Method and apparatus to estimate state of battery based on battery charging voltage data

• US 10,114,078 B2
• Filed: 09/10/2015
• Issued: 10/30/2018
• Est. Priority Date: 02/06/2015
• Status: Active Grant

• Current Assignee: Samsung Electronics Co. Ltd. (Samsung Group)
• Original Assignee: Samsung Electronics Co. Ltd. (Samsung Group)
• Inventors: Park, Jeonghyun
• Primary Examiner(s): Kuan, John
• Application Number:
  US14/849,913
• Publication Number:
  US 20160231388A1
• Time in Patent Office: 1,146 Days
• Field of Search: None
• CPC Class Codes: G01R 31/367 Software therefor, e.g. for battery testing using modelling or look-up tables
• CPC Class Codes: G01R 31/3835 involving only voltage measurements
• CPC Class Codes: G01R 31/392 Determining battery ageing or deterioration, e.g. state of health
• CPC Class Codes: Y02E 60/10 Energy storage using batteries

Abstract

A method and an apparatus to estimate a battery state include a sensor, a data extractor, and a state estimator. The sensor is configured to sense charging voltage data, and the data extractor is configured to extract partial data corresponding to a section from the sensed charging voltage data. The state estimator is configured to estimate a state of a current battery using the extracted partial data.

Claims

1. A computing apparatus for performing a real-time battery stabilization using battery state estimation, the computing apparatus comprising:

one or more sensors configured to sense charging voltage data for a current battery and for a plurality of batteries at a battery life termination point, wherein the sensed charging voltage data for the plurality of batteries at the battery life termination point is pre-stored; and

one or more processors, in communication with the one or more sensors, configured to;

extract partial data corresponding to a section from the sensed charging voltage data;

determine a first distance between data extracted from pre-stored charging voltage data of an initial battery life and the partial data extracted from the sensed charging voltage data of the current battery, for reducing a computation or calculation workload using the partial data in the determining of the first distance;

determine a second distance between the data extracted from the pre-stored charging voltage data of the initial battery life and data extracted from the pre-stored charging voltage data of the plurality of batteries at the battery life termination point;

determine a score using the first distance and the second distance; and

estimate an abnormal state of the current battery using the score, such that the real-time battery stabilization is provided using a result of the estimating.

2. The apparatus of claim 1, wherein the sensed charging voltage data comprises charging voltage data of the initial battery life, charging voltage data of the plurality of batteries at the battery life termination point, and charging voltage data of the current battery.

3. The apparatus of claim 1, wherein the one or more processors are configured to extract the partial data, as charging voltage data by extracting the charging voltage data for a predetermined first amount of time from the sensed charging voltage data of the current battery, by extracting the charging voltage data at a predetermined time interval from the sensed charging voltage data of the current battery, or by extracting the charging voltage data at the predetermined time interval for the predetermined first amount of time from the sensed charging voltage data of the current battery.

4. The apparatus of claim 3, wherein the data extracted from the sensed charging voltage data and data extracted from pre-obtained charging voltage data of an initial battery life are extracted using a same extraction process.

5. The apparatus of claim 1, wherein the score is dependent on a relationship between the first distance and the second distance.

6. The apparatus of claim 1, wherein the one or more processors are configured to determine the first and second distances using at least one of a Euclidian distance calculation method, a Mahalanobis distance calculation distance, and a cosine similarity calculation method.

7. The apparatus of claim 1, wherein the one or more processors are configured to further

calculate a score S_t as the score using an equation

8. The apparatus of claim 1, wherein the one or more processors are further configured to estimate the abnormal state by comparing the determined score to a prestored score history.

9. The apparatus of claim 7, wherein the one or more processors are further configured to estimate the abnormal state in response to a fluctuation range of the score S_t being greater than a threshold value, and display a warning corresponding to the abnormal state.

10. The apparatus of claim 7, wherein the one or more processors are further configured to estimate the abnormal state in response to a fluctuation range of the score S_t being greater than an average of fluctuation ranges measured prior to the calculating of the score S_t and being less than a threshold value, and perform the real-time battery stabilization in response to the abnormal state.

11. The apparatus of claim 7, wherein the one or more processors are further configured to calculate a variance of scores S_t, estimate the abnormal state in response to the calculated variance being greater than a threshold value, and display a warning corresponding to the abnormal state.

12. A battery state estimating method implemented by one or more processors of a computing apparatus, of performing a real-time battery stabilization using a battery state estimation, the method comprising:

using one or more sensors for the computing apparatus, sensing charging voltage data for a current battery and for a plurality of batteries at a battery life termination point, wherein the sensed charging voltage data for the plurality of batteries at the battery life termination point is pre-stored

extracting, using the one or more processors in communication with the one or more sensors, partial data corresponding to a section from the sensed charging voltage data;

determining, using the one or more processors, a first distance between data extracted from pre-stored charging voltage data of an initial battery life and the partial data extracted from the sensed charging voltage data of the current battery, for reducing a computation or calculation workload using the partial data in the determining of the first distance;

determining, using the one or more processors, a second distance between the data extracted from the pre-stored charging voltage data of the initial battery life and data extracted from the pre-stored charging voltage data of the plurality of batteries at the battery life termination point;

determining, using the one or more processors, a score using the first distance and the second distance; and

estimating, using the one or more processors, an abnormal state of the current battery using the score, such that the real-time battery stabilization is provided using a result of the estimating.

13. The method of claim 12, wherein the sensed charging voltage data comprises charging voltage data of the initial battery life, charging voltage data of the plurality of batteries at the battery life termination point, and charging voltage data of the current battery.

14. The method of claim 12, wherein the extracting of the partial data comprises one of:

extracting charging voltage data for a predetermined amount of time from the sensed charging voltage data of the current battery,

extracting charging voltage data at a predetermined time interval from the sensed charging voltage data of the current battery, and

extracting charging voltage data at the predetermined time interval for the predetermined amount of time from the sensed charging voltage data of the current battery.

15. The method of claim 12, wherein the score is dependent on a relationship between the first distance and the second distance.

16. The method of claim 12, wherein the determining of the first and second distances further comprises:

determining the first and second distances using one of a Euclidian distance calculation method, a Mahalanobis distance calculation distance, and a cosine similarity calculation method.

17. The method of claim 12, wherein the determining the score further comprises:

calculating a score S_t as the score, using an equation

18. The method of claim 12, wherein the estimating of the abnormal state of the current battery further comprises:

estimating the abnormal state of the current battery in response to a fluctuation range of the score being greater than a threshold value; and

displaying a warning corresponding to the abnormal state.

19. The method of claim 12, wherein the estimating of the abnormal state of the current battery further comprises:

estimating the abnormal state of the current battery in response to a fluctuation range of the score being greater than an average of fluctuation ranges measured prior to the determining of the score and being less than a threshold value; and

performing the real-time battery stabilization in response to the abnormal state.

20. A non-transitory computer-readable storage medium comprising a program comprising instructions to cause a computer to perform the method of claim 12.