions in FPGA. Here it is used to inform the user through an LCD display. Once the
LCD is initialized, it provides information about measured currents Iu, Iv, measured rotor
position and speed from the resolver card, calculated values of currents Id and Iq and the error
number. The display is updated with a period of 0.5 s, as only four signals can be displayed in
a given time, the screen is switched with SW1. SW2 is currently not used. The Picoblaze core
also switches off the strataflash and platform flash on the board as they share the SPI bus with
the amplifier and A/D converter and are not used in this design. The microprocessor is used
only to communicate with the user it does not control anything else. The rest of the controller
is entirely hardware based to provide maximal speed.
The LTC6919 amplifier is controlled with the corresponding block in the diagram. It
produces SPI data and clock to set the boards internal programmable gain amplifier to gain
10. As the amplifier and A/D converter share the SPI_CLK signal the selection whether the
amplifier of A/D converter is accessed is made by the Picoblaze core with the LTC6912_ce
signal. This signal is held high during LCD initialization and then held low. This takes about
50 ms. The initialization done the LTC1407 A/D converter takes control of the SPI_CLK and
reads periodically the input channels. The same signal also controls the reading from the
resolver through the parallel interface.
76
Chapter 9.FPGA Controller implementation
The resolver block is accessing the resolver hardware through the parallel interface.
Speed or position is selected with the RDVEL signal high or low. As the input data is inverted
in the interface hardware, a software 12 bit inverter is added. The output position and speed is
available on separate busses either in 16 or 12 bit. The 12 bit signal is used in the controller,
the 16 bit signals are connected to the Picoblaze core for user information through caster
blocks to 16 bits for convenient reading. They are not used for the calculations of controllers.
The principal part of the controller is placed around the four PID controllers in the
right side of the block diagram.
The measured values of currents Iu and Iv go through the Clarke transformation and
form currents Ialfa and Ibeta in the stator reference frame. By adding the information about
position from the resolver block currents Id and Iq are calculated in the Park transformation
block. The Park transformation is created with a help of a sinus and cosinus ROM table with 8
bit output. This proved to be sufficient for this application. The example of Park transform
implementation is on Fig 9.5. It uses Xilinx IP Core multipliers and manually coded
saturating adders.
The latency indicated in the figure shows the number of clock cycles needed to
perform the operation. For all blocks this latency is the basic without any optimization and it
could be decreased further if required. The information about latency will be later used to
calculate the controller performance and to compare it with DSP controller performance.
Signals Id and Iq the continue to the Id and Iq PID controllers. Although called PID this is in
fact only a PI implementation as the derivative component is not required for this application.
The PID controllers are protected against saturation, they signal it to the error block which
can either take an action or ignore it as specified by its setting.
An example of implementation of the PID controller is on Fig 9.6. Care was taken to
synchronize clock cycles between the P and I components so that corresponding input are
calculated together. The clock cycle synchronization is the purpose of delay block. For the
time being the controller constants are fixed during compilation time, but they could be also
entered from the Picoblaze core in the future.
The output of the Id and Iq PI controllers is fed through the inverse Clarke and Park
transforms to the PWM generator. It uses a saw tooth generator based on an up/down 8 bit
counter and three 8 bit comparators that are producing the control signals for TOPx and
BOTx transistors in the power module. The module dead time is not considered here but its
including in the controller could improve its properties in the future. The PWM block is
shown on Fig 9.7. This block is one of the few in the design running of clock frequency of 5
MHz.
The output PWM signal frequency is set to 10 kHz for the time being to be the same as
the output frequency of the DSP controller. It can be set to a higher value if necessary.
The higher level loop is the field weakening controller and the speed PI controllers.
The field weakening controller makes sure that the motor nominal current is not exceeded
when higher speed is necessary. The requested speed is coming from the development board’s
rotary encoder and is shown on LED LD0 – LD7 as well.
77
Fig 9.5 – Block diagram of Park transform
78
Fig 9.6 – Example of PI controller FPGA implementation
79
Fig 9.7 –PWM FPGA implementation
80
Chapter 9.
FPGA Controller implementation
The implementation results are the following. The FPGA controller itself is running
currently on 50 MHz but the speed can be increased to 150 MHz. The limiting factor is the
Picoblaze core that is capable to run only on 98 MHz. Therefore the speed is kept on 50 MHz
to the time being. The calculation takes 22 clock cycles. For frequency 50 MHz (20 ns) this is
440 ns. The DSP implementation needed 66 μs. As can be seen the FPGA controller is
significantly faster, around 150 times. Considering that no optimization of the FPGA
implementation has been done, there is a good chance that if required this could be increased.
Only by removing the Picoblaze core, the speed increase could be of another 3 times making
it around 450 times faster than the DSP. The above given data are valid for implementation of
Id and Iq controllers only. When two other PI controllers are added, for flux weakening and
speed, an internal loop is created slowing the design significantly. The speed is then around
15MHz. Nonetheless this is still about 40 times faster than the DSP implementation.
From those results it can be seen that the FPGA implementation of the PMSM
controller removes the limitations imposed by the DSP implementation and that in will allow
us to reach higher speed with future motors. In fact, the FPGA is so fast that even a sensor
less control could be implemented as it allows calculating a real time model of the motor.
This could be required especially for high speed induction motor control. In fact when
pipelining is implemented, there is a chance to produce an controller result in every cycle and
to speed even more the design.
The FPGA implementation is using around 25 percent of the FPGA leaving plenty of
space for future development. One of the goals for the near future is to provide on-line signal
output to allow capture of motor currents and controller internal states for comparison with
DSP. The implementation results are summarized in Tab. 9.1 where a selection of the
compilation results is presented.
Tab. 9.1 - Device Utilization Summary
Logic Utilization
Used
Available
Utilization
Number of Slice Flip Flops
1,683
9,312
18%
Number of 4 input LUTs
1,383
9,312
14%
Number of occupied Slices
1,161
4,656
24%
Total Number of 4 input LUTs
1,439
9,312
15%
Number of RAMB16s
2
20
10%
Number of BUFGMUXs
6
24
25%
Number of MULT18X18SIOs
14
20
70%
81
Fig 9.8 –Block diagram of FPGA controller implementation
82
Chapter 10. Sensor-less control
10. Sensor-less control
As in many cutting edge applications there is usually some bottleneck that limits
further development. I have shown in this work that it is possible to develop an FPGA based
controller for PMSM. This design allows achieving much higher speeds that a DSP controller
by maintaining the control quality as it uses field oriented control. So I have solved the
bottleneck of insufficient calculation power in the controller. Now the next problem
component is the speed - position sensor. Only very few (if any) sensors are capable to work
reliably with a high speed machine. In the test system a resolver was used. The idea is
therefore to replace the sensor with a sensor-less approach. The controller has to include the
internal model of PMSM and estimate the rotor position with an observer. The model
calculations need to be performed at a very high sampling frequency. For this reason I believe
it to be an ideal task for FPGA.
In this chapter I am presenting some possible approaches for sensor-less control found
in several papers. It is the preparation for future work and should show what methods could
be suitable for FPGA implementation. I have selected some of the ideas for this chapter.
10.1.
Stator and rotor flux linkage estimation
Fig 10.1 - Space vector diagram - adapted from [21]
The procedure from [21] is based on the space vector diagram on Fig 10.1. The
diagram shows the general situation in flux weakening mode. In full magnetic flux mode
current id is zero. In this diagram s is the stator flux linkage vector, s and s are the
corresponding components in the stator  reference frame, sd and sq are the
corresponding components in the rotor d-q frame,  is the angle of stator flux linkage. r is
the permanent magnet rotor flux linkage, r is the angle of rotor flux linkage, β is the torque
angle, vs is the stator winding voltage with its components in the d-q rotor frame and is is the
stator current with its components in the d-q rotor frame.
From Fig 10.1 the flux linkage is
 d   sd   r  Ld  id   r
(10.1.1)
 q   sq  Lq  iq
(10.1.2)
where Ld and Lq are inductances in d-q axes.
83
Chapter 10. Sensor-less control
The situation for current and voltage can be described with a phasor diagram on Fig 10.2.
Fig 10.2 - Synchronous motor diagram of phasor for torque control
The stator circuit can be described as
ˆ
d
s
ˆ   R  Iˆ
VˆS 
 j
s
s
dt
(10.1.3)
and the components of the stator voltage vs can be described as
vd 
vq 
d  sd
  sq  Rs  id
dt
d  sq
dt
(10.1.4)
  sd   Rs  iq
(10.1.5)
where  is angular speed of stator voltage and Rs is stator winding resistance.
The created torque is proportional to stator current and can be described as
Tm 
3
p p   d  iq   q  id 
2
(10.1.6)
where pp is the number of pole-pairs
Torque from equation (10.1.6) created with current i has to be in accordance to load torque,
damping and inertia as described by the motion equation
Tm  J
dm
 Bm  TL
dt
(10.1.7)
where m = /pp is mechanical speed, J moment of inertia, B damping constant and TL
load torque.
The torque angle  is the angle between the stator flux linkage s and rotor flux linkage r
r    
(10.1.8)
The first described algorithm is based on the estimation of stator flux linkage vector. From
(10.1.4) and (10.1.5) the stator flux linkage components in d-q frame can be expressed
84
Chapter 10. Sensor-less control
d  sd
 vd   sd   Rs  id
dt
d  sq
dt
(10.1.9)
 vq   sq  Rs  iq
(10.1.10)
Equations (10.1.9) and (10.1.10) in stator d-q frame can be rewritten to the  rotor
frame and since in this frame  = 0 they are simplified to
d  s
 v  Rs  i
dt
d  s
dt
(10.1.11)
 v  Rs  i
(10.1.12)
The components of stator flux linkage components in  frame can therefore be expressed as
 s    vs  Rs  is dt
(10.1.13)
 s    vs  Rs  is dt
(10.1.14)
The searched stator flux linkage angle can then be expressed from (10.1.13) and (10.1.14) as
 
  arctan  s 
  s 
(10.1.15)
The rotor speed can then be calculated from (10.1.15) as

d
dt
(10.1.16)
or in a discrete system
 k  
  k     k  1
(10.1.17)
Ts
where Ts is the sampling period of the discrete system
Another approach is to use the rotor flux linkage to estimate rotor position. "The angle
of the rotor linkage vector is equal to the angle of stator flux linkage vector minus the torque
angle." [21]
Equation (10.1.6) can be expressed also in sampled time as
Tm  k  
3
p p   s  k   is  k    s  k   is  k  
2
(10.1.18)
The torque in a DTC system is calculated as
Tm  k  
3
1
p p  s  k   r  k  sin    k  
2
L
From equations (10.1.18) and (10.1.19) the load angle  can be expressed as
85
(10.1.19)
Chapter 10. Sensor-less control

2  L T  k 


 3 p  s  k   r  k  


  k   arcsin 
(10.1.20)
r    
(10.1.21)
The estimated speed is then given as
 k  
  k     k  1
Ts

  k     k  1
Ts
(10.1.22)
The algorithm block diagram is shown on Fig 10.3. In this block diagram two blocks
are added compared to the standard block diagram on Fig 8.11. It is the block of decoupling
and the angle and speed observer.
This algorithm shows much potential for FPGA implementation as it is of integral type
and therefore should be able to work in a noisy environment of an industrial application.
10.2.
PI compensator based estimation
Fig 10.3 - Block diagram of sensor-less control with angle and speed observer - adapted from [19]
The decoupling block limits the dependence of voltage vq on voltage vd and vice-versa. The
decoupling feed-forward terms Vds_ff and Vqs_ff are given as
Vds _ ff  Rs  id  L  *  iq
(10.1.23)
Vqs _ ff  Rs  iq  L  *  id  *   f
(10.1.24)
where Rs is stator resistance, L is stator inductance, * is estimated rotor speed and λf
is the back-emf constant of PMSM.
The voltage in the estimated reference frame is [19]
*
vds
 Rs  id*  Ls  *  iq*    f sin err
(10.1.25)
*
vqs
 Rs  iq*  Ls  *  id*  *   f  cos err
(10.1.26)
where Θerr is the angle error between the real angle of the rotor  and estimated angle *. The
authors of [19] used then a PI compensator based on (10.1.23) and (10.1.25). The PI
compensator can be seen on Fig 10.3




vdse _ error  Rs  idse  ids  Ls  re  iqse  iqs  r  f sin err
86
(10.1.27)
Chapter 10. Sensor-less control
From equation (10.1.27) it can be seen that if the system is controller with a good controller,
the difference between the estimated and real currents goes to zero and due to the PI
compensator for , this also goes to zero. Therefore equation (10.1.27) can be simplified to
vdse _ error  r  f sin err  r  f err
(10.1.28)
The described method is robust against noise as it uses integration instead of derivation to
obtain the angular speed and position.
10.3.
High frequency signal injection
Another approach to sensor-less control is presented in paper [20].
This approach uses the filtering capability of the motor. The motor is power with
standard PWM inverter and pulses; a high frequency signal is injected to the input signal. The
motor acts as a filter, whereas the high frequency signal is measured. From the high frequency
voltage, motor parameters like rotor position can be estimated. For high frequency the motor
model is simplified to
dihf _ dq
vhf _ dq  L
(10.1.29)
dt
where L is the leakage inductance and vhf_d-q and ihf_d-q are high frequency voltage and
current in the rotor d-q reference frame.
As the injected high frequency signal with angular frequency c is vhf_d-q = vhf_d-q ejc t, the
high frequency current is [20]
ihf _ dq   j
vhf
2 c    L d L q
 L
 L q  e
d
j c  t
  L q  L d  e
 j c  t
 (10.1.30)
After the transformation to the stator stationary reference frame  the current is
ihf _    j
vhf
2 c    L d L q
 L
d
 L q  e
j c t
  L q  L d  e
 j c  2 t
 (10.1.31)
The desired extraction of the rotor position dependent component with frequency -c+2 is
done by multiplication with another high frequency signal with frequency +c+2
ic  2r   j
vhf
2 c    L d L q
 L
d
 L q  e
j  2c  2 t
  L q  L d  e
 j  2c  2 t
 (10.1.32)
and the produced low frequency signal is filtered with a low pass filter


LPF ic  2   j
vhf
2 c    L d L q
 L
q
 L d  e
 j  2c  2 t

(10.1.33)
Only the real part is now taken and this yields

 
LPF ic  2 
c
vhf
   L d L q
sin   
For small position difference sin ()  
87
(10.1.34)
Chapter 10. Sensor-less control

 
LPF ic  2 
vhf
c    L d L q
 
(10.1.35)
where  is the error between the actual and estimated angle.
Another described possibility of sensor-less position estimation described in [20] takes the
multiple of  current components
ihf _  
ihf _  
vhf
2c L d L q
vhf
2c L d L q
 L
 L q  sin ct    L q  L d  sin ct  2 t 
 L
 L q  cos ct    L q  L d  cos ct  2 t 
d
d
LPF  i  i   K1K 2 sin  2 t 


(10.1.36)
(10.1.37)
(10.1.38)
where
K1 
vhf
2c L d L q
L
d
 L q  K 2 
vhf
2c L d L q
L
d
 L q 
(10.1.39)
To obtain the rotor frequency a frequency shift signal processing method is used by
multiplying the signal with another signal with angular frequency h as described with
equation
ih  K1K2  sin  2 t   cos ht   cos  2 t   sin ht    K1K 2 sin  h  2  t  (10.1.40)
The instantaneous signal frequency is now estimated using the Short Time Fourier Transform
ridges algorithm. The authors have tested the described algorithm in simulation with injected
voltage amplitude 15 V and frequency 1.5 kHz.
In this chapter I have analyzed the properties of thee selected sensor-less rotor position
estimators. It was the stator or rotor flux based estimator, PI compensator and high-frequency
signal injection.
From the analysis of selected sensor-less algorithms I came to the conclusion that the
most promising is the PI compensator type algorithm as it should be able to work in a noisy
environment of an industrial application. The stator or rotor flux estimator could be also used,
especially the rotor flux estimator. Those methods require the calculation a simplified
mathematical model of the machine. As in my implementation of FPGA controller there is
enough space and computational power for the sensor less approach, I am considering this
implementation in the near future. The use of the signal injection methods remains
questionable. The method is more suitable for salient pole machines; permanent magnet
machines have usually non salient poles. Therefore the dependency of signal properties on
position will be less significant. Also for the high-speed machine the injected signal would
have to be with a very high frequency. The usual frequency of the injected signal is at least
ten times higher than the usual PWM switching frequency. For a high-speed machine, where
the PWM frequency is around 15 kHz, this would represent a frequency about 150 kHz. For
the reasons of switching losses, this is hard to achieve. Also the estimation of instantaneous
signal frequency using the short time Fourier transforms could be a promising way.
88
Chapter 11. Thesis contributions, conclusions and future work
11. Thesis contributions, conclusions and future work
This thesis presents the experiments and theoretical developments of projects I have
been working on in the past few years. They are all focused on special purpose permanent
magnet machines. I have been working on many details in the field, starting with a review of
current technology state to find out current limits and to improve the technology.
From the made review of current state it was clear, that the problems and theirs
solution in the field of high-speed machines, control, measurement, modeling and sensors-less
control are demanded in the industry. The applications are wide ranging from turbochargers,
micro-turbine power generators, hybrid vehicles, fuel cells, spindles to cryo-coolers or cogeneration units. The motivation for high-speed machine development is mainly the high
power density of such machines. Following the current state review I found out that problems
within the field of measurement, modeling and mostly control of high-speed machines are
currently present. In the field of modeling, the current models for standard low speed
machines did not take into account parameters like eddy current losses, bearing losses, air
friction etc. that can be significant for high-speed machines. In the field of control algorithms,
high-speed machines were controlled without any feedback with V/f. For this reason, they
have lower dynamic response compared as if they would be controlled with field oriented
control algorithms. All the present applications were controlled with a DSP that does not
allow the application of FOC for high-speed machines as it has high computational power
demands. Last but not least, there was a problem with the measurement of rotor position for
high speed. For high speeds, the employment of a position sensor is not practical, as it limits
the maximal speed and complicates construction of the machine. The solution is sensor-less
control, but it requires the calculation of a simplified mathematical model of the machine. For
those reasons it is also limited for high speeds and current versions of controllers of highspeed machines are working with an open loop V/f control.
The origin of the herein described projects lied within the needs coming from the
automotive and energy production industry when I have been working with the Josef Božek
Research Centre of Engine and Automotive Engineering, a Czech Technical University in
Prague based research project.
Another research project described here is the project Development of Environmental
- Friendly Decentralized Power Engineering headed by prof. Hrdlička, the dean of the Faculty
of Mechanical Engineering. In this group I am currently still working on the development of a
high-speed micro-turbine generator with a high-speed permanent magnet machine. This
research project is supposed to finish at the end of 2013.
From the needs of those projects several areas have been identified to work on. In
principle one of them was a high-speed machine; the other was a special purpose synchronous
machine, the electric power splitter. Those projects required a substantial amount of
development work in the field of hardware, software, control system and modeling. I have
been working on the selected issues of those problems.
I have been working on a simulation model of a high-speed permanent magnet
synchronous motor for the purposes of algorithm testing, verification and control system
design. Apart from the traditional motor properties considered in ordinary low speed model, I
added some specific issues for high-speed machines. I also identified the parameters of a real
high-speed permanent magnet motor that was used for our experiments.
I have shown the specifics of high-speed machine modeling. Compared to standard
low speed machine models, more parameters have been taken into consideration like air
89
Chapter 11. Thesis contributions, conclusions and future work
friction or bearing losses. For high-speed machines, especially ones with lower power rating,
around 100 W those losses can represent around 20 percent of the rated power and it is not
possible to neglect them any longer in mathematical modeling. For medium power high-speed
machines, those losses can be neglected only when the speed is relatively low or the lower
model precision is sufficient. To improve model precision more parameters like eddy current
losses, reluctance torque etc. can also be taken into consideration.
For the successful development of a high-speed motor controller system, I have been
working towards a suitable test setup. The work started with a selection and preparation of a
PMSM rotor position measurement system. For all PMSM control algorithms, the information
about instantaneous rotor position is essential for a control system. Although there were also
some sensor-less estimator at the time, theirs function was not reliable for high-speed
machines and required a high amount of computational power. For this reason, the test setup
was created with a position sensor approach. More than one method was examined for rotor
position sensing, including direct, indirect and phase error methods. Based on this, I have
designed, developed and tested a special rotor measurement unit.
The special rotor measurement unit I have developed, build and tested evaluates the
resolver signal with 4096 position per one revolution. This device was further used in the
development of an experimental setup with high-speed PMSM. The developed unit provides
means of parallel and serial communication to accommodate both the DSP and FPGA
controller systems described in this thesis. It also provides error signal to diagnose the current
state of the resolver and to detect errors. It is able to work up to speed 6000 rad/s. The results
have been published in [nm32][nm33][nm34].
I have also designed and developed a special measurement unit to measure voltage,
currents and power in PWM circuits. Standard devices available on the market did not allow
measuring the parameters of our circuits in an economical way. A unique experimental device
was designed, tested and build in multiple exemplars. The device allowed measuring all the
required electrical parameters of PWM circuits even for high frequencies necessary for highspeed machines. Components from this unit were then employed in the test setup for highspeed machines. The results have been published in [nm30].
An important research and design was made in the field of a power inverter for highspeed machines. The previously available power inverters did not allow various control
algorithm testing, they were proprietary devices of the manufactures and no modification was
allowed. For this reason I have developed a power inverter platform that allows testing of all
our algorithms. Without this experimental power converter or with a commercial power
inverter, those tests would have been impossible. The inverter allowed testing of various
control algorithms and various switching frequencies as well. It is a robust novel device and
can be used both in laboratories and in industrial applications. The results have been
published in [nm13][nm14][nm15][nm16].
After the test setup was completed, I have been working on various problems of
control of high-speed machines. Several ways of control have been explored, including
control of instantaneous current values or field oriented control. The advantage of controlling
instantaneous values is in lower calculation power requirements as transformations are not
required. On the other hand, the requested value for the controller is not a constant value. It is
sinusoidal and this creates additional problems for controller setting. It was also shown that
controller parameter adaptation can be used to improve control quality. However, for high
dynamic control, the field oriented control has to be used.
90
Chapter 11. Thesis contributions, conclusions and future work
The calculation requirements of FOC are significant and even for high speed DSP's
available today, the limit for this type of control is not far. For our 4400 rad/s motor and TMS
320F2812, the limit was almost reached.
The results were wide and detailed and allowed to choose the appropriate algorithm
for high-speed machines with fast dynamics. The results have been published in [nm1][nm12], [nm17]-[nm28].
From the experiments with the DSP controller system it became clear that if higher
speeds would be required, a different controller system would have to be developed. The
digital signal processor used was not fast enough to provide field oriented control for highspeed machines. No available DSP has enough calculation power for a really high-speed
machine and field oriented control. For this reason I have developed a unique, novel and
innovative controller based on FPGA that solves those problems.
The research results are the following. The FPGA controller itself has sampling clock
currently on 50 MHz but the speed can be increased to 150 MHz. The calculation takes 22
clock cycles. For frequency 50 MHz (20 ns) this is 440 ns. The DSP implementation needed
66 μs. As can be seen the FPGA controller is significantly faster, around 150 times.
Considering that no optimization of the FPGA implementation has been done yet, there is a
good chance that if required this could be increased even more. The above given data are
valid for implementation of Id and Iq controllers only. When two other PI controllers are
added, for flux weakening and speed, an internal loop is created slowing the design. The
achievable speed is then around 15MHz.
My novel and innovative design is able to achieve a speed increase of at least 40
times compared to the previous DSP controller. So thanks to my work, the future is
open for tests above the DSP speed limit. The DSP speed limit 4400 rad/s is now removed,
if a suitable motor is available.
From those results it can be seen that the FPGA implementation of the PMSM
controller removes the limitations imposed by the DSP implementation and that in will allow
us to reach higher speed with future motors. In fact, the FPGA is so fast that even a sensorless control could be implemented as it allows calculating a real time model of the motor.
This could be required especially for high speed induction motor control. In fact when
pipelining is implemented, there is a chance to produce a controller result in every cycle and
to speed even more the design.
After the development of the novel FPGA high-speed motor controller, many ways are
open for future development. For high-speed machines the employment of rotor position
sensor is very problematic from motor construction point of view. For this reason I also have
investigated various sensor-less rotor position estimation methods. They are all model based
and require a calculation of the simplified machine model in real time. Due to short
calculation time for high-speed machine control, its employment was previously not possible
in DSP system for high-speed machines and field oriented control. Thanks to my unique
FPGA platform controller, theirs use is now possible.
From the analysis of selected sensor-less algorithms I came to the conclusion that the
most promising is the PI compensator type algorithm as it is able to work in a noisy
environment of an industrial application. The stator or rotor flux estimator could be also used,
especially the rotor flux estimator. Those methods require the calculation of a simplified
mathematical model of the machine. As in my implementation of FPGA controller there is
enough space and computational power for the sensor-less approach, I am considering this
implementation in the near future.
91
Chapter 11. Thesis contributions, conclusions and future work
The use of the signal injection methods remains questionable. The method is more
suitable for salient pole machines; permanent magnet machines have usually non salient
poles. Therefore the dependency of signal properties on position will be less significant. Also
for the high-speed machine the injected signal would have to be with a very high frequency.
The usual frequency of the injected signal is at least ten times higher than the usual
PWM switching frequency. For a high-speed machine, where the PWM frequency is around
15 kHz, this would represent a frequency about 150 kHz. For the reasons of switching losses,
this is hard to achieve with a current IGBT power inverter, but it could be done with a
MOSFET inverter.
The future logical steps are the improvements of the power inverter so that it can
sustain higher PWM switching frequencies, at least 20 kHz. This is possible due to recent
innovation in the field of MOSFET semiconductors. Power MOSFETs for high voltage
applications up to 1.2 kV became recently available. Theirs employment would reduce losses
in the inverter and reduce its size and weight.
An open question for the future remains whether it is possible to build an own highspeed PMSM in our conditions. As shown by some examples from other universities this is
not an impossible task.
Ultra high speed machines have a very promising future. Speeds will increase too
much higher levels as this allows the construction of smaller machines with high power
density. An example of future industrial applications of high speed machines is PCB drilling.
It is shown in [63] “The smallest drilling diameters in actual PCB drilling machines are 50
μm…. there will be a need for drives providing speed of more than 300 000 rpm”.
So it is my belief that high speed machines and theirs high performance control will
become a hot topic in the near future with many interesting applications.
All the herein presented results have been published mainly on international
IEEE conferences in many papers that I have either authored or co-authored. I have in
total authored or co-authored more than 30 papers on the thesis subject and more than
60 other papers on related subjects.
The herein presented controller high-speed FPGA controller is currently
reviewed for a patent application.
92
Chapter 12. References
12. References
The references are arranged into two sections. The first section is a list of papers that I
have authored or co-authored relating either or not to the habilitation thesis sorted according
to year of publication. Those papers are labeled [nmXX] where XX is the paper number. The
second section is a list of references used for the development of the herein described
projects. Those papers are labeled [XX] where XX is the paper number. This allows to
distinguished between own and referenced papers.
12.1.
External references on thesis subject
[1] RIPKA P. TIPEK A.: Master Book on Sensors, CTU-Czech Technical University in Prague, ISBN 807300-129-2.
[2] Companies presentations SEW Eurodrive, Texas Instruments, Atlas Copco, Analog Devices, Atas Náchod
[3] An Introduction to Vector Control of AC Motors Using the V850 [online], November, 2002, Vol.12, No.
U16483EE1V0AN00, Available on <www2.renesas.eu/_pdf/U16483EE1V0AN00.PDF> [accessed 6.12.2011]
[4] Field Orientated Control of 3-Phase AC-Motors [online],
<www.ti.com/lit/an/bpra073/bpra073.pdf> [accessed 6.12.2011]
February,
[5] Sensorless Field Oriented Control of PMSM Motors [online],
<ww1.microchip.com/downloads/en/.../01078A.pdf> [accessed 6.12.2011]
1998,
2007,
Available
on
Available
on
[6] ČEŘOVSKÝ, Z.: Power electronics in automotive hybrid drives. 10th International Power Electronics and
Motion Control Conference – EPE-PEMC 2002, CD-ROM – T5-013, Dubrovnik 2002. ISBN953-184-046-6.
[7] NOVÁK, J. - GREGORA, S. - SCHEJBAL, V.: Hardware for Real - Time AC Drive Analyses.
International Conference on Electrical Drives and Power Electronics, CD-ROM – T4.3 C14, s. 380 – 383,
Vysoké Tatry, Slovensko 2003. ISBN 80–89 114–45-4
[8] NOVÁK, J. - GREGORA, S. - SCHEJBAL, V.: Study of Methods for Induction Machine Torque
Monitoring - 10th International Power Electronics and Motion Control Conference – EPE-PEMC 2002, CDROM – T7-020, Dubrovnik 2002. ISBN953-184-047-4.
[9] NOVÁK, J. - SCHEJBAL, V.: The possibility of mathematical model utilization for real-time analyses of
induction machine. Acta Technica CSAV, vol. 48, n. 4, ISSN 0001-7043 – pp. 411 – 426
[10] HOLTZ, J.: Pulse Width Modulation – A Survey, IEEE Trans. on IE 39, No. 5, Dec. 1992, pp. 410 – 419
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PMSM - THEORETICAL ANALYSIS. In Sborník odborného semináře NOVÉ METODY A POSTUPY V
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Ústav přístrojové a řídicí techniky FS ČVUT, 2011, p. 59-64.
2010
[nm8] Novák, M. -Chyský, J.: MICROTURBINE POWER GENERATOR WITH HIGHSPEED
PERMANENT MAGNET SYNCHRONOUS MOTOR. In Proceedings of The 9th International Conference
Process Control2010 [CD-ROM]. Pardubice: Universita Pardubice, 2010, p. 1-6. ISBN 978-80-7399-951-3.
[nm9] Novák, M. - Novák, J.: CONTROL OF AN ELECTRICAL POWER SPLITTER IN A HYBRID
TRACTION PROPULSION SYSTEM. In Proceedings of The 9th International Conference Process
Control2010 [CD-ROM]. Pardubice: Universita Pardubice, 2010, p. 1-9. ISBN 978-80-7399-951-3.
[nm10] Novák, M. - Novák, J. -Čeřovský, Z. - Uhlíř, I.:Electric Power Splitter Pulse Rectifier Control in a
Hybrid Propulsion System. In Proceedings of the 14th EPE-PEMC Conference 2010. Skopje:International
Council on Large Electric Systems Macedonian National Commitee, 2010, p. T4-7-T4-11. ISBN 978-14244-7854-5.
[nm11] Novák, M. -Chyský, J. -Stanke, O.:High-speed Micro Turbine Power Generator. In Nové metody a
postupy v oblasti přístrojové techniky, automatického řízení a informatiky 2010 [CD-ROM]. Praha: Ústav
přístrojové a řídicí techniky FS ČVUT, 2010, ISBN 978-80-01-04625-8.
[nm12] Stanke, O. - Novák, M. -Chyský, J.:Control of small energy supply. In Sborník přednášek z technické
konference ARaP 2010. Praha:Dimart, s.r.o., 2010, s. 111-116. ISBN 978-80-903844-5-3. (inCzech)
99
Chapter 12. References
2009
[nm13] Cerovsky, Z. - Novak, J. - Novak, M. et al.: High Speed Synchronous Motor Control for Electrically
Driven
Compressors
on
Overcharged
Gasoline
or
Diesel
Engines
In Iecon 2009 35th Annual Conference of Ieee Industrial Electronics, Vols 1-6 Pages:1079-1084
Published:2009
[nm14] Novak, L.; Novak, J.; Novak, M.; et al.: Electrically-Driven Compressors on Turbocharged Engines
with High-Speed Synchronous Motors In 2009 8th International Symposium on Advanced
Electromechanical Motion Systems Pages:184-189Published:2009
[nm15] Čeřovský, Z.-Novák, J.- Novák, M.: High Speed Synchronous Motor Control for Electrically Driven
Compressors on Overcharged Gasoline or Diesel Engines. In Proceedings of the 35th Annual Conference of
the IEEE Industrial Electronics Society. Porto: Faculdade de Engenharia da Universidade do Porto, 2009, .
[nm16] Novák, L. - Novák, J. - Novák, M.: Electrically Driven Compressors on Turbocharged Engines with
High Speed Synchronous Motors. In Proceedings of The 8thElectromotion Conference, EPE Chapter
“Electric Drives”. Lille: HEI Graduate School, 2009, p. 600-605. ISBN 978-2-915913-25-5.
[nm17] Novák, J. - Novák, M. - Čeřovský, Z.: High Speed Synchronous Motor Control. In XXXI. celostátní
konference o elektrických pohonech[CD-ROM]. Praha: Česká elektrotechnická společnost, 2009, s. 1-8.
ISBN 978-80-02-02151-3. (in Czech).
[nm18] Novák, M.: Vector Control of High-Speed Synchronous Motor. In Sborník odborného semináře Nové
metody a postupy v oblasti přístrojové techniky, automatického řízení a informatiky [CD-ROM]. Praha:
Ústav přístrojové a řídicí techniky FS ČVUT, 2009, s. 22-27. ISBN 978-80-01-04353-0. (in Czech).
2008
[nm19] Cerovsky, Z. - Novak, J. - Novak, M.; et al. Digital Controlled High Speed Synchronous Motor in 13th
International Power Electronics and Motion Control Conference Pages:982-987 Year:2008
[nm20] Čeřovský, Z. - Novák, J. - Novák, M. - Čambál, M.: Digital Controlled High Speed Synchronous Motor.
In Proceedings of the 13th International Power Electronics andMotion Control Conference EPE-PEMC
2008. Poznaň: PTETiS, 2008, p. 997-1002. ISBN 978-1-4244-1742-1.
[nm21] Novák, J. - Čambál, M. - Novák, M.: High-speed Permanent Magnet Synchronous Motors Torque Control. In Nové metody a postupy v oblasti přístrojové techniky, automatického řízení a
informatiky. Praha: České vysoké učení technické v Praze, 2008, s. 28-33. ISBN 978-80-01-04087-4.
(in Czech).
2007
[nm22] Cambal, A. - Novak, M.; Novak, J.; et al.: Possibilities to increase the quality of phase current control
for synchronous motors, In Conference: Mediterranean Conference on Control and Automation Pages:533538 Year:2007
[nm23] Uhlir, I. - Cambal, M. - Novak, M.; et al.: Synchronous motor current controler quality augmentation
with adaptive control, In Conference:33rd Annual Conference of the IEEE-Industrial-ElectronicsSocietyPages:1198-1203Year:2007
[nm24] Čambál, M. - Novák, M. - Novák, J.: Possibilities to Increase the Quality of Phase Current Control for
Synchronous Motors. In Proceedings of the 15th Mediterranean Conference on Control and Automation
[CD-ROM]. Athens: Mediterranean Control Association, 2007, ISBN 978-960-254-664-2.
[nm25] Čambál, M.
Novák, M.
Novák, J.: Synchronous Motors Phase Current Adaptive Control.
In Proceedings of the 8th International Carpathian Control Conference. Košice: Technical University ,
BERG Faculty, 2007, p. 91-94. ISBN 978-80-8073-805-1.
[nm26] Uhlíř, I. - Čambál, M. - Novák, M. - Novák, J.: Synchronous Motor Current Controler Quality
Augmentation with Adaptive Control. In The 33rd Annual Conference ofthe IEEE Industrial Electronics
Society. Taipei: IEEE Industrial Electronics Society, 2007, p. 1198-1203. ISBN 1-4244-0783-4.
100
Chapter 12. References
[nm27] Novák, J. - Čambál, M. - Novák, M.: Adaptive Control of Synchronous Motor Torque . In Nové metody
a postupy v oblasti přístrojové techniky, automatického řízení a informatiky. Praha: ČVUT FS, Ústav
přístrojové a řídící techniky, 2007, s. 7-12. ISBN 978-80-01-03747-8. (in Czech).
[nm28] Novák, J. - Čambál, M. - Novák, M.: Possibilities to Increase the Quality of Synchronous Motor Phase
Current Control. In XXX. celostátní konference o elektrických pohonech. Praha: Česká elektrotechnická
společnost, 2007, díl I., s. 18-21. ISBN 978-80-02-01921-3. (in Czech).
2006
[nm29] Novák, M. -Čambál, M. - Novák, J.: Application of Sinusoidal Phase Current Control for Synchronous
Drives. In ISIE 2006 International Symposium on Industrial Electronic. NewYork: IEEE, 2006, p. 22602265. ISBN 978-1-4244-0496-4.
[nm30] Novák, M. - Novák, J. - Čambál, M. - Uhlíř, I.: Digital Measurement of Power in Impulse Powered
Circuits. In Proceedings of the 8th International Scientific-Technical Conference Process Control 2008
[CD-ROM]. Pardubice: University of Pardubice, 2008, ISBN 978-80-7395-077-4.
[nm31] Čambál, M. - Novák, M. - Novák, J.: Research of Synchronous Motor Torque Control Methods.
In Sborník odborného semináře Nové metody a postupy v oblasti přístrojové techniky, automatického řízení
a informatiky. Praha: Ústav přístrojové a řídicí techniky FS ČVUT, 2006, s. 11-18. ISBN 80-01-03491-7.
(in Czech).
2005
[nm32] Čambál, M. - Novák, M. - Novák, J.: Study of Synchronous Motor Rotor Position Measuring Methods.
In 13th International Conference on Electrical Drivers andPower Electronics. Zagreb: KoREMA, 2005, p.
62-66. ISBN 953-6037-42-4.
[nm33] Čambál, M. - Novák, M.: Study of Synchronous Motor Rotor Position Measuring Methods. In Nové
metody a postupy v oblasti přístrojové techniky, automatického řízení a informatiky. Praha: Vydavatelství
ČVUT, 2005, s. 3-7. ISBN 80-01-03240-X. (in Czech).
[nm34] Čambál, M. - Novák, M. - Novák, J.: The Resolvers Output Signal Evaluation for Synchronous Motor
Rotor Position . In XXIX. celostátní konference o elektrických pohonech. Praha: Česká elektrotechnická
společnost, 2005, s. 115-118. ISBN 80-02-01733-1. (in Czech).
12.3.
Own patents and utility designs
[nm35] Novák, M. - Uhlíř, I. - Do, M.L. - Gumalay, R. - Sigalingging, A.A.: Vapour phase soldering device.
Užitný vzor Office of Industrial Ounership, 19396. 2009-03-09. (in Czech).
[nm36] Novák, M. - Volf, J.: Electronic circuit for information processing from variable resistance sensors.
Užitný vzor Office of Industrial Ounership, 19700. 2009-06-08. (in Czech).
[nm37] Volf, J. - Novák, M. - Vlček, J. - Trinkl, A.: Device for tactile information sensing. Užitný vzor
Office of Industrial Ounership, 19725. 2009-06-15. (in Czech).
[nm38] Novák, M. -Chyský, J. -Stanke, O. - Novák, J.:Combined heat and powers upply. Užitný vzor Office of
Industrial Ounership, 21700. 2011-02-03. (in Czech).
[nm39] Novák, M. - Volf, J.:Electronic circuit for information processing from variable resistance sensor.
Patent Office of Industrial Ownership, 301690. 2010-04-14. (in Czech).
[nm40] Volf, J. - Novák, M. - Vlček, J. -Trinkl, A.: Device for tactile information sensing. Patent Office of
Industrial Ounership, 301717. 2010-04-22. (in Czech)
101
Chapter 12. References
12.4.
List of co-authored papers on other topics
2010
[nm41] Do, M. - Novák, M. - Uhlíř, I.:Experience with Vapor Phase Soldering Device. In ARTEP -Zborník
príspevkov[CD-ROM]. Košice: Technical University of Košice, 2010, p. 16-1-16-9. ISBN 978-80-5530347-5.
[nm42] Do, M. - Novák, M. - Uhlíř, I.: VAPOR PHASE SOLDERING DEVICE. In Proceedings of The 9th
International Conference Process Control2010 [CD-ROM]. Pardubice: Universita Pardubice, 2010, p. 1-9.
ISBN 978-80-7399-951-3.
[nm43] Novák, M. - Novák, J.: CONTROL OF AN ELECTRICAL POWER SPLITTER IN A HYBRID
TRACTION PROPULSION SYSTEM. In Proceedings of The 9th International Conference Process
Control2010 [CD-ROM]. Pardubice: Universita Pardubice, 2010, p. 1-9. ISBN 978-80-7399-951-3.
[nm44] Novák, M. - Novák, J. -Čeřovský, Z.: Pulse Rectifier Control for Electric Power Splitter of a Hybrid
Propulsion System. In Proceedings of the2010 IEEE International Symposium on Industrial
Electronics[CD-ROM]. Bari:Politecnico di Bari, 2010, p. 1462-1467. ISBN 978-1-4244-6391-6.
[nm45] Roztočil, J. - Novák, M.: FAULT DIAGNOSIS OF ROTATING MACHINERY BASED ON
WAVELET TRANSFORMS. In Proceedings of The 9th International Conference ProcessControl 2010
[CD-ROM]. Pardubice: Universita Pardubice, 2010, p. 1-10. ISBN 978-80-7399-951-3.
[nm46] Roztočil, J. - Novák, M.:System for diagnostic of combustion engine with wavelet transform and
neuron network. In ARTEP -Zborník príspevkov[CD-ROM]. Košice:Technical University of Košice, 2010,
s. 56-1-56-13. ISBN 978-80-553-0347-5. (inCzech).
[nm47] Novák, M. - Novák, J. -Čeřovský, Z. - Uhlíř, I.:Electric Power Splitter Pulse Rectifier Control in a
Hybrid Propulsion System. In Proceedings of the 14th EPE-PEMC Conference 2010. Skopje:International
Council on Large Electric Systems Macedonian National Commitee, 2010, p. T4-7-T4-11. ISBN 978-14244-7854-5.
[nm48] Do, M. - Novák, M. - Uhlíř, I.: Experience with vapor phase soldering device. Strojárstvo. 2010, no. 5,
p. 1-4. ISSN 1335-2938.
2009
[nm49] Novák, J. - Novák, M.: Power measurement in impulse powered circuits. Elektro. 2009, roč. 2009, č. 1,
s. 8-12. ISSN 1210-0889. (in Czech).
[nm50] Novák, M.: Touch screen principles and their usage in automation. Elektro.
ISSN 1210-0889. (in Czech).
2009,
č. 2,
s. 46-48.
[nm51] Do, ML. - Novak, M. - Uhlir, I.: Vapour Soldering System with Peltier Heater
In APPLIED ELECTRONICS, INTERNATIONAL CONFERENCE, Pages:91-94 Published:2009
[nm52] Nedela, R. - Novak, M. - Volf, J.: New Generation of Plantograf Tactile Sensor
In APPLIED ELECTRONICS, INTERNATIONAL CONFERENCE, Pages:187-190 Published:2009
[nm53] Sulc, B. - Novak, M.: Self tuned state-feedback for keeping optimal setting of superior PI control
In. 2009 Ieee International Conference on Control and Automation, Vols 1-3 Pages:337-342
Published:2009
[nm54] Trinkl, A. - Volf, J. - Novák, M. - Růžička, M.: OPTIMAL SIZE DETERMINATION OF TACTILE
SENSOR
PLANTOGRAF
V08
AND
ITS
ELECTRODES.
In 26th
Symposium
on Advances in Experimental Mechanics. Leoben: Montan
universitat Leoben,
2009,
p. 233-234.
ISBN 978-3-902544-02-5.
[nm55] Volf, J. - Vítek, K. - Novák, P. - Novák, M. - Vlček, J. -etal.: MULTI-AXES FORCE TRANSDUCER
WITH SUPPORT THE ROBOTIC SYSTEM FOR ACTING PRESSURE IMAGE VISUALISATION. In
XIX IMEKOWorldCongress2009 –Fundamental and Applied Metrology[CD-ROM]. Lisbon: Instituto
Superior Técnico/Institutode Telecomunicaçoes Portugal, 2009, p. 2278-2281. ISBN 978-963-88410-0-1.
102
Chapter 12. References
[nm56] Do, M. - Novák, M.: Device for Vapour Phase Soldering with Peltier Heaters. In Sborník odborného
semináře Nové metody a postupy v oblasti přístrojové techniky, automatického řízení a informatiky [CDROM]. Praha: Ústav přístrojové a řídicí techniky FS ČVUT, 2009, p. 3-8. ISBN 978-80-01-04353-0.
2008
[nm57] Novák, M.: Correlation method application for estimation of signal frequency changes. Automatizace.
2008, roč. 51, č. 11, s. 702-705. ISSN 0005-125X. (in Czech).
[nm58] Novák, M.: Correlation and Wavelet Methods in Engine Diagnostic. In Proceedings of the 8th
International Scientific-Technical Conference Process Control2008 [CD-ROM]. Pardubice: University of
Pardubice, 2008, ISBN 978-80-7395-077-4.
[nm59] Novák, M.: Universal Process Controller with Touchscreen. In Proceedings of the abstracts - 12th
International Conference on Mechanical Engineering 2008. Bratislava: Slovak University of Technology,
2008, p. II-23-II-25. ISBN 978-80-227-2987-1.
[nm60] Novák, J. - Čambál, M. - Novák, M.: Electric Parameter Measurement in PWM Powered Circuits.
In Nové metody a postupy v oblasti přístrojové techniky, automatického řízení a informatiky. Praha: České
vysoké učení technické v Praze, 2008, s. 22-27. ISBN 978-80-01-04087-4. (in Czech).
[nm61] Novák, M.: Resistive Touch Screens and Usage in a Universal Controller. In Nové metody a postupy v
oblasti přístrojové techniky, automatického řízení a informatiky. Praha: České vysoké učení technické v
Praze, 2008, s. 16-21. ISBN 978-80-01-04087-4. (in Czech).
[nm62] Novák, M.: New Methods for Instantaneous Angular Velocity Estimation by Processing of Analog
Signals, Ph.D. thesis, 2008, Ph.D., Faculty of Mechanical Engineering, Czech Technical University in
Prague, branch Control and System Engineering– in czech
2007
[nm63] Novák, M.: Instantaneous frequency deviation estimation by correlation methods.
In Applied Electronics 2007. Pilsen: University of West Bohemia, 2007, p. 137-140. ISBN 978-80-7043537-3.
[nm64] Volf, J. - Papežová, S. - Vasko, S. - Novák, M. - Vlček, J.: Transducer as Watchdog Alarm for
Physiological Harmful Pressures Levels Determination. In Proceeding ISHF. Lisbon: Faculdade de
Motricida de Humana, 2007, p. 143-148. ISBN 978-972-735-145-9.
[nm65] Novák, M.: Instantaneous Frequency Deviation Estimation by Correlation Methods. In Nové metody a
postupy v oblasti přístrojové techniky, automatického řízení a informatiky. Praha: ČVUT FS, Ústav
přístrojové a řídící techniky, 2007, p. 17-22. ISBN 978-80-01-03747-8.
[nm66] Uhlíř, I. - Novák, L. - Novák, M.: Soldering Device for Surface Mounting Technology. In Nové metody
a postupy v oblasti přístrojové techniky, automatického řízení a informatiky. Praha: ČVUT FS, Ústav
přístrojové a řídící techniky, 2007, s. 29-32. ISBN 978-80-01-03747-8. (in Czech).
2006
[nm67] Novák, M. - Novák, J. - Čambál, M. - Uhlíř, I.: Digital Measurement of Power in Impulse Powered
Circuits. In Proceedings of the 8th International Scientific-Technical Conference Process Control 2008
[CD-ROM]. Pardubice: University of Pardubice, 2008, ISBN 978-80-7395-077-4.
[nm68] Novák, M.: Instantaneous Angular Velocity Irregularity Evaluation. In EDERS 2006 - Proceedings.
Houston: Texas Instruments, 2006, p. 369-375. ISBN 0-9552047-1-2.
[nm69] Chyský, J. - Novák, M.: Fiscal Module for PC Cash System. In Sborník odborného semináře Nové
metody a postupy v oblasti přístrojové techniky, automatického řízení a informatiky. Praha: Ústav
přístrojové a řídicí techniky FS ČVUT, 2006, s. 21-22. ISBN 80-01-03491-7. (in Czech).
103
Chapter 12. References
[nm70] Novák, M.: Miniature Wireless Accelerometer for Shaft Mounting. In Sborník odborného semináře
Nové metody a postupy v oblasti přístrojové techniky, automatického řízení a informatiky. Praha: Ústav
přístrojové a řídicí techniky FS ČVUT, 2006, s. 21-24. ISBN 80-01-03491-7. (in Czech).
[nm71] Novák, M.: Instantaneous Angular Velocity Irregularity Evaluation. In EDERS 2006 - Proceedings.
Houston: Texas Instruments, 2006, p. 369-375. ISBN 0-9552047-1-2.
2005
[nm72] Novák, M.: FPGA Datalogger with DIMM Memory. In Proceedings of the International
Interdisciplinary Honeywell EMI 2005 Student Competition and Conference. Brno: VUT v Brně, FEKT,
2005, p. 190-194. ISBN 80-214-2942-9.
[nm73] Novák, M. - Chyský, J.: Using FPGA's for Sensors Signal Data Storage into a DIMM Memory. In
Applied Electronics 2005 - International Conference Pilsen. Pilsen: University of West Bohemia, 2005, p.
249-252. ISBN 80-7043-369-8.
[nm74] Novák, M. - Čambál, M. - Chyský, J. - Uhlíř, I.: Combustion Engine's Running RoughnessMeasuring
and Utilization for Fault Diagnosis. In Proceedings of Workshop2005 [CD-ROM]. Prague: CTU, 2005, p.
260-261. ISBN 80-01-03201-9.
[nm75] Novák, M.: FPGA usage to high speed sensors data storage. [Nepublikovaná přednáška]. České vysoké
učení technické v Praze, Fakulta strojní. 2005-05-26. (inFrench).
[nm76] Novák, M.: FPGA Data Logger with SDR DIMM Memory. In Nové metody a postupy v oblasti
přístrojové techniky, automatického řízení a informatiky. Praha: Vydavatelství ČVUT, 2005, s. 13-16.
ISBN 80-01-03240-X. (in Czech).
2004
[nm77] Novák, M.: Processing of the Signal from Inductive Sensors for Measuring Engine's Instantaneous
Angular Velocity. In Proceedings of the 6th InternationalScientific-Technical Conference on Process
Control (Říp 2004). Pardubice: University of Pardubice, 2004, p. 246. ISBN 80-7194-662-1.
[nm78] Novák, M.: Digital Signal Processing for Determining Engines Running Roughness. [Nepublikovaná
přednáška]. České vysoké učení technické v Praze, Fakulta strojní. 2004-05-19. (in French).
[nm79] Novák, M.: Simplified Simulation Model of Internal Combustion Engine for Emerging Fault Influence
Assessment to the Instantaneous Angular Velocity. [UnpublishedLecture]. České vysoké učení technické v
Praze, Fakulta strojní. 2004-05-19.
104