A novel quantitative electrochemical aging model considering side reactions for lithium-ion batteries

被引:74
作者
Zhang, Xi [1 ]
Gao, Yizhao [1 ]
Guo, Bangjun [1 ]
Zhu, Chong [1 ]
Zhou, Xuan [2 ]
Wang, Lin [3 ]
Cao, Jianhua [3 ]
机构
[1] Shanghai Jiao Tong Univ, Sch Mech Engn, Shanghai, Peoples R China
[2] Kettering Univ, Dept Elect & Comp Engn, Flint, MI USA
[3] Shanghai & Prop Auto Technol Co Ltd, Shanghai, Peoples R China
基金
中国国家自然科学基金;
关键词
Lithium-ion batteries; Quantitative electrochemical aging model; Side reactions; Transfer-function type; Post-mortem analysis; Macroscopic and microscopic validation; SOLID-ELECTROLYTE INTERPHASE; DEGRADATION MODEL; STATE; HEALTH; CHARGE; CELLS; LAYER; MECHANISMS; PHYSICS; GROWTH;
D O I
10.1016/j.electacta.2020.136070
中图分类号
O646 [电化学、电解、磁化学];
学科分类号
081704 ;
摘要
A novel quantitative electrochemical aging model for lithium-ion batteries considering side reactions is proposed in this paper. The resistance of solid electrolyte interphase and the thickness of deposited layer caused by side reactions are utilized as degradation representatives to explicitly quantify the aging effects. The aging model is established through deriving the transfer function relationship between the aging representatives and input current history. Therefore, the gap between macroscopic (battery operating mode) and microscopic (aging mechanism) can be well bridged. The aging mechanisms for the lithium-ion batteries are well identified by comprehensive post-mortem analysis. The experimental results demonstrate that the irreversible side reactions occurring at the surface of anode particles are the primary cause for performance degradation in this study. To verify the proposed aging model, the comparisons are made between experimental and simulated results at both macroscopic cell-level (cell voltage response, capacity fade, and solid-electrolyte interphase resistance increase) and microscopiclevel (deposited-layer growth). The capacity decay error is bounded to 3% up to 400 cycles. The results demonstrate that the presented transfer-function type aging model is capable of predicting battery degradation severity precisely. (C) 2020 Elsevier Ltd. All rights reserved.
引用
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页数:14
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