Online characterization of battery model parameters with augmented dynamic stimulus

Patent metadata

Field	Value
Publication number	US-2024134325-A1
Application number	US-202318308420-A
Country	US
Kind code	A1
Filing date	Apr 27, 2023
Priority date	Oct 12, 2022
Publication date	Apr 25, 2024
Grant date	—

Abstract

A method for intelligently generating a stimulus for use in characterization of parameters of a model of a battery may include dynamically analyzing a current drawn from the battery by a load, based on analysis of the current, determining a sink current for augmenting the current drawn by the load, and generating the sink current based on a determined need to update the parameters.

First claim

What is claimed is:

1 . A method for intelligently generating a stimulus for use in characterization of parameters of a model of a battery, comprising:
dynamically analyzing a current drawn from the battery by a load; based on analysis of the current, determining a sink current for augmenting the current drawn by the load; and generating the sink current based on a determined need to update the parameters.

2 . The method of claim 1 , wherein the parameters correspond to model parameters of an equivalent circuit model of the battery.

3 . The method of claim 1 , wherein determining the sink current comprises determining the sink current based on a signal-to-noise ratio requirement of an algorithm for estimating the parameters.

4 . The method of claim 1 , wherein determining the sink current comprises determining the sink current based on a spectral requirement of an algorithm for estimating the parameters.

5 . The method of claim 1 , wherein dynamically analyzing the current comprises measuring a battery current drawn from the battery and a battery voltage across terminals of the battery.

6 . The method of claim 1 , wherein dynamically analyzing the current comprises determining whether each of a plurality of frequency sub-bands have sufficient spectral content required to estimate parameters associated with such frequency sub-band in accordance with a requirement of an algorithm for estimating the parameters.

7 . The method of claim 1 , wherein the determined need to update the parameters is based on a change of temperature associated with the battery since a previous update of one or more of the parameters.

8 . The method of claim 1 , wherein the determined need to update the parameters is based on a comparison of a root-mean-square value of the current over a period of time to a preset threshold value.

9 . The method of claim 1 , wherein the determined need to update the parameters is based on whether a rate of change of a battery voltage across the terminals of the battery exceeds a preset threshold value.

10 . The method of claim 1 , wherein the determined need to update the parameters is based on whether the current is below a preset threshold value for a preset period of time.

11 . The method of claim 1 , wherein the determined need to update the parameters is based on a confidence associated with the parameters.

12 . The method of claim 1 , wherein:
dynamically analyzing the current drawn from the battery by the load comprises dynamically analyzing spectral content of the current present in each of a plurality of frequency sub-bands; and determining the sink current for augmenting the current drawn by the load comprises determining, based on analyzing spectral content of the current present in each of the plurality of frequency sub-bands, an augmented current needed for each sub-band in order to meet requirements of estimating parameters associated with such sub-band in accordance with an estimation algorithm.

13 . A system for intelligently generating a stimulus for use in characterization of parameters of a model of a battery, comprising circuitry for:
dynamically analyzing a current drawn from the battery by a load; based on analysis of the current, determining a sink current for augmenting the current drawn by the load; and generating the sink current based on a determined need to update the parameters.

14 . The system of claim 13 , wherein the parameters correspond to model parameters of an equivalent circuit model of the battery.

15 . The system of claim 13 , wherein determining the sink current comprises determining the sink current based on a signal-to-noise ratio requirement of an algorithm for estimating the parameters.

16 . The system of claim 13 , wherein determining the sink current comprises determining the sink current based on a spectral requirement of an algorithm for estimating the parameters.

17 . The system of claim 13 , wherein dynamically analyzing the current comprises measuring a battery current drawn from the battery and a battery voltage across terminals of the battery.

18 . The system of claim 13 , wherein dynamically analyzing the current comprises determining whether each of a plurality of frequency sub-bands have sufficient spectral content required to estimate parameters associated with such frequency sub-band in accordance with a requirement of an algorithm for estimating the parameters.

19 . The system of claim 13 , wherein the determined need to update the parameters is based on a change of temperature associated with the battery since a previous update of one or more of the parameters.

20 . The system of claim 13 , wherein the determined need to update the parameters is based on a comparison of a root-mean-square value of the current over a period of time to a preset threshold value.

21 . The system of claim 13 , wherein the determined need to update the parameters is based on whether a rate of change of a battery voltage across the terminals of the battery exceeds a preset threshold value.

22 . The system of claim 13 , wherein the determined need to update the parameters is based on whether the current is below a preset threshold value for a preset period of time.

23 . The system of claim 13 , wherein the determined need to update the parameters is based on a confidence associated with the parameters.

24 . The system of claim 13 , wherein:
dynamically analyzing the current drawn from the battery by the load comprises dynamically analyzing spectral content of the current present in each of a plurality of frequency sub-bands; and determining the sink current for augmenting the current drawn by the load comprises determining, based on analyzing spectral content of the current present in each of the plurality of frequency sub-bands, an augmented current needed for each sub-band in order to meet requirements of estimating parameters associated with such sub-band in accordance with an estimation algorithm.

Assignees

• Cirrus Logic Int Semiconductor Ltd

Inventors

• Ebenezer Samuel P
• King Eric J
• Marchais Emmanuel A
• Hendrix Jon D
• Sabet Mohamed

Classifications

• G01R31/367

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

• G05B13/042 Primary

  in which a parameter or coefficient is automatically adjusted to optimise the performance · CPC title