Download A Novel Approach of Position Estimation, Fuzzy based PFC

A Novel Approach of Position Estimation, Fuzzy based PFC
Converter and Energy generation in BLDC Motor Drive
Selamparasan.S 1, Shyamalagowri.M 2
1
PG Scholar, Erode Sengunthar Engineering College, Thudupathi.
2
Associate Professor / EEE, Erode Sengunthar Engineering College, Thudupathi.
1
[email protected],[email protected]
1
9965271383, 2 9842660908
Abstract— This paper describes a simple way to
is carried out by fuzzy logic techniques to
control the Brush Less DC Motor (BLDCM)
improve the performance of the system.
for
electrical
applications.
This
proposed
approach makes the control of BLDC motor
with sensorless motion control of BLDC motor,
Keywords:- BLDC motor,
Power Factor
Correction, Fly wheel generator, Regenerative
Braking.
Bridgeless Buck-Boost Rectifier based power
factor correction and regeneration of electric
I.
power from the motor at time of running
condition as well as in braking condition. To
control this machine it is generally required to
OBJECTIVE
The main objective of this paper is efficient
way of Power Factor Correction (PFC).
measure the speed and position of rotor by
Position
using the sensor because the inverter phases,
industrial based BLDC drives and also
acting at any time, must be commutated
electrical energy conservation from the motor
depending on the rotor position. The position
at running time as well as braking time.
sensors
make
the
motor
system
estimation
and
controlling
of
more
complicated and mechanically unreliable. A
II.
INTRODUCTION
method for the estimation of the speed and
Now a day’s PFC and BLDC motor drives
rotor position of a BLDCM is presented in this
becomes more popular in industries. Normally
work. Fuzzy based PFC is employed to control
BLDC motor has a rotor with permanent
the power factor by using measurements of the
power factor angle. Most existing PFC methods
of the BLDC motor have low performance. To
overcome this problem, the estimation of a PFC
magnet and stator with windings. Brushless
motors are not self-commutating, and hence
are more complicated to control. BLDC motor
control requires knowledge of the rotor
position and mechanism to commutate the
Fig.1 shows the block diagram of proposed
motor. For closed-loop speed control it
system .The proposed system consists of
requires
Fuzzy based
two
additional
requirements,
bridge
less
power
factor
measurement of the motor speed and/or motor
Converter, Three Phase Inverter, BLDC Motor
current and PWM signal to control the motor
Fly Wheel Generator, Battery and Zero
speed and power. BLDC motors can use edge-
Crossing Detector.
aligned
or
centre-aligned
PWM
signals
depending on the application requirements.
Most applications, that only require variable
speed operation, will use six independent
edge-aligned PWM signals. This provides the
highest resolution. If the application requires
servo-positioning,
dynamic
braking,
or
dynamic reversal, it is recommended that
complementary centre-aligned PWM signals
Fig. 1 Block diagram of Proposed System
be used. To sense the rotor position BLDC
IV.
motors use Hall Effect sensors to provide
CORRECTION IN INDUSTRY
absolute position sensing, which results in
more wires and higher cost. Sensorless BLDC
control eliminates the need for Hall Effect
sensors, using the back-EMF (electromotive
force) of the motor instead to estimate the
rotor position. Sensorless control is essential
for low-cost variable speed applications such
as fans and pumps. Refrigerator and air
conditioning
compressors
also
require
sensorless control when using BLDC motors.
NEDD OF POWER FACTOR
A power factor of one or "unity power
factor" is the goal of any electric utility
company since if the power factor is less than
one, they have to supply more current to the
user for a given amount of power use. In so
doing, they incur more line losses. They also
must have larger capacity equipment in place
than would be otherwise necessary. As a
result, an industrial facility will be charged a
penalty if its power factor is much different
III.
BLOCK DIAGRAM OF THE
from 1. Industrial facilities tend to have a
PROPOSED SYSTEM
"lagging power factor", where the current lags
the
voltage
(like
an inductor).
This
is
primarily the result of having a lot of electric
induction motors - the windings of motors act
as
inductors
as
seen
by
the
A.
power
Operation During Positive and Negative
Half Cycle of Supply Voltage
supply. Capacitors have the opposite effect
In this mode converter switches Sw1 and Sw2
and can compensate for the inductive motor
are operate in positive and negative half cycle
windings. Some industrial sites will have large
of
banks of capacitors strictly for the purpose of
positive half cycle switch SW1, inductor Li1
correcting the power factor back toward one to
and diodes D1 and Dp are operated to transfer
save on utility company charges.
energy to DC link capacitor Cd. Similarly in
supply
voltage
respectively.
During
negative half cycle of supply voltage switches
V.
POWER FACTOR CORRECTION
Sw2, inductor Li2 and diode D2 and D2
CONVERTER
conducts. In Discontinuous Inductor Current
Mode(DICM) operation of converter
current
in
the
inductor
Li
the
becomes
discontinuous for certain duration in a
switching period.
B.
Fig. 2 PFC based bridgeless Buck-Boost
Operation During Complete Switching
Cycle
In this switching cycle there are three modes
Converter
of operation.
In the proposed configuration of bridgeless
buck-boost
converter
has
the
minimum
number of components and least number of
conduction devices during each half cycle of
supply voltage which governs the choice of
BL buck-boost converter for this application.
The operation of the PFC bridgeless buckboost converter is classified into two parts
which include the operation during the
positive and negative half cycles of supply
voltage and during the complete switching
cycle.
Mode I: In this mode, switch Sw1 conducts
for charging the inductor Li1, hence the
inductor current iLi1 increases in this mode.
Diode Dp completes the input side and the DC
link capacitor Cd is discharged by VSI fed
BLDC motor.
Mode II: In this mode of operation switch
Sw1 is turned off and the stored energy from
the inductor Li1 is transferred to DC link
capacitor Cd till the inductor is fully
discharged and current in the inductor is fully
reduced to zero.
Mode III: In this mode of operation inductor
Li1 operate in discontinuous conduction mode
and diodes and switch are in off condition. At
this time DC link capacitor Cd starts
discharging. This operation can be continue up
Fig. 3 BLDC Motor Construction
to switch Sw1 is turned on again.
In the DC commutator motor, the current
VI.
BRUSHLESS DC MOTOR
polarity is altered by the commutator and
BLDC motors are very popular in a wide
brushes. However, in the DC motor, polarity
variety of applications. Compared with a DC
reversal is performed by power transistors
motor,
electric
switching in synchronization with the rotor
mechanical
position. Therefore, BLDC motors often
commutator, so it is more reliable then the DC
incorporate either internal or external position
motor. In a BLDC motor, rotor magnets
sensors to sense the actual position, or the
generate the rotor’s magnetic flux, so VLDC
position can be detected without sensors.
BLDC
commutator
motor
rather
uses
than
a
an
motor achieve higher efficiency. Therefore,
BLDC motors may be used in high-end white
goods
(refrigerators,
washing
VII.
FUZZY LOGIC CONTROL
machines,
dishwashers, etc.), high end pumps, and fan
and in other appliances which require high
reliability and efficiency.
BLDC motor has an stator with an three
phase stator like that an induction motor, and
the rotor has surface is a classic 3-phase stator
like that of an induction motor, and the rotor
Fig. 4 Fuzzy logic controller operation
has surface-mounted permanent magnets are
shown in Fig. 3
In this section, we will explain the main
components of a fuzzy logic controller and
also implement a simple fuzzy control
program. The three main actions performed by
controller. Fuzzification consists of two main
a fuzzy logic controller are:
components:
 fuzzification

membership functions
 fuzzy processing

labels
 defuzzification
As shown in Figure 4, when the fuzzy
VII.I.
Membership Functions:-
controller receives the input data, it translates
During fuzzification, a fuzzy logic controller
it into a fuzzy form. This process is called
receives input data, also known as the fuzzy
fuzzification. The controller then performs
variable, and analyses it according to user-
fuzzy
the
defined charts called membership functions.
evaluation of the input information according
Membership functions group input data into
to IF…THEN rules created by the user during
sets, such as temperatures that are too cold,
the fuzzy control system’s programming and
motor speeds that are acceptable, etc. The
design stages. Once the fuzzy controller
controller assigns the input data a grade from
finishes the rule-processing stage and arrives
0 to 1 based on how well it fits into each
at an outcome conclusion, it begins the
membership function (e.g., 0.45 too cold, 0.7
defuzzification process. In this final step, the
acceptable speed). Membership functions can
fuzzy
output
have many shapes, depending on the data set,
conclusions into “real” output data (e.g.,
but the most common are the S, Z, Λ, and Π
analog counts) and sends this data to the
shapes. Here we have use two membership
process via an output module interface. If the
functions namely input membership function
fuzzy logic controller is located in the PLC
and output membership function. Figure 5
rack and does not have a direct or built-in I/O
shows the input membership functions. Here
interface with the process, then it will send the
we have take triangular membership functions
defuzzification output to the PLC memory
for both inputs as well as in output.
processing,
controller
which
involves
converts
the
location that maps the process’s output
interface module.
VIII.
The
FUZZIFICATION COMPONENTS
fuzzification
process
is
the
interpretation of input data by the fuzzy
5. Large
Fig. 5 Input Membership Function
Power Factor angle is taking as input.
6. Very large
Output membership function is shown in
7. High
figure number 6. Firing angle is taking as an
8. Very high
output in output membership function.
Inference Mechanism
In this step, the value of the fuzzy output is
determined using a rule base. A typical rule is
described as:
Power Factor Angle
Firing Angle
(Input)
(Output)
Very very small
Very very small
Very small
Very small
Small
Small
Medium
Medium
membership functions, with seven being the
Large
Large
maximum and the norm, that define its
Very large
Very large
conditions. Each membership function is
Huge
Huge
defined by a name called a label. For example,
Very huge
Very huge
Fig. 6 Output Membership Function
VII.II.
Labels
Each fuzzy controller input can have several
an input variable such as temperature might
have five membership functions labelled as
cold,
cool,
normal,
warm,
and
hot.
Generically, the seven membership functions
have the following labels, which span from
the data range’s minimum point (negative
large) to its maximum point (positive large).
In this paper we have take 8 labels namely
1. Very very small
2. Very small
3. Small
4. Medium
Table I fuzzy rule base
Table I shows the rule-base. The database
contains descriptions of the input and output
Variables.
Fig. 9 Simulation Diagram of Fuzzy
Based PFC Controlled BLDC Motor Drive
Fig. 7 Rule Viewer
Figure 7 shows the Rule Viewer of the Input
and Output Membership Functions.
Fig. 10 Simulation Diagram of Fuzzy
Based PFC
Figure 10 shows the simulation diagram of
fuzzy based PFC.
Fig. 8 Surface Viewer
Figure 8 shows the surface viewer of the
input and output membership functions.
IX.
RESULT
Here MATLAB simulink
is
used as
simulation platform. Figure 9 shows the
existing method used for BLDC motor
control.
Fig. 11 Simulation Diagram of PFC With
out Fuzzy
Figure 11 shows the simulation diagram of
BL PFC without fuzzy controller.
Figure 13 shows the power factor range of
fuzzy based PFC. Here power factor is
maintain 0.9 to unity
Mechanical out from the BLDC motor is
connected to the flywheel generator. Flywheel
generator has been used to generate the
electrical output at time of BLDC motor
running. Figure 14 shows the flywheel
generator speed with respect to time.
Fig. 12 Power Factor Range in BL PFC
without fuzzy
Figure 12 shows the simulation result BL
Fig. 14 Flywheel generator speed
PFC without fuzzy controller. Power Factor
Range in BL PFC without fuzzy is maintain
from 0.85 to unity.
Fig. 13 Power Factor Range in Fuzzy
based PFC
Figure 15 shows the output three phase
voltage from the flywheel generator.
Fig. 15 Three phase Output Voltage from
Flywheel Generator
X.
Control Strategy for Four-Switch
CONCLUSION
The estimation of the speed and rotor
Three-Phase Brushless DC Motor
position is determined by back-EMF observer
Using
Single
Current
Sensor,”
which is carried out with the help of fuzzy
( IEEE Transaction on Industrial
logic techniques to improve the Power Factor
Electronics, Vo.,56, No 6, June
of the system. The proposed algorithm using
2009)
fuzzy based PFC observer is used to maintain
the power factor range in unity. As a result,
2. M.Basezynski, and S.Pirog, Member,
the proposed sensorless BLDC motor drive
IEEE “ A Novel Speed Measurement
method without an additional circuit has
method for a high- speed BLDC
higher
motor based on the signals from the
performance
than
conventional
sensorless methods. In addition, this proposed
rotor
position
sensorless method can be easily applied to
Transaction
industrial applications requiring low-cost and
Electronics)
sensor”
on
(IEEE
Industrial
reliable drive of the BLDC motor. With the
help of a conventional speed controller, both
3. Sanjeev Singh, Member, IEEE, and
sensor and sensorless drive have been
Bhim Singh, Fellow, IEEE “A
performed in Matlab/Simulink environment.
Voltage-Controlled
Simulation results show that the performance
Converter-Based PMBLDCM Drive
of the fuzzy based drive is similar to that of
for
the sensor based drive. Therefore, the fuzzy
Transaction
based drive can replace the sensor drive which
Application, Vo.,48, No 2, March
has lot of demerits. Electrical energy is
/April 2012)
PFC
Air-Conditioners”
on
(
Cuk
IEEE
Industrial
regenerated from the BLDC motor at running
time and also in braking time by using fly
wheel generator and regenerative braking.
4. Abbas A. Fardoun, Senior Member,
IEEE,
Esam
H.
Ismail,
Senior
Member, IEEE “ New Efficient
XI.
Bridgeless Cuk Rectifier for PFC
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“Performance
BIOGRAPHY
SELAMPARASAN.S
received
the diploma in electrical &
electronics
engineering
Directorate
of
from
Technical
Education in 2008, and degree in
electrical & electronics engineering from
Anna University in 2012, Currently pursing
Master of Engineering from Power Electronics
And Drives in Anna university, Chennai.
Prof. M.SHYAMALAGOWRI
received the B.E degree in
Electrical
and
Electronics
Engineering from KSR College
of Technology, Thiruchengodu in 2001 and
M.E., Control Systems from PSG College of
Technology, Coimbatore in