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

Rui Li, Liying Bao, Lai Chen*, Cheng Zha, Jingyang Dong, Nan Qi, Rui Tang, Yun Lu, Meng Wang, Rong Huang, Kang Yan, Yuefeng Su, Feng Wu

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

27 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)3055-3079
Number of pages25
JournalScience Bulletin
Volume68
Issue number23
DOIs
Publication statusPublished - 15 Dec 2023

Keywords

  • Accelerated aging
  • Aging mechanism
  • Battery lifetime prediction
  • Degradation mode
  • Lifetime model
  • Lithium-ion battery

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