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Ramana K.Vinjamuri 08/25/2004 Under direction of Dr. Pritpal Singh

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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

- BACKGROUND
- PROCEDURE (experimental setup)
- MEASUREMENTS AND ANALYSIS
- FUZZY LOGIC MODELING
- IMPLEMENTATION IN MC68HC12 (micro controller)
- CONCLUSIONS
- FUTURE SCOPE

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.

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-of-Charge and State-of-Health.

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

- Higher Energy density
- Higher voltage
- Long operating time
- Compact

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.

Efficient battery interrogation techniques are required for determining the state-of-charge (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’

Diffusion

Anode

Capacitive

behavior

Cathode

10 mHz

1kHz

Rs

100Hz

0

inductive tail

Z”

Inductive

behavior

Rcathode

Ranode

RS

L

Canode

Ccathode

Research by J. P.Fellner

At Air force laboratory, OH [1]

Research by J. P.Fellner

At Air force laboratory, OH [2]

Research by Dr. Pritpal Singh [3]

200

60

60

400

Research by J. P.Fellner

At Air force laboratory, OH [2]

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.

- Mamdani Approach: Uses membership functions for both input and output variables
- Sugeno Approach: Output membership functions are “singletons” (zero order) or polynomials (first order).

n1

Rule1

m1

F1

S1

m2

Rule2

F2

n2

S2

- 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)

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

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

Load current profile Voltage recovery profile

- 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

- 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

- 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)

Nyquist plot

Bode plots

- Minimum voltage curves
- Difference voltage curves

- The locus of the minimum voltages of every pulse in one cycle forms one curve corresponding to Cxx in the graph

- 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

- The locus of the difference between the maximum and minimum voltages of every pulse in a cycle forms a curve Cxx in the figure.

- 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.

- Two models
- To predict SOC –Remaining pulses (implemented)
- To predict SOH –Cycle number (theoretical model)

- 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

- 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

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)

Voltage of the battery pack is stepped down to be given as input to HC12

R=511 K Ohms

Op Amp=LMC60 42 AIN

Display showing 21 pulses remaining Average error=+/-2 pulses

LCD display Stem Plot

- 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

- 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

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

- 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