Method and apparatus for monitoring battery state

Patent metadata

Field	Value
Publication number	US-10094806-B2
Application number	US-201615064898-A
Country	US
Kind code	B2
Filing date	Mar 9, 2016
Priority date	Mar 9, 2015
Publication date	Oct 9, 2018
Grant date	Oct 9, 2018

Abstract

A method and an apparatus for monitoring battery state are provided. A method of monitoring battery state involves collecting vibration information based on a signal from an acceleration sensor, calculating a cumulative impact based on the vibration information, and estimating a degree of damage to a battery based on the cumulative impact.

First claim

What is claimed is:

1. A method of monitoring battery state, comprising:
collecting vibration information associated with a target battery, based on signals from one or more acceleration sensors attached to the target battery;
calculating a cumulative impact based on the vibration information associated with the target battery; and
estimating a degree of damage to the target battery based on the cumulative impact.

2. A method of monitoring battery state, comprising:
collecting vibration information based on a signal from an acceleration sensor;
calculating a cumulative impact based on the vibration information; and
estimating a degree of damage to a battery based on the cumulative impact, wherein the collecting of the vibration information further comprises:
monitoring the signal from the acceleration sensor;
extracting an acceleration sensor signal block for a predetermined period of time in response to an amplitude of the signal being greater than or equal to a predetermined first threshold value;
determining a frequency and an impact magnitude level of the acceleration sensor signal block; and
generating an impact profile based on the impact magnitude level and a number of events corresponding to a frequency band including the determined frequency.

3. The method of claim 2 , wherein the determining of the frequency and the impact magnitude level of the acceleration sensor signal block comprises:
converting the acceleration sensor signal block to a frequency domain;
selecting, from the frequency domain, a main impact response frequency at which a frequency response coefficient exceeds a predetermined second threshold value; and
determining the main impact response frequency to be the frequency of the acceleration sensor signal block.

4. The method of claim 2 , wherein the determining of the frequency and the impact magnitude level of the acceleration sensor signal block comprises:
calculating an average acceleration amplitude of the acceleration sensor signal block; and
selecting an impact magnitude level among a plurality of impact magnitude levels based on the average acceleration amplitude.

5. The method of claim 1 , wherein the calculating of the cumulative impact comprises:
calculating the cumulative impact based on an impact profile generated using the vibration information and based on a weighting profile.

6. The method of claim 5 , wherein the weighting profile is generated based on a frequency weighting profile indicating a degree of influence of a frequency band on the degree of damage, and an impact magnitude weighting profile indicating a degree of influence of an impact magnitude level on the degree of damage.

7. The method of claim 5 , wherein the calculating of the cumulative impact comprises:
calculating the cumulative impact by calculating an element-wise product between a matrix of the weighting profile and a matrix of the impact profile.

8. The method of claim 1 , wherein the estimating of the degree of damage comprises:
estimating a total magnitude of damage due to impacts using the cumulative impact.

9. A method of monitoring battery state, comprising:
collecting vibration information based on a signal from an acceleration sensor;
calculating a cumulative impact based on the vibration information;
estimating a degree of damage to a target battery based on the cumulative impact
measuring a degree of similarity between a pattern of reference sensing data obtained by sensing at least one of a voltage, a current, and a temperature of a normal battery and a pattern of target sensing data obtained by sensing at least one of a voltage, a current, and a temperature of the target battery; and
estimating a state of the target battery using the estimated degree of damage and the measured degree of similarity.

10. The method of claim 9 , wherein the estimating of the state of the target battery using the degree of damage and the degree of similarity comprises:
determining the target battery to be in an error state in response to the degree of similarity being determined to be less than a predetermined value; and
determining a contact fault as a cause of the error state based on the estimated degree of damage.

11. The method of claim 10 , wherein the estimating of the contact fault is performed using at least one machine learning classification model among a neural network, a support vector machine, and a decision tree model.

12. An apparatus for monitoring battery state, comprising:
a collector configured to collect vibration information associated with a target battery, based on signals from one or more acceleration sensors attached to the target battery;
an impact calculator configured to calculate a cumulative impact based on the vibration information associated with the target battery; and
a damage estimator configured to estimate a degree of damage to the target battery based on the cumulative impact.

13. The apparatus of claim 12 , wherein the collector comprises:
a monitorer configured to monitor the signals;
a block extractor configured to extract an acceleration sensor signal block for a predetermined period of time in response to a corresponding amplitude of the acceleration sensor signals being greater than or equal to a predetermined first threshold value;
a determiner configured to determine a frequency and an impact magnitude level of the acceleration sensor signal block; and
a profile generator configured to generate an impact profile based on the impact magnitude level and a number of events corresponding to a frequency band including the determined frequency.

14. The apparatus of claim 13 , wherein the determiner is configured to convert the acceleration sensor signal block to a frequency domain; select, from the frequency domain, a main impact response frequency at which a frequency response coefficient exceeds a predetermined second threshold value; and determine the main impact response frequency to be the frequency of the acceleration sensor signal block.

15. The apparatus of claim 13 , wherein the determiner is configured to calculate an average acceleration amplitude of the acceleration sensor signal block and select an impact magnitude level among a plurality of impact magnitude levels based on the average acceleration amplitude.

16. The apparatus of claim 12 , wherein the impact calculator is configured to calculate the cumulative impact based on an impact profile generated using the vibration information and based on a weighting profile.

17. The apparatus of claim 16 , wherein the weighting profile is generated based on a frequency weighting profile indicating a degree of influence of a frequency band on the degree of damage and an impact magnitude weighting profile indicating a degree of influence of an impact magnitude level on the degree of damage.

18. The apparatus of claim 12 , wherein the damage estimator is configured to estimate a total magnitude of damage due to impacts using the cumulative impact.

19. The apparatus of claim 12 , further comprising:
a similarity measurer configured to measure a degree of similarity between a pattern of reference sensing data obtained by sensing at least one of a voltage, a current, and a temperature of a normal battery and a pattern of target sensing data obtained by sensing at least one of a voltage, a current, and a temperature of the target battery; and
a state estimator configured to determine a state of the target battery using the estimated degree of damage and the measured degree of similarity.

Assignees

• Samsung Electronics Co Ltd

Inventors

• Sung Jaemo
• Park Jeonghyun
• Yeo Taejung

Classifications

• B60L2240/545

  Temperature · CPC title

• G01N29/12 Primary

  by measuring frequency or resonance of acoustic waves {(measuring frequency or resonant frequency of mechanical vibrations or acoustic waves in general G01H1/06, G01H3/04, G01H13/00; acoustic resonators G10K11/04; vibration or shock testing of structures G01M7/00)} · CPC title

• G01N29/4454

  Signal recognition, e.g. specific values or portions, signal events, signatures · CPC title

• B60L2240/549

  Current · CPC title

• G01N29/4427

  with stored values, e.g. threshold values · CPC title