IP Library › Granted Patent US 10,427,535
Granted Patent B2
US 10,427,535 · App. 15/360,522 · Granted Oct 1, 2019

Method and apparatus for battery management

Inventors: Sang Do Park (Seoul, KR); Kae Weon You (Hwaseong-si, KR)
Assignee: Samsung Electronics Co., Ltd.
B60L11/1851B60L58/10G01S19/42H02J7/0045B60L2240/622B60L2240/64B60L2240/662H02J2007/0096Y02T10/7005Y02T10/705Y02T10/7291Y02T90/16Y02T90/162
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Quick Facts
Patent No.
US 10,427,535
App. No.
15/360,522
Granted
Oct 1, 2019
Kind
B2
Abstract

The present disclosure is related to a battery management system which includes a location information obtainer configured to obtain location information of a battery, and an estimation model changer configured to change an estimation model to estimate an internal state of the battery according to a change in the location information.

Claims (32)

1. A battery management apparatus, comprising: a processor configured to: obtain a state of health (SOH) estimation model configured to estimate a SOH of a battery based on regional information; determine location information of the battery using measured data from a sensor; determine updated regional information corresponding to the location information, in response to the location information being determined to deviate from a region predefined in the SOH estimation model; update the SOH estimation model based on the updated regional information; generate an updated SOH of the battery being estimated using the updated SOH estimation model; and calculate a replacement time of the battery using the updated SOH of the battery generated from the estimation.

2. The apparatus of claim 1 , wherein the processor is further configured to determine the location information using the measured data from a global positioning system (GPS).

3. The apparatus of claim 1 , wherein the processor is further configured to periodically check for a change in the location information, or to check for a change in the location information based on a driving record of an electric vehicle (EV).

4. The apparatus of claim 1 , wherein the estimation model estimates the SOH of the battery based on either one or both of a neural network (NN) or a deep neural network (DNN).

5. The apparatus of claim 1 , wherein the regional information comprises any one or any combination of any two or more environmental factors of temperature, humidity, weather, geography, road conditions, or city characteristics of a local area.

6. The apparatus of claim 1 , wherein the processor is further configured to determine the updated regional information using data obtained through a charging cable of the battery.

7. The apparatus of claim 1 , wherein the processor is further configured to obtain the regional information from a remote server.

8. The apparatus of claim 1 , wherein the processor is further configured to recommend to a user to replace the battery when a value of the updated SOH is less than a health threshold.

9. The apparatus of claim 1 , wherein the SOH estimation model is further configured to indicate a usage environment of the battery based on initial location information.

10. The apparatus of claim 1 , wherein the processor is further configured to:

obtain internal data of an inside of the battery; and

generate the updated SOH based on the internal data, using the updated estimation model.

11. A processor-implemented method for battery management, the method comprising:

obtaining a state of health (SOH) estimation model configured to estimate a SOH of a battery based on regional information;

determining location information of the battery using measured data from a sensor;

determining updated regional information corresponding to the location information, in response to the location information being determined to deviate from a region predefined in the SOH estimation model;

updating the SOH estimation model based on the updated regional information;

generating an updated SOH of the battery being estimated using the updated SOH estimation model; and

calculating a replacement time of the battery using the updated SOH of the battery generated from the estimation.

12. The method of claim 11 , wherein the obtaining of the location information comprises determining the location information of the battery using the measured data from a global positioning system (GPS).

13. The method of claim 11 , wherein the determining of the location information comprises either one or both of periodically checking for a change in the location information, or checking for a change in the location information based on a driving record of an electric vehicle (EV) which includes the battery.

14. The method of claim 11 , wherein the estimation model estimates the SOH of the battery based on either one or both of a neural network (NN) or a deep neural network (DNN).

15. The method of claim 11 , wherein the regional information comprises any one or any combination of any two or more environmental factors of temperature, humidity, weather, geography, road conditions, or city characteristics of a local area.

16. The method of claim 11 , wherein the determining of the updated regional information comprises updating the updated regional information using data obtained through a charging cable of the battery.

17. The method of claim 11 , wherein the determining of the updated regional information comprises updating the updated regional information using data obtained from a server by communicating with the server using any one or any combination of any two or more of WiFi, Zigbee, near field communication (NFC), Bluetooth, or radio frequency (RF).

18. A non-transitory computer-readable storage medium storing instructions that, when executed by a processor, cause the processor to perform the method of claim 11 .

19. A processor-implemented method for battery management, the method comprising:

obtaining a state of health (SOH) estimation model configured to estimate a SOH of a battery based on regional information;

determining location information of the battery using measured data from a sensor;

determining updated regional information corresponding to the location information, in response to the location information being determined to deviate from a region predefined in the SOH estimation model;

updating the SOH estimation model based on the updated regional information to estimate an updated SOH of the battery using the updated SOH estimation model; and

calculating a replacement time of the battery using the updated SOH of the battery generated from the estimation.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 23, 2016
From: PARK, SANG DO; YOU, KAE WEON
To: SAMSUNG ELECTRONICS CO., LTD.
Reel/Frame 040412/0642 →
Priority Claims (1)
KR 10-2015-0165064 · Nov 24, 2015 · national
Continuity (1)
Related Publication 20170144560A1 · May 25, 2017