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Accelerated aging of lithium-ion batteries: bridging battery aging analysis and operational lifetime prediction.

Authors :
Li, Rui
Bao, Liying
Chen, Lai
Zha, Cheng
Dong, Jingyang
Qi, Nan
Tang, Rui
Lu, Yun
Wang, Meng
Huang, Rong
Yan, Kang
Su, Yuefeng
Wu, Feng
Source :
Science Bulletin. Dec2023, Vol. 68 Issue 23, p3055-3079. 25p.
Publication Year :
2023

Abstract

[Display omitted] The exponential growth of stationary energy storage systems (ESSs) and electric vehicles (EVs) necessitates a more profound understanding of the degradation behavior of lithium-ion batteries (LIBs), with specific emphasis on their lifetime. Accurately forecasting the lifetime of batteries under various working stresses aids in optimizing their operating conditions, prolonging their longevity, and ultimately minimizing the overall cost of the battery life cycle. Accelerated aging, as an efficient and economical method, can output sufficient cycling information in short time, which enables a rapid prediction of the lifetime of LIBs under various working stresses. Nevertheless, the prerequisite for accelerated aging-based battery lifetime prediction is the consistency of aging mechanisms. This review, by comprehensively summarizing the aging mechanisms of various components within LIBs and the battery degradation mechanisms under stress-accelerated conditions, provides a reference for evaluating the consistency of battery aging mechanisms. Furthermore, this paper introduces accelerated aging-based lifetime prediction models and offers constructive suggestions for future research on accelerated lifetime prediction of LIBs. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20959273
Volume :
68
Issue :
23
Database :
Academic Search Index
Journal :
Science Bulletin
Publication Type :
Academic Journal
Accession number :
174320203
Full Text :
https://doi.org/10.1016/j.scib.2023.10.029