公开(公告)号：US20190257886A1

公开(公告)日：2019-08-22

申请号：US16273505

申请日：2019-02-12

Applicant: NEC Laboratories America, Inc.

Inventor： Ali Hooshmand ,  Mehdi Assefi ,  Ratnesh Sharma

IPC: G01R31/367 ,  G06N3/08 ,  G06N3/04 ,  G06F17/18 ,  G06N20/20 ,  G01R31/382 ,  H01M10/42

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.

公开(公告)号：US11131713B2

公开(公告)日：2021-09-28

申请号：US16273505

申请日：2019-02-12

Applicant: NEC Laboratories America, Inc.

Inventor： Ali Hooshmand ,  Mehdi Assefi ,  Ratnesh Sharma

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.