Invention Grant
- Patent Title: Deep learning approach for battery aging model
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Application No.: US16273505Application Date: 2019-02-12
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Publication No.: US11131713B2Publication Date: 2021-09-28
- Inventor: Ali Hooshmand , Mehdi Assefi , Ratnesh Sharma
- Applicant: NEC Laboratories America, Inc.
- Applicant Address: US NJ Princeton
- Assignee: NEC Laboratories America, Inc.
- Current Assignee: NEC Laboratories America, Inc.
- Current Assignee Address: US NJ Princeton
- Agent Joseph Kolodka
- Main IPC: G01R31/367
- IPC: G01R31/367 ; G06N3/08 ; G06N3/04 ; H01M10/42 ; G06N20/20 ; G01R31/382 ; G06F17/18

Abstract:
A computer-implemented method predicting a life span of a battery storage unit by employing a deep neural network is presented. The method includes collecting energy consumption data from one or more electricity meters installed in a structure, analyzing, via a data processing component, the energy consumption data, removing one or more features extracted from the energy consumption data via a feature engineering component, partitioning the energy consumption data via a data partitioning component, and predicting battery capacity of the battery storage unit via a neural network component sequentially executing three machine learning techniques.
Public/Granted literature
- US20190257886A1 DEEP LEARNING APPROACH FOR BATTERY AGING MODEL Public/Granted day:2019-08-22
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