Method and apparatus for estimating state of battery

Patent metadata

Field	Value
Publication number	US-10509077-B2
Application number	US-201815864252-A
Country	US
Kind code	B2
Filing date	Jan 8, 2018
Priority date	Jan 17, 2017
Publication date	Dec 17, 2019
Grant date	Dec 17, 2019

Abstract

A battery state estimation method and apparatus are provided. Sensing data of a battery is received, and feature information is acquired by preprocessing the sensing data. The preprocessed sensing data is selected based on the feature information, and state information of the battery is determined based on at least one of the selected preprocessed sensing data or previous state information of the battery.

First claim

What is claimed is:

1. A battery state estimation method comprising:
receiving sensing data of a battery;
acquiring feature information by preprocessing the sensing data;
selecting the preprocessed sensing data based on the feature information; and
determining state information of the battery based on either one or both of the selected preprocessed sensing data and previous state information of the battery.

2. The battery state estimation method of claim 1 , wherein the feature information comprises any one or any combination of a data size of the preprocessed sensing data and a variance value of the preprocessed sensing data.

3. The battery state estimation method of claim 1 , wherein the selecting of the preprocessed sensing data comprises:
calculating a reliability of the preprocessed sensing data based on the feature information; and
selecting the preprocessed sensing data by comparing the reliability to a threshold.

4. The battery state estimation method of claim 1 , wherein the selection of the preprocessed sensing data comprises selecting the preprocessed sensing data in response to a length of the preprocessed sensing data being greater than or equal to a threshold.

5. The battery state estimation method of claim 1 , wherein the selection of the preprocessed sensing data comprises:
calculating a deviation between each of sample values of the preprocessed sensing data and a previous sample value of the each of the sample values; and
selecting the preprocessed sensing data based on a variance of the calculated deviation.

6. The battery state estimation method of claim 1 , wherein the determining of the state information comprises determining the state information based on Gall the previous state information in response to the preprocessed sensing data not being selected.

7. The battery state estimation method of claim 1 , wherein the determining of the state information comprises determining the previous state information as the state information in response to the preprocessed sensing data not being selected.

8. The battery state estimation method of claim 1 , wherein the determining of the state information comprises determining the state information based on the preprocessed sensing data in response to the preprocessed sensing data being selected.

9. The battery state estimation method of claim 1 , wherein the acquiring of the feature information comprises:
filtering the sensing data; and
downsampling the filtered sensing data.

10. The battery state estimation method of claim 1 , wherein
the preprocessed sensing data corresponds to data suitable for estimation of a state of the battery, in response to the preprocessed sensing data being selected, and
the preprocessed sensing data corresponds to data unsuitable for the estimation of the state of the battery, in response to the preprocessed sensing data not being selected.

11. A non-transitory computer-readable storage medium storing instructions, that when executed by a processor, causes the processor to perform the battery state estimation method of claim 1 .

12. A battery state estimation apparatus comprising:
a controller configured to receive sensing data of a battery, to acquire feature information by preprocessing the sensing data, select the preprocessed sensing based on the feature information, and to determine state information of the battery based on either one or both of the selected preprocessed sensing data and previous state information of the battery.

13. The battery state estimation apparatus of claim 12 , wherein the feature information comprises any one or any combination of a data size of the preprocessed sensing data and a variance value of the preprocessed sensing data.

14. The battery state estimation apparatus of claim 12 , wherein the controller is further configured to calculate a reliability of the preprocessed sensing data based on the feature information and to select the preprocessed sensing data by comparing the reliability to a threshold.

15. The battery state estimation apparatus of claim 12 , wherein the controller is further configured to select the preprocessed sensing data in response to a length of the preprocessed sensing data being greater than or equal to a threshold.

16. The battery state estimation apparatus of claim 12 , wherein the controller is further configured to calculate a deviation between each of sample values of the preprocessed sensing data and a previous sample value of the each of the sample values, and to select the preprocessed sensing data based on a variance of the calculated deviation.

17. The battery state estimation apparatus of claim 12 , wherein the controller is further configured to determine the state information based on the previous state information in response to the preprocessed sensing data not being selected.

18. The battery state estimation apparatus of claim 12 , wherein the controller is further configured to determine the previous state information as the state information in response to the preprocessed sensing data not being selected.

19. The battery state estimation apparatus of claim 12 , wherein the controller is further configured to determine the state information based on the preprocessed sensing data in response to the preprocessed sensing data being selected.

20. The battery state estimation apparatus of claim 12 , wherein the controller is further configured to filter the sensing data and to downsample the filtered sensing data.

21. The battery state estimation apparatus of claim 12 , wherein
the preprocessed sensing data corresponds to data suitable for estimation of a state of the battery, in response to the preprocessed sensing data being selected, and
the preprocessed sensing data corresponds to data unsuitable for the estimation of the state of the battery, in response to the preprocessed sensing data not being selected.

Assignees

• Samsung Electronics Co Ltd

Inventors

• Park Sangdo
• You Kaeweon

Classifications

• G01R31/3835

  involving only voltage measurements · CPC title

• G01R31/3648 Primary

  comprising digital calculation means, e.g. for performing an algorithm · CPC title

• 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

• G01R31/387

  Determining ampere-hour charge capacity or SoC · CPC title