The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Nov. 26, 2024

Filed:

Mar. 08, 2021
Applicant:

Toyota Research Institute, Inc., Los Altos, CA (US);

Inventors:

Linnette Teo, Seattle, WA (US);

Chirranjeevi Balaji Gopal, San Jose, CA (US);

Assignee:

TOYOTA RESEARCH INSTITUTE, INC., Los Altos, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G07C 5/08 (2006.01); B60L 58/12 (2019.01); B60L 58/16 (2019.01); G06N 3/04 (2023.01); G06N 3/08 (2023.01); H01M 10/48 (2006.01);
U.S. Cl.
CPC ...
G07C 5/0808 (2013.01); B60L 58/12 (2019.02); B60L 58/16 (2019.02); G06N 3/04 (2013.01); G06N 3/08 (2013.01); H01M 10/48 (2013.01); B60L 2240/545 (2013.01); B60L 2240/547 (2013.01); B60L 2240/549 (2013.01); H01M 2220/20 (2013.01);
Abstract

An approach to forecasting battery health as a dynamic time-series problem as opposed to a static prediction problem is presented. Systems and methods disclosed herein forecast a trajectory to failure by predicting a path to failure as opposed to only predicting when the battery may fail. A machine-learning model is implemented that extracts unique features taken from time-series data, such as time snippets of charging data. The raw time-series data may include current voltage and temperature with complex transformations and without capturing a full cycle, which permits wider applicability to instances of varying depth of discharge (DoD).


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