Method, system, and computer-readable medium for determining performance characteristics of an object undergoing one or more arbitrary aging conditions

Patent metadata

Field	Value
Publication number	US-9625532-B2
Application number	US-201213598290-A
Country	US
Kind code	B2
Filing date	Aug 29, 2012
Priority date	Oct 10, 2011
Publication date	Apr 18, 2017
Grant date	Apr 18, 2017

Abstract

A method, system, and computer-readable medium are described for characterizing performance loss of an object undergoing an arbitrary aging condition. Baseline aging data may be collected from the object for at least one known baseline aging condition over time, determining baseline multiple sigmoid model parameters from the baseline data, and performance loss of the object may be determined over time through multiple sigmoid model parameters associated with the object undergoing the arbitrary aging condition using a differential deviation-from-baseline approach from the baseline multiple sigmoid model parameters. The system may include an object, monitoring hardware configured to sample performance characteristics of the object, and a processor coupled to the monitoring hardware. The processor is configured to determine performance loss for the arbitrary aging condition from a comparison of the performance characteristics of the object deviating from baseline performance characteristics associated with a baseline aging condition.

First claim

What is claimed is:

1. A method for characterizing performance loss of a battery or battery cell undergoing at least one arbitrary aging condition, the method comprising:
loading, with a processor, known baseline aging data for a battery or battery cell having an aging profile for at least one known baseline aging condition over time;
determining, with the processor, baseline rate expression model parameters from the baseline aging data for the battery or battery cell;
receiving, at the processor, additional aging data associated with the battery or battery cell undergoing different arbitrary aging conditions over successive time periods, each of the different arbitrary aging conditions having an unknown consequence that differs from the at least one known baseline aging condition used for the known baseline aging data;
determining, with the processor, rate expression model parameters for each of the different arbitrary aging conditions and related time interval within the additional aging data;
determining, with the processor, previously unknown performance loss due to aging of the battery or battery cell over time utilizing the rate expression model parameters associated with the battery or battery cell undergoing the different arbitrary aging conditions using a differential deviation-from-baseline approach from the baseline rate expression model parameters;
predicting an aging progression based on the determined previously unknown performance loss; and
controlling operation of the battery or battery cell dynamically in real time responsive to the predicted aging progression.

2. The method of claim 1 , wherein determining performance loss due to aging of the battery or battery cell over time includes determining the rate expression model parameters associated with the battery or battery cell undergoing the different arbitrary aging conditions through performing a computer simulation of the battery or battery cell undergoing the different arbitrary aging conditions.

3. The method of claim 2 , wherein performing the computer simulation of the battery or battery cell undergoing the different arbitrary aging conditions includes performing a plurality of computer simulations, each computer simulation having common time periods with different arbitrary aging conditions.

4. The method of claim 3 , wherein the different arbitrary aging conditions include at least one different aging path over time.

5. The method of claim 3 , wherein the different arbitrary aging conditions include at least one different thermal management parameter for the battery or battery cell.

6. The method of claim 1 , wherein determining the rate expression model parameters includes performing a regression analysis through multiple sigmoid model rate expressions to establish sensitivity of multiple sigmoid model parameters to a plurality of baseline aging conditions.

7. The method of claim 1 , wherein using a differential deviation-from-baseline approach from the baseline rate expression model parameters includes adapting each of the rate expression model parameters associated with each different arbitrary aging condition within each distinct aging period for a plurality of degradation mechanisms over a plurality of unique aging periods, wherein the rate expression model parameters are variable over the plurality of unique aging periods.

8. The method of claim 1 , further comprising selecting, with the processor, the at least one known baseline aging condition to include at least one of a known temperature, a cycling rate, state of charge, and a condition of daily thermal cycling for a battery or battery cell.

9. The method of claim 1 , further comprising loading the baseline rate expression model parameters onboard a monitoring and control system associated with the battery or battery cell.

10. The method of claim 1 , wherein performance loss includes at least one of a capacity loss, a conductance loss, and a power loss of a battery.

11. The method of claim 10 , wherein each of the capacity loss, the conductance loss, and the power loss of a battery or battery cell is defined in terms of fractional or percent reduction or remaining in each metric from a reference value.

12. The method of claim 10 , wherein performance loss includes at least the capacity loss, and the capacity loss includes at least one of a loss of active host sites and a loss of free lithium ions in a lithium-ion battery or battery cell.

13. The method of claim 1 , wherein determining performance loss of the battery or battery cell further includes identifying the performance loss crossing a predetermined threshold indicating potential for critical failure of a battery or battery cell.

14. The method of claim 1 , wherein determining previously unknown performance loss of the battery or battery cell over time includes determining previously unknown chronological path-dependent performance loss of the battery or battery cell over a succession of selected time periods.

15. The method of claim 14 , wherein the selected time periods have different lengths.

16. The method of claim 1 , wherein controlling the operation of the battery or battery cell includes at least one of adjusting a temperature or pressure around the battery or battery cell, adjusting a voltage output of the battery or battery cell, adjusting a power supplied to a load of the battery or battery cell, adjusting a state of charge level, and adjusting an operating condition of the load.

17. A system for determining performance characteristics of a battery or battery cell, the system comprising:
a battery or battery cell having an aging profile;
monitoring hardware configured to sample aging-dependent performance characteristics of the battery or battery cell; and
a processor coupled to the monitoring hardware, and configured to:
determine unknown performance loss for different arbitrary aging conditions over different successive time intervals, the different arbitrary aging conditions having unknown consequences, from a comparison of the performance characteristics of the battery or battery cell deviating from baseline performance characteristics associated with a baseline aging condition, wherein the different arbitrary aging conditions are different from the baseline aging condition associated with the baseline performance characteristics;
predict an aging progression based on the determined previously unknown performance loss; and
control operation of the battery or battery cell dynamically in real time responsive to the predicted aging progression.

18. The system of claim 17 , wherein the battery or battery cell includes at least one electrochemical cell, and wherein the monitoring hardware includes at least one of a temperature sensor, a voltage sensor, and a current sensor configured to monitor the at least one electrochemical cell over time.

19. The system of claim 17 , further comprising a memory operably coupled on-board with the processor, wherein the baseline performance characteristics associated with the baseline aging condition are stored in the memory.

20. The system of claim 17 , wherein the sampled performance characteristics are represented as multiple sigmoid model rate expressions and their parameters, wherein each multiple sigmoid model rate expression covers an aging mechanism within each distinct aging condition over time.

21. The system of claim 17 , wherein the processor is further configured to perform thermodynamic analysis on the sampled performance characteristics.

Assignees

• Gering Kevin L
• Battelle Energy Alliance Llc

Inventors

• Gering Kevin L

Classifications

• G01R31/367 Primary

  Software therefor, e.g. for battery testing using modelling or look-up tables · CPC title

• G01R31/392

  Determining battery ageing or deterioration, e.g. state of health · CPC title

• G01R31/3679

  Physics · mapped topic

• G01R31/3651 Primary

  Physics · mapped topic