Download NIH PROJECT

Design and Implementation of a
State-of-charge meter
for Lithium ion batteries to be
used in Portable Defibrillators
Ramana K.Vinjamuri
08/25/2004
Under direction of
Dr. Pritpal Singh
Outline
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BACKGROUND
PROCEDURE (experimental setup)
MEASUREMENTS AND ANALYSIS
FUZZY LOGIC MODELING
IMPLEMENTATION IN MC68HC12 (micro controller)
CONCLUSIONS
FUTURE SCOPE
BACKGROUND
Portable defibrillators
Today portable defibrillators are considered as
sophisticated devices by FDA (Food and Drug
Administration). As a trend towards the
widespread deployment of portable defibrillators
in the hands of non-medical or non-technical
personnel increases, there exists a need for a
simple procedure to ensure that it will operate
properly when needed.
Portable defibrillators
According to the FDA the major cause of
defibrillator failure was improper care of
the rechargeable battery . The effective
operation of a portable defibrillator
depends critically on the condition of the
battery which are defined by State-ofCharge and State-of-Health.
Chemistry of Li ion batteries
Reactions that occur at Electrodes
Positive LiMO2 → Li 1-xMO2 + x Li + + xe
Negative C + x Li + +xe → Li x C
Overall
LiMO2 + C → Li x C + Li 1-x MO2
Features of Li-ion batteries
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Higher Energy density
Higher voltage
Long operating time
Compact
Definitions
SOC denotes the remaining pulses in a
battery pack in one discharge cycle
SOH represents the remaining number of
cycles (charge-discharge) that can be
obtained from a battery pack in its entire
life. When the battery pack is new it is
said to have 100% SOH. As the battery
ages SOH eventually decreases.
Battery Interrogation Techniques
Efficient battery interrogation techniques are
required for determining the state-ofcharge (SOC) of a battery.
The three basic methods are:
1) Coulomb counting
2) Voltage delay and
3) Impedance method
TYPICAL NYQUIST PLOT OF ELECTRO
CHEMICAL CELL
Z’
Capacitive
behavior
Diffusion
Anode
Cathode
Rs
10 mHz
1kHz
Inductive
behavior
100Hz
0
inductive tail
Z”
Equivalent Circuit for this Cell
Ranode
Rcathode
RS
L
Canode
Ccathode
Using AC impedance for
determination of SOC
Research by J. P.Fellner
At Air force laboratory, OH [1]
Using AC impedance for
determination of SOC
Research by J. P.Fellner
At Air force laboratory, OH [2]
Using AC impedance for
determination of SOC
Research by Dr. Pritpal Singh [3]
Using AC impedance for
determination of SOC
200
60
60
400
Research by J. P.Fellner
At Air force laboratory, OH [2]
Introduction to Fuzzy Logic
In fuzzy logic, a quantity may be a member of a
set to some degree or not be a member of a set
to some degree. The boundaries of the set are
fuzzy rather than crisp.
A fuzzy system is a rule-based mapping of inputs
to outputs for a system.
Two approaches in Fuzzy Logic
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Mamdani Approach: Uses membership
functions for both input and output
variables
Sugeno Approach: Output membership
functions are “singletons” (zero order)
or polynomials (first order).
Example: Two input, two rule Fuzzy
Model
n1
m1
Rule1
F1
S1
m2
Rule2
n2
F2
S2
Sugeno type of inference
PROCEDURE
Li-ion battery pack
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This Li ion battery pack consists of 12 cells
connected in series parallel
(4s3p configuration)
Effective voltage of the battery pack is
16.8 volts(4.2 volts per cell)
Charge profile
The profile that we have adopted is
A constant current charging of 2.5 A till
the battery voltage is 16.6172 v
A constant voltage charging of 16.6 v till
the charge current drops below 100mA
Discharge profile
The profile suggested by
Medtronic/ Physio Control was
Continuous discharge of 1.4 A and a
discharge of 10 A for every 5 minutes for
a period of 5 s
Discharge profile
Load current profile
Voltage recovery profile
Apparatus
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For discharge -- Electronic load 6063B from Agilent
Technologies
For the impedance and the voltage recovery
measurements--Solartron 1280B,which is Potentiostat
/Galvanostat /FRA
For charge --Centronix BMS2000, The Battery
Management System
For different temperatures Tenney Environmental
oven
Battery pack, EC Load and Solartron
EC-Load and Oven
Software
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To control the Electronic Load the software
is HP VEE
To view and plot the impedance data its
Zview and Zplot respectively
To view and plot the voltage recovery
profiles data its Corr view and Corr ware
Software control
Test process
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Constant current discharge at 1.4A for 5 minutes,
monitoring the voltage of the battery pack
Constant current discharge at 10 A for 5 seconds,
monitoring the voltage of the battery pack
Repeat this process for a total of 1100 seconds which
includes three 10 A discharges
EIS (Electro chemical Impedance spectroscopy)
measurement over frequency range of 1Hz-1KHz
Repeat above four steps until end of discharge is
reached (2.5V/cell)
Test process
MEASUREMENTS AND ANALYSIS
Impedance measurements
Nyquist plot
Impedance measurements
Bode plots
Monotonic variation of the voltage
recovery profiles with SOC
Comparing the First and the Last pulse
Analysis
Minimum voltage curves
 Difference voltage curves
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Minimum voltage curves
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The locus of the minimum voltages of
every pulse in one cycle forms one curve
corresponding to Cxx in the graph
One Pulse
Minimum voltage curves
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The locus of the minimum voltages of
every pulse in one cycle forms one curve
corresponding to Cxx in the graph
The above means the set of all As in
figure shown
For battery pack at room temperature
Difference voltage curves
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The locus of the difference between the
maximum and minimum voltages of every
pulse in a cycle forms a curve Cxx in the
figure.
One pulse
Difference voltage curves
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Voltage Difference=B-A
The locus of the difference between the
maximum and minimum voltages of every
pulse (B-A) in a cycle forms a curve Cxx in
the figure.
For battery pack at room temperature
FUZZY LOGIC MODELING
Two models
1. To predict SOC –Remaining pulses (implemented)
2. To predict SOH –Cycle number (theoretical model)
Fuzzy Logic Modeling
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Inputs: Maximum voltage and Minimum voltage
Output: Pulses remaining
Type of mem. functions: Trapezoidal
Type of inference : Sugeno
No. of rules : 12
4 mem. Functions for Max. voltage
3 mem. Functions for Min. voltage
Membership Functions for Input1
Membership Functions for input2
Training error (0.95425)
Testing error (0.99126)
Surface plot
Fuzzy Logic Modeling
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Inputs: Maximum voltage and Minimum voltage
Output: Cycle Number
Type of mem. functions: Trapezoidal
Type of inference : Sugeno
No. of rules : 12
2 mem. Functions for Max. voltage
6 mem. Functions for Min. voltage
Testing error (2.6554)
Training error (2.565)
Surface plot
IMPLEMENTATION IN MC68HC12
(micro controller)
Implementation in
MC68HC12 (micro controller)
Features of HC12:
 On-Chip A/D conversion (any voltage
between 0-5 volts;0-00H and 5-FFH )
 Instruction Set with Fuzzy Logic
instructions (ability to implement
trapezoidal and triangular mem. functions)
Step down circuit
Voltage of the battery pack is stepped down to be
given as input to HC12
R=511 K Ohms
Op Amp=LMC60 42 AIN
Flow chart of the main program
Timing Diagram
Experimental setup
Results
Display showing 21 pulses remaining
LCD display
Average error=+/-2 pulses
Stem Plot
Summary
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Impedance and Voltage recovery profiles collected for
battery packs at room temperature and 00C
Battery characteristics were analyzed and Minimum
voltage curves and Difference voltage curves were
developed
Based on the voltage recovery profiles a good Fuzzy
Logic Model was obtained to predict the SOC of the
battery pack at room temperature with a minimum error
as low as 0.9
Implemented on Micro Controller HC12 with a very low
error of +/-2 pulses
Future scope
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This model can be extended to estimate
the SOC of the battery packs at different
temperatures
An SOH meter that can predict the cycle
number can also be developed provided,
sufficient data is collected for the battery
packs at different temperatures
Publications
1. Pritpal Singh and Ramana Vinjamuri, Xiquan Wang and David
Reisner “FUZZY LOGIC MODELING OF EIS
MEASUREMENTS ON LITHIUM-ION BATTERIES”. EIS’04
2.
Pritpal Singh and Ramana Vinjamuri, Xiquan Wang and David
Reisner.” Analysis on Voltage recovery profiles and
Impedance measurements of High Power Li ion
batteries”.
41 st Power sources conference,2004
References
1.
2.
3.
J.P.Fellner and R.A. Marsh “Use of the pulse current and AC impedance
characterization to enhance Lithium ion battery maintenance”,
Electrochemical society proceedings volume 99-25
J.P.Fellner, G.J.Loeber, S.S.Sadhu “Testing of lithium ion 18650 cells and
characterizing/predicting cell performance” Journal of Power sources
conference 81-82(1999)
P. Singh, Y.S. Damodar, C. Fennie, and D.E. Reisner, “Fuzzy Logic-Based
Determination of Lead Acid Battery State-of-Charge by Impedance
Interrogation Methods”Procs. EVS-17, Montreal, Canada, Oct 15-18, 2000