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

doi:10.1016/j.scib.2023.10.029

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

Sci Bull (Beijing). 2023 Dec 15;68(23):3055-3079. doi: 10.1016/j.scib.2023.10.029. Epub 2023 Oct 29.

Authors

Rui Li¹, Liying Bao², Lai Chen³, Cheng Zha⁴, Jingyang Dong¹, Nan Qi¹, Rui Tang¹, Yun Lu¹, Meng Wang⁴, Rong Huang⁵, Kang Yan⁶, Yuefeng Su⁷, Feng Wu¹

Affiliations

¹ School of Materials Science and Engineering, Beijing Institute of Technology, Beijing 100081, China; Chongqing Innovation Center, Beijing Institute of Technology, Chongqing 401120, China.
² School of Materials Science and Engineering, Beijing Institute of Technology, Beijing 100081, China.
³ School of Materials Science and Engineering, Beijing Institute of Technology, Beijing 100081, China; Chongqing Innovation Center, Beijing Institute of Technology, Chongqing 401120, China. Electronic address: chenlai@bit.edu.cn.
⁴ Chongqing Innovation Center, Beijing Institute of Technology, Chongqing 401120, China.
⁵ Beijing Electric Vehicle Co., Ltd., Beijing 100176, China.
⁶ School of Materials Science and Engineering, Beijing Institute of Technology, Beijing 100081, China; Chongqing Innovation Center, Beijing Institute of Technology, Chongqing 401120, China. Electronic address: yankang@bit.edu.cn.
⁷ School of Materials Science and Engineering, Beijing Institute of Technology, Beijing 100081, China; Chongqing Innovation Center, Beijing Institute of Technology, Chongqing 401120, China. Electronic address: suyuefeng@bit.edu.cn.

PMID: 37926585
DOI: 10.1016/j.scib.2023.10.029

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.

Keywords: Accelerated aging; Aging mechanism; Battery lifetime prediction; Degradation mode; Lifetime model; Lithium-ion battery.

Publication types

Review