Model-based predictive diagnostic tool for primary and secondary batteries

• US 20030184307A1
• Filed: 02/06/2003
• Published: 10/02/2003
• Est. Priority Date: 02/19/2002
• Status: Abandoned Application

• Current Assignee: Penn State Research Foundation
• Original Assignee: Penn State Research Foundation
• Inventors: Hay, Todd A., Cawley, Thomas, Watson, Matthew J., Byington, Carl S., Garga, Amulya K., Kozlowski, James D.
• Application Number:
  US10/360,023
• Publication Number:
  US 20030184307A1
• Time in Patent Office: Days
• US Class Current: 324/427
• CPC Class Codes: B60L 2240/545 Temperature
• CPC Class Codes: B60L 2240/547 Voltage
• CPC Class Codes: B60L 2240/549 Current
• CPC Class Codes: B60L 2260/44 by parameter estimation
• CPC Class Codes: B60L 2260/50 by future state prediction
• CPC Class Codes: B60L 3/0046 relating to electric energy storage systems, e.g. batteries or capacitors
• CPC Class Codes: B60L 58/12 responding to state of charge [SoC]
• CPC Class Codes: B60L 58/16 responding to battery ageing, e.g. to the number of charging cycles or the state of health [SoH]
• CPC Class Codes: B60W 2510/248 Age of storage means
• CPC Class Codes: G01R 31/367 Software therefor, e.g. for battery testing using modelling or look-up tables
• CPC Class Codes: G01R 31/389 Measuring internal impedance, internal conductance or related variables
• CPC Class Codes: G01R 31/392 Determining battery ageing or deterioration, e.g. state of health
• CPC Class Codes: H01M 10/48 Accumulators combined with arrangements for measuring, testing or indicating the condition of cells, e.g. the level or density of the electrolyte constructional details of current conducting connections for detecting conditions inside cells or batteries, e.g. details of voltage sensing terminals, H01M50/569
• CPC Class Codes: H01M 6/5044 Cells or batteries structurally combined with cell condition indicating means
• CPC Class Codes: Y02E 60/10 Energy storage using batteries
• CPC Class Codes: Y02T 10/70 Energy storage systems for electromobility, e.g. batteries

Abstract

A method for determining a condition parameter of an electrochemical cell, such as in a battery, includes the step of obtaining condition data correlated with the condition parameter. Additionally, the method includes the step of providing the condition data to a plurality of prediction algorithms, wherein each prediction algorithm provides a condition parameter estimate. Therefore, a plurality of condition parameter estimates are provided. The method also includes a step in determining the condition parameter using the plurality of condition parameter estimates.

Claims

1. A method for determining a condition parameter of an electrochemical cell, the method comprising:

obtaining condition data correlated with the condition parameter;

providing the condition data to a plurality of prediction algorithms, wherein each prediction algorithm provides a condition parameter estimate, so as to provide a plurality of condition parameter estimates; and

determining the condition parameter using the plurality of condition parameter estimates.

2. The method of claim 1, wherein the condition parameter is determined from the plurality of condition parameter estimates using a decision fusion algorithm.

3. The method of claim 1, wherein the condition data is derived from electrical impedance data relating to the electrochemical cell.

4. The method of claim 1, wherein the condition parameter is a state of charge of the electrochemical cell.

5. The method of claim 1, wherein the condition parameter is a state of health of the electrochemical cell.

6. The method of claim 1, wherein the condition parameter is a remaining useful energy or a remaining useful number of cycles of the electrochemical cell.

7. The method of claim 1, wherein the number of prediction algorithms is three.

8. The method of claim 1, wherein the plurality of prediction algorithms comprises a neural network algorithm, a fuzzy logic algorithm, and an auto-regressive moving-average algorithm.

9. A method of determining a condition parameter of an electrochemical cell, comprising:

determining electrical impedance data relating to the electrochemical cell;

determining at least one electrochemical parameter from the electrical impedance data;

providing the electrochemical parameter to a prediction algorithm, wherein the prediction algorithm provides an estimate of the condition parameter.

10. The method of claim 9, wherein the electrical impedance data comprises electrical impedances of the electrochemical cell at a plurality of frequencies.

11. The method of claim 9, wherein the electrical impedance data comprises electrical impedances of the electrochemical cell over a plurality of frequencies over a frequency range, the frequency range at least extending from 10 Hz to 10 kHz.

12. The method of claim 9, wherein the at least one electrochemical parameter is determined from the electrical impedance data using a simulating annealing method.

13. The method of claim 9, wherein the prediction algorithm is an auto-regressive moving-average algorithm

14. The method of claim 9, wherein the prediction algorithm is a neural network.

15. The method of claim 9, wherein the prediction algorithm is a fuzzy logic algorithm.

16. The method of claim 9, wherein the electrochemical parameter is further provided to at least one other predictive algorithm, wherein the condition parameter is determined from condition parameter estimates provided by each predictive algorithm using a decision fusion algorithm.

17. The method of claim 16, wherein the electrochemical parameter is provided to an auto-regressive moving-average algorithm, a neural network, and a fuzzy logic algorithm

18. An apparatus for determining a condition parameter of an electrochemical cell, comprising:

electrical connections, providing electrical communication with the electrochemical cell, the electrical connections receiving measurement signals correlated with the condition parameter of the electrochemical cell;

a processor;

a memory;

a clock; and

a software program, executable by the processor, operable to pass input data determined from the measurement signals to a plurality of prediction algorithms, wherein each prediction algorithm provides a condition parameter estimate;

wherein the condition parameter of the electrochemical cell is determined from a plurality of condition parameter estimates provided by the prediction algorithms.

19. The apparatus of claim 18, wherein the measurement signals comprise an electrical signal correlated with the electrical impedance of the electrochemical cell.

20. The apparatus of claim 18, wherein the software program is further operable to provide a decision fusion algorithm receiving the plurality of estimations of the condition parameter;

wherein the condition parameter of the electrochemical cell is provided by the decision fusion algorithm.

21. An apparatus to determine a condition parameter of an electrochemical cell, wherein the condition parameter is the state of charge, state of health, or state of life of the electrochemical cell, comprising:

electrical contacts, locatable so as to be in electrical communication with the electrochemical cell;

circuitry operable to provide an electrical excitation signal to the electrochemical cell through the electrical contacts, to receive an electrical signal from the electrochemical cell, and to determine electrical impedance data for the electrochemical cell;

a processor;

a memory;

software, executable by the processor, operable to provide three predictive algorithms and a decision fusion algorithm, wherein the three prediction algorithms receive input data derived from the electric impedance data, the three prediction algorithms each provide an estimate of the condition parameter, so as to provide three estimates of the condition parameter to the decision fusion algorithm, wherein the condition parameter is determined by the decision fusion algorithm using the three estimates; and

a display, whereby the condition parameter may be displayed to a user of the apparatus.

22. The apparatus of claim 21, further comprising a data input mechanism operable to receive an identification code corresponding to the electrochemical cell, wherein the prediction algorithms access information stored within the memory corresponding to electrochemical cells having the identification code.

23. The apparatus of claim 21, wherein the input data comprises an electrochemical parameter.