Battery management apparatus and method

Patent metadata

Field	Value
Publication number	US-2023358812-A1
Application number	US-202118038081-A
Country	US
Kind code	A1
Filing date	Nov 26, 2021
Priority date	Nov 26, 2020
Publication date	Nov 9, 2023
Grant date	—

Abstract

A battery management apparatus according to an embodiment of the present disclosure includes: a feature value extracting unit configured to extract a feature value of a learning battery at every charging and discharging cycle; a first state judging unit configured to judge a state of the learning battery at every charging and discharging cycle, based on the feature value extracted by the feature value extracting unit and a criterion value preset to correspond to the feature value; a labelling unit configured to set a label for the feature value of the learning battery at every charging and discharging cycle, based on the state of the learning battery judged by the first state judging unit; a model learning unit configured to learn a classification model for judging a state of an analysis battery based on the feature value for which the label is set by the labelling unit; and a second state judging unit configured to judge the state of the analysis battery based on the classification model learned by the model learning unit.

First claim

1 . A battery management apparatus, comprising:
a feature value extracting unit extracting a feature value of a learning battery at a charging and discharging cycle of the learning battery; a first state judging unit judging a state of the learning battery based on the feature value extracted by the feature value extracting unit and a criterion value corresponding to the feature value; a labelling unit setting a label for the feature value of the learning battery based on the state of the learning battery judged by the first state judging unit; a model learning unit learning a classification model for judging a state of an analysis battery based on the feature value of the learning battery; and a second state judging unit judging the state of the analysis battery based on the classification model learned by the model learning unit.

2 . The battery management apparatus according to claim 1 , wherein the first state judging unit judges the state of the learning battery as a normal state or a defective state at every charging and discharging cycle of the learning battery.

3 . The battery management apparatus according to claim 1 ,
wherein when the state of the learning battery is judged to be in the normal state, the labelling unit sets a first label to the feature value of the learning battery for a corresponding normal charging and discharging cycle, and wherein when the state of the learning battery is judged to be in the defective state, the labelling unit sets a second label to the feature value of the learning battery for a corresponding defective charging and discharging cycle.

4 . The battery management apparatus according to claim 3 , wherein the labelling unit sets the label for the feature value of the learning battery, based on the state of the learning battery judged at a predetermined charging and discharging cycle.

5 . The battery management apparatus according to claim 4 , wherein when the state of the learning battery is judged to be in the normal state at the predetermined charging and discharging cycle, the labelling unit sets the first label to with the feature value of the learning battery before the predetermined charging and discharging cycle, and
wherein when the state of the learning battery is judged to be in the defective state at the predetermined charging and discharging cycle, the labelling unit sets the second label to the feature value of the learning battery after the predetermined charging and discharging cycle.

6 . The battery management apparatus according to claim 3 , wherein when the state of the learning battery is judged to be in the defective state, the labelling unit sets the second label to the feature value of the learning battery for a subsequent charging and discharging cycle to the predetermined charging and discharging cycle.

7 . The battery management apparatus according to claim 3 , wherein the labelling unit counts the number of times that the state of the learning battery is judged as the defective state, and when the counted number is equal to or greater than a criterion number, the labelling unit sets the second label to the feature value of the learning battery after a last charging and discharging cycle at which the state of the learning battery is judged as the defective state.

8 . The battery management apparatus according to claim 1 , wherein the feature value extracting unit extracts a plurality of feature values for the learning battery, and
wherein the first state judging unit judges the state of the learning battery for each of the plurality of feature values at every charging and discharging cycle, based on the plurality of feature values of the learning battery and a criterion value corresponding to each of the plurality of feature values.

9 . The battery management apparatus according to claim 8 , wherein the labelling unit sets the label for each of the plurality of feature values at every charging and discharging cycle.

10 . The battery management apparatus according to claim 1 , wherein the second state judging unit extracts the feature value of the analysis battery at every charging and discharging cycle and judges the state of the analysis battery by inputting the extracted feature value to the learned classification model.

11 . A battery pack, comprising the battery management apparatus according to claim 1 .

12 . A battery management method, comprising the steps of:
extracting, by a feature value extracting unit, a feature value of a learning battery at a charging and discharging cycle of the learning battery; judging, by a first state judging unit, a state of the learning battery at every charging and discharging cycle based on the feature value extracted by the feature value extracting unit and a criterion value corresponding to the feature value; setting, by a labelling unit, a label for the feature value of the learning battery based on the state of the learning battery judged in the first state judging step; learning, by a model learning unit, a classification model for judging a state of an analysis battery based on the feature value of the learning battery; and judging, by a second state judging unit, the state of the analysis battery based on the classification model learned by the model learning unit.

Assignees

• Lg Chemical Ltd

Inventors

• Jo Pil-Sung
• Lee Seok-Kyeong
• Park Sung-Bin
• Park Soo-Min
• Lee Chang-Song

Classifications

• H02J7/80

  including monitoring or indicating arrangements · CPC title

• G01R31/367 Primary

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

• G06N20/00

  Machine learning · CPC title

• G01R31/3648

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

• H01M10/425

  Structural combination with electronic components, e.g. electronic circuits integrated to the outside of the casing (printed circuits H05K1/00) · CPC title