电池(电)
预言
降级(电信)
可靠性工程
锂离子电池
钥匙(锁)
计算机科学
阳极
工程类
可靠性(半导体)
功率(物理)
电信
计算机安全
化学
物理
量子力学
物理化学
电极
作者
Xiao Hu,Le Xu,Xianke Lin,Michael Pecht
出处
期刊:Joule
[Elsevier]
日期:2020-01-08
卷期号:4 (2): 310-346
被引量:752
标识
DOI:10.1016/j.joule.2019.11.018
摘要
Lithium-ion batteries have been widely used in many important applications. However, there are still many challenges facing lithium-ion batteries, one of them being degradation. Battery degradation is a complex problem, which involves many electrochemical side reactions in anode, electrolyte, and cathode. Operating conditions affect degradation significantly and therefore the battery lifetime. It is of extreme importance to achieve accurate predictions of the remaining battery lifetime under various operating conditions. This is essential for the battery management system to ensure reliable operation and timely maintenance and is also critical for battery second-life applications. After introducing the degradation mechanisms, this paper provides a timely and comprehensive review of the battery lifetime prognostic technologies with a focus on recent advances in model-based, data-driven, and hybrid approaches. The details, advantages, and limitations of these approaches are presented, analyzed, and compared. Future trends are presented, and key challenges and opportunities are discussed.
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