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Data‐Driven Online Prognosis of Rechargeable Batteries: Prospect and Perspective.

Authors :
Liu, Kun‐Yu
Wang, Ting‐Ting
Liu, Xinyan
Peng, Hong‐Jie
Source :
Batteries & Supercaps; Mar2024, Vol. 7 Issue 3, p1-11, 11p
Publication Year :
2024

Abstract

Along with the growing popularity of electric vehicles (EVs) and smart grids, rechargeable batteries are playing an increasingly important role in the field of energy storage. To ensure a safe and stable operation, it remains essential to estimate the states of batteries accurately and efficiently in advance. Herein, we provide a perspective on data‐driven online prognosis of rechargeable batteries, where its scope and superiorities are first introduced. Four promising application scenarios in real world including battery manufacture, EVs, smart grid, and battery recycling are then discussed, followed by the challenges that require further investigation. We anticipate this perspective to attract more interest to this field, to illuminate potential directions for future researches, and to broaden the context of data‐driven physical and engineering sciences. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
25666223
Volume :
7
Issue :
3
Database :
Complementary Index
Journal :
Batteries & Supercaps
Publication Type :
Academic Journal
Accession number :
175947366
Full Text :
https://doi.org/10.1002/batt.202300596