Method and system for joint battery state and parameter estimation

• US 20060111870A1
• Filed: 11/23/2004
• Published: 05/25/2006
• Est. Priority Date: 11/23/2004
• Status: Active Grant

• Current Assignee: LG Energy Solution Limited (LG Corporation)
• Original Assignee: LG Chem Limited (LG Corporation)
• Inventors: Plett, Gregory L.
• Granted Patent: US 7,593,821 B2
• Time in Patent Office: Days
• US Class Current: 702/181
• CPC Class Codes: G01R 31/367 Software therefor, e.g. for battery testing using modelling or look-up tables
• CPC Class Codes: G01R 31/374 with means for correcting the measurement for temperature or ageing
• CPC Class Codes: G01R 31/3842 combining voltage and current measurements
• CPC Class Codes: H01M 10/42 Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells H01M10/60 takes precedence
• CPC Class Codes: Y02E 60/10 Energy storage using batteries

Abstract

A method and apparatus for estimation of the augmented state of an electrochemical cell, the method comprising: making an internal augmented states prediction of the cell where the augmented state comprises at least one internal state value and at least one internal parameter value; making an uncertainty prediction of the internal augmented states prediction; correcting the internal augmented states prediction and the uncertainty prediction; and applying an algorithm that iterates the making an internal augmented states prediction, the making an uncertainty prediction and the correcting to yield an ongoing estimation to the augmented state and an ongoing uncertainty to the augmented state estimation.

Claims

1. A method for estimating a present augmented state of an electrochemical cell system, the method comprising:

making an internal augmented states prediction of the cell where said augmented state comprises at least one internal state value and at least one internal parameter value;

making an uncertainty prediction of said internal augmented states prediction;

correcting said internal augmented states prediction and said uncertainty prediction; and

applying an algorithm that iterates said making an internal augmented states prediction, said making an uncertainty prediction and said correcting to yield an ongoing estimation to said augmented state and an ongoing uncertainty to said augmented state estimation.

2. The method of claim 1 wherein said making an internal augmented states prediction comprises:

determining a current measurement;

determining a voltage measurement; and

using said current measurement and said voltage measurement in a mathematical model to make said internal augmented states prediction.

3. The method of claim 2 wherein said making an uncertainty prediction comprises using said current measurement and said voltage measurement in a mathematical model to make said uncertainty prediction.

4. The method of claim 3 wherein said correcting comprises:

computing a gain factor;

computing a corrected internal augmented states prediction using said gain factor, said voltage measurement and said internal augmented states prediction; and

computing a corrected uncertainty prediction using said gain factor and said uncertainty prediction.

5. The method of claim 4 wherein said applying comprises using said corrected augmented internal states prediction and said corrected uncertainty prediction to obtain predictions for a next time step where said algorithm repeats.

6. The method of claim 5 wherein said algorithm is at least one of a Kalman Filter and an extended Kalman filter.

7. The method of claim 6 wherein said augmented state vector includes one or more of:

a state-of-charge, a voltage polarization level, a hysteresis level, a resistance, a capacity, a polarization voltage time constant, a polarization voltage blending factor, a hysteresis blending factor, a hysteresis rate constant, and an efficiency factor.

8. The method of claim 2 wherein said making an internal augmented states prediction further comprises:

determining a temperature; and

using said temperature measurement, said current measurement, and said voltage measurement in a mathematical model to make said internal augmented states prediction.

9. The method of claim 8 wherein said making an uncertainty prediction comprises using said temperature measurement, said current measurement, and said voltage measurement in a mathematical model to make said uncertainty prediction.

10. The method of claim 9 wherein said correcting comprises:

computing a gain factor;

computing a corrected internal states prediction using said gain factor, said voltage measurement and said internal states prediction; and

computing a corrected uncertainty prediction using said gain factor and said uncertainty prediction.

11. The method of claim 10 wherein said applying comprises using said corrected internal states prediction and said corrected uncertainty prediction to obtain predictions for a next time step where said algorithm repeats.

12. The method of claim 11 wherein said algorithm is at least one of a Kalman Filter and an extended Kalman Filter.

13. The method of claim 12 wherein said augmented state vector includes one or more of:

a state-of-charge, a voltage polarization level, a hysteresis level, a resistance, a capacity, a polarization voltage time constant, a polarization voltage blending factor, a hysteresis blending factor, a hysteresis rate constant, and an efficiency factor.

14. The method of claim 2 wherein said making an uncertainty prediction further comprises:

determining a temperature; and

using said temperature measurement, said current measurement, and said voltage measurement in a mathematical model to make said uncertainty prediction.

15. The method of claim 1 wherein said making an uncertainty prediction comprises:

determining a current measurement;

determining a voltage measurement; and

using said current measurement and said voltage measurement in a mathematical model to make said internal augmented states prediction.

16. The method of claim 15 wherein said making an uncertainty prediction further comprises:

determining a temperature; and

using said temperature measurement, said current measurement, and said voltage measurement in a mathematical model to make said uncertainty prediction.

17. The method of claim 16 wherein said correcting comprises:

computing a gain factor;

computing a corrected internal states prediction using said gain factor, said voltage measurement and said internal states prediction; and

computing a corrected uncertainty prediction using said gain factor and said uncertainty prediction.

18. The method of claim 17 wherein said applying comprises using said corrected internal states prediction and said corrected uncertainty prediction to obtain predictions for a next time step where said algorithm repeats.

19. The method of claim 18 wherein said algorithm is at least one of a Kalman Filter and an extended Kalman Filter.

20. The method of claim 1 further comprising ensuring convergence of one or more augmented states to their respective physical values.

21. The method of claim 20 wherein said ensuring includes supplementing a cell model output with said augmented states whose convergence is desired.

22. The method of claim 21 wherein said mechanism further includes supplementing a measurement vector with corresponding estimates of said augmented states based on present measured values.

23. The method of claim 22 wherein a filter is used to adapt a augmented state estimate based on said supplemented cell model output and said supplemented measurement vector.

24. The method of claim 23 wherein said filter is at least one of a Kalman filter and an extended Kalman filter.

25. An apparatus configured to estimate present augmented state of a cell pack system comprising:

a component configured to make an internal augmented states prediction of a cell;

a component configured to make an uncertainty prediction of said internal augmented states prediction;

a component configured to correct said internal augmented states prediction and said uncertainty prediction; and

a component configured to apply an algorithm that iterates steps taken by said component configured to make an internal augmented states prediction, said component configured to make an uncertainty prediction and said component configured to correct to yield an ongoing estimation to said augmented state and an ongoing uncertainty to said augmented state estimation.

26. The apparatus of claim 25 wherein said component configured to make an internal states prediction comprises:

a component configured to determine a current measurement;

a component configured to determine a voltage measurement; and

a component configured to use said parameter estimate and said current measurement and said voltage measurement in a mathematical model to make said internal augmented states prediction.

27. The apparatus of claim 26 wherein said component configured to make an uncertainty prediction comprises a component configured to use said current measurement and said voltage measurement in a mathematical model to make said uncertainty prediction.

28. The apparatus of claim 27 wherein said component configured to correct comprises:

a component configured to compute a gain factor;

a component configured to compute a corrected internal augmented states prediction using said gain factor, said voltage measurement and said internal augmented states prediction; and

a component configured to compute a corrected uncertainty prediction using said gain factor and said uncertainty prediction.

29. The apparatus of claim 28 wherein said component configured to apply comprises a component configured to use said corrected internal augmented states prediction and said corrected uncertainty prediction to obtain predictions for a next time step where said algorithm repeats.

30. The apparatus of claim 29 wherein said algorithm is at least one of a Kalman Filter and an Extended Kalman Filter.

31. The apparatus of claim 30 wherein said augmented state vector includes one or more of:

a state-of-charge, a voltage polarization level, a hysteresis level, a resistance, a capacity, a polarization voltage time constant, a polarization voltage blending factor, a hysteresis blending factor, a hysteresis rate constant, and an efficiency factor.

32. The apparatus of claim 26 wherein said component configured to make an internal augmented states prediction further comprises:

a component configured to determine a temperature; and

a component configured to use temperature measurement, said current measurement, and said voltage measurement in a mathematical model to make said internal states prediction.

33. The apparatus of claim 32 wherein said component configured to make an uncertainty prediction comprises a component configured to use said temperature measurement, said current measurement, and said voltage measurement in a mathematical model to make said uncertainty prediction.

34. The apparatus of claim 33 wherein said component configured to correct comprises:

a component configured to compute a gain factor;

a component configured to compute a corrected internal augmented states prediction using said gain factor, said voltage measurement and said internal states prediction; and

a component configured to compute a corrected uncertainty prediction using said gain factor and said uncertainty prediction.

35. The apparatus of claim 34 wherein said component configured to apply comprises a component configured to use said corrected internal augmented states prediction and said corrected internal states prediction and said corrected uncertainty prediction to obtain predictions for a next time step where said algorithm repeats.

36. The apparatus of claim 35 wherein said algorithm is at least one of a Kalman Filter and an Extended Kalman Filter.

37. The apparatus of claim 36 wherein said augmented state vector includes one or more of:

a state-of-charge, a voltage polarization level, a hysteresis level, a resistance, a capacity, a polarization voltage time constant, a polarization voltage blending factor, a hysteresis blending factor, a hysteresis rate constant, and an efficiency factor.

38. The apparatus of claim 26 wherein said component configured to make an uncertainty prediction further comprises:

a component configured to determine a temperature; and

a component configured to use said temperature measurement, said current measurement, and said voltage measurement in a mathematical model to make said uncertainty prediction.

39. The apparatus of claim 25 wherein said component configured to make an uncertainty prediction comprises:

a component configured to determine a current measurement;

a component configured to determine a voltage measurement; and

a component configured to use said current measurement and said voltage measurement in a mathematical model to make said uncertainty prediction.

40. The apparatus of claim 39 wherein said component configured to make an uncertainty prediction further comprises:

a component configured to determine a temperature; and

a component configured to use said temperature measurement, said current measurement, and said voltage measurement in a mathematical model to make said uncertainty prediction.

41. The apparatus of claim 40 wherein said component configured to correct comprises:

a component configured to compute a gain factor;

a component configured to compute a corrected internal augmented states prediction using said gain factor, said voltage measurement and said internal states prediction; and

a component configured to compute a corrected uncertainty prediction using said gain factor and said uncertainty prediction.

42. The apparatus of claim 41 wherein said component configured to apply comprises a component configured to use said corrected internal augmented states prediction and said corrected internal states prediction and said corrected uncertainty prediction to obtain predictions for a next time step where said algorithm repeats.

43. The apparatus of claim 42 wherein said algorithm is at least one of a Kalman Filter and an Extended Kalman Filter.

44. The apparatus of claim 25 further comprising a component configured to insure convergence of one or more augmented states to their respective physical values.

45. The apparatus of claim 44 wherein said component configured to insure convergence includes a component configured to supplement a cell model output with said one or more augmented states whose convergence is desired.

46. The apparatus of claim 45 wherein said component configured to insure convergence further includes a component configured to supplement a respective measurement vector with corresponding estimates of said one or more augmented states based on present measured values.

47. The apparatus of claim 46 wherein a component is configured to implement a filter to adapt a augmented state estimate based on said supplemented cell model output and said supplemented measurement vector.

48. The apparatus of claim 47 wherein said filter is at least one of a Kalman filter and Extended Kalman Filter.

49. A system for estimating present augmented state of an electrochemical cell comprising:

a means for making an internal augmented states prediction of the cell where said augmented state comprises at least one internal state value and at least one internal parameter value;

a means for making an uncertainty prediction of said internal augmented states prediction;

a means for correcting said internal augmented states prediction and said uncertainty prediction; and

a means for applying an algorithm that iterates said making an internal augmented states prediction, said making an uncertainty prediction and said correcting to yield an ongoing estimation to said augmented state and an ongoing uncertainty to said augmented state estimation.

50. A storage medium encoded with a machine-readable computer program code, wherein said storage medium includes instructions for causing a computer to implement a method for estimating present augmented state of an electrochemical cell, the method comprising:

making an internal augmented states prediction of the cell where said augmented state comprises at least one internal state value and at least one internal parameter value;

making an uncertainty prediction of said internal augmented states prediction;

correcting said internal augmented states prediction and said uncertainty prediction; and

applying an algorithm that iterates said making an internal augmented states prediction, said making an uncertainty prediction and said correcting to yield an ongoing estimation to said augmented state and an ongoing uncertainty to said augmented state estimation.

51. A computer data signal embodied in a computer readable medium:

said computer data signal comprising code configured to cause a computer to implement a method for estimating present augmented state of an electrochemical cell, the method comprising;

making an internal augmented states prediction of the cell where said augmented state comprises at least one internal state value and at least one internal parameter value;

making an uncertainty prediction of said internal augmented states prediction;

correcting said internal augmented states prediction and said uncertainty prediction; and

applying an algorithm that iterates said making an internal augmented states prediction, said making an uncertainty prediction and said correcting to yield an ongoing estimation to said augmented state and an ongoing uncertainty to said augmented state estimation.