1. 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

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

3. BACKGROUND

4. 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. 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.

5. 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-of- Charge and State-of-Health. 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.

6. Chemistry of Li ion batteries Reactions that occur at Electrodes Reactions that occur at Electrodes Positive LiMO2 → Li 1-x MO2 + x Li + + xe Negative C + x Li + +xe → Li x C Overall LiMO2 + C → Li x C + Li 1-x MO2

7. Features of Li-ion batteries Features of Li-ion batteries Higher Energy density Higher Energy density Higher voltage Higher voltage Long operating time Long operating time Compact Compact

8. 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.

9. Battery Interrogation Techniques Efficient battery interrogation techniques are required for determining the state-of- charge (SOC) of a battery. The three basic methods are: The three basic methods are: 1) Coulomb counting 1) Coulomb counting 2) Voltage delay and 2) Voltage delay and 3) Impedance method 3) Impedance method

10. Z’ Z”inductive tail RsRs 0 Diffusion Anode Cathode 1kHz 100Hz 10 mHz Capacitive behavior Inductive behavior TYPICAL NYQUIST PLOT OF ELECTRO CHEMICAL CELL

11. Equivalent Circuit for this Cell RSRS R anode R cathode C anode C cathode L

12. Using AC impedance for determination of SOC Research by J. P.Fellner At Air force laboratory, OH [1]

13. Using AC impedance for determination of SOC Research by J. P.Fellner Research by J. P.Fellner At Air force laboratory, OH [2] At Air force laboratory, OH [2]

14. Using AC impedance for determination of SOC Research by Dr. Pritpal Singh [3]

15. Using AC impedance for determination of SOC Research by J. P.Fellner Research by J. P.Fellner At Air force laboratory, OH [2] At Air force laboratory, OH [2] 200 60 400 60

16. 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. 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. A fuzzy system is a rule-based mapping of inputs to outputs for a system.

17. Two approaches in Fuzzy Logic Mamdani Approach: Uses membership functions for both input and output variables Mamdani Approach: Uses membership functions for both input and output variables Sugeno Approach: Output membership functions are “singletons” (zero order) or polynomials (first order). Sugeno Approach: Output membership functions are “singletons” (zero order) or polynomials (first order).

18. Example: Two input, two rule Fuzzy Model m1 n1 F1 m2 n2 F2 S1 S2 Rule1 Rule2

19. Sugeno type of inference

20. PROCEDURE

21. Li-ion battery pack This Li ion battery pack consists of 12 cells connected in series parallel (4s3p configuration) 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) Effective voltage of the battery pack is 16.8 volts(4.2 volts per cell)

22. Charge profile The profile that we have adopted is 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 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 A constant voltage charging of 16.6 v till the charge current drops below 100mA

23. Discharge profile The profile suggested by The profile suggested by Medtronic/ Physio Control was 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 Continuous discharge of 1.4 A and a discharge of 10 A for every 5 minutes for a period of 5 s

24. Discharge profile Load current profile Voltage recovery profile

25. Apparatus For discharge -- Electronic load 6063B from Agilent Technologies For discharge -- Electronic load 6063B from Agilent Technologies For the impedance and the voltage recovery measurements--Solartron 1280B,which is Potentiostat /Galvanostat /FRA For the impedance and the voltage recovery measurements--Solartron 1280B,which is Potentiostat /Galvanostat /FRA For charge --Centronix BMS2000, The Battery Management System For charge --Centronix BMS2000, The Battery Management System For different temperatures Tenney Environmental oven For different temperatures Tenney Environmental oven

26. Battery pack, EC Load and Solartron

27. EC-Load and Oven

28. Software To control the Electronic Load the software is HP VEE 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 impedance data its Zview and Zplot respectively To view and plot the voltage recovery profiles data its Corr view and Corr ware To view and plot the voltage recovery profiles data its Corr view and Corr ware

29. Software control

30. Test process Constant current discharge at 1.4A for 5 minutes, monitoring the voltage of the battery pack 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 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 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 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) Repeat above four steps until end of discharge is reached (2.5V/cell)

31. Test process

32. MEASUREMENTS AND ANALYSIS

33. Impedance measurements Nyquist plot

34. Impedance measurements Bode plots

35. Monotonic variation of the voltage recovery profiles with SOC

36. Comparing the First and the Last pulse

37. Analysis Minimum voltage curves Minimum voltage curves Difference voltage curves Difference voltage curves

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

39. One Pulse

40. 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 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 above means the set of all As in figure shown

41. For battery pack at room temperature

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

43. One pulse

44. Difference voltage curves Voltage Difference=B-A 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. 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.

45. For battery pack at room temperature

46. FUZZY LOGIC MODELING Two models 1.To predict SOC –Remaining pulses (implemented) 2.To predict SOH –Cycle number (theoretical model)

47. Fuzzy Logic Modeling Inputs: Maximum voltage and Minimum voltage Inputs: Maximum voltage and Minimum voltage Output: Pulses remaining Output: Pulses remaining Type of mem. functions: Trapezoidal Type of mem. functions: Trapezoidal Type of inference : Sugeno Type of inference : Sugeno No. of rules : 12 No. of rules : 12 4 mem. Functions for Max. voltage 4 mem. Functions for Max. voltage 3 mem. Functions for Min. voltage 3 mem. Functions for Min. voltage

48. Membership Functions for Input1

49. Membership Functions for input2

50. Training error (0.95425)

51. Testing error (0.99126)

52. Surface plot

53. Fuzzy Logic Modeling Inputs: Maximum voltage and Minimum voltage Inputs: Maximum voltage and Minimum voltage Output: Cycle Number Output: Cycle Number Type of mem. functions: Trapezoidal Type of mem. functions: Trapezoidal Type of inference : Sugeno Type of inference : Sugeno No. of rules : 12 No. of rules : 12 2 mem. Functions for Max. voltage 2 mem. Functions for Max. voltage 6 mem. Functions for Min. voltage 6 mem. Functions for Min. voltage

54. Testing error (2.6554)

55. Training error (2.565)

56. Surface plot

57. IMPLEMENTATION IN MC68HC12 (micro controller)

58. Implementation in MC68HC12 (micro controller) Features of HC12: On-Chip A/D conversion (any voltage between 0-5 volts;0-00H and 5-FFH ) 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) Instruction Set with Fuzzy Logic instructions (ability to implement trapezoidal and triangular mem. functions)

59. 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

60. Flow chart of the main program

61. Timing Diagram

62. Experimental setup

63. Results Display showing 21 pulses remaining Average error=+/-2 pulses LCD display Stem Plot

64. Summary Impedance and Voltage recovery profiles collected for battery packs at room temperature and 0 0 C Impedance and Voltage recovery profiles collected for battery packs at room temperature and 0 0 C Battery characteristics were analyzed and Minimum voltage curves and Difference voltage curves were developed 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 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 Implemented on Micro Controller HC12 with a very low error of +/-2 pulses

65. Future scope This model can be extended to estimate the SOC of the battery packs at different temperatures 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 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

66. 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 41 st Power sources conference,2004

67. References 1. 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 2. 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) 3. 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