NIH PROJECT
April 15, 2018 | Author: Anonymous | Category: N/A
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Description
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
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
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
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
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
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
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
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
Minimum voltage curves
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
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
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
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
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
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
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
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
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