加速老化
电池(电)
可靠性工程
锂离子电池
桥接(联网)
加速寿命试验
计算机科学
一致性(知识库)
充电周期
工程类
人工智能
汽车蓄电池
功率(物理)
心理学
计算机网络
发展心理学
成熟度(心理)
物理
量子力学
作者
Yulin Deng,Liying Bao,Lai Chen,Cheng Zha,Jingyang Dong,Nan Qi,Rui Tang,Yun Lu,Meng Wang,Rong Huang,Kang Yan,Yuefeng Su,Feng Wu
标识
DOI:10.1016/j.scib.2023.10.029
摘要
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.
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