A generalized physics-based calendar life model for Li-ion cells

被引:28
作者
Rahimian, Saeed Khaleghi [1 ]
Forouzan, Mehdi M. [1 ]
Han, Sangwoo [1 ]
Tang, Yifan [1 ]
机构
[1] SERES, Battery Technol Dept, Santa Clara, CA 95054 USA
关键词
Li-ion battery; Calendar life model; SEI Modeling; Ni-rich cathode; State of health estimation; PREDICTING CAPACITY FADE; GRAPHITE/LIFEPO4; CELL; CYCLE-LIFE; BATTERIES; ELECTROLYTE; STATE; SEI; MECHANISMS; SIMULATION; MORPHOLOGY;
D O I
10.1016/j.electacta.2020.136343
中图分类号
O646 [电化学、电解、磁化学];
学科分类号
081704 ;
摘要
A physics-based calendar life model is developed for Li-ion cells with a Ni-rich cathode and a graphite-silicon composite anode. Solid electrolyte interphase (SEI) growth on the anode particles, a cathode side reaction, and an electrolyte thermal decomposition are modeled. Loss of lithium ions in the SEI formation is responsible for the cell capacity fade during storage. However, the irregular lower capacity fade at 100% state of charge (SOC) compared to 80% SOC is explained by the oxidation of lithium compounds (e.g. Li2CO3) at cathode particles that provokes the reinsertion of lithium ions into the particles. The cathode unwanted reaction also causes the major growth in resistance at high SOCs due to gas generation. The electrolyte decomposition is also modeled to improve the resistance prediction at high temperatures. An excellent agreement between the model and the storage data at a broad range of temperatures and SOCs confirms the high-fidelity of the proposed model. The new model is general enough to predict the storage aging data of Li-ion cells with different cathode and anode chemistries. The algebraic expressions for estimating the capacity and resistance allows the model to be easily implemented in a battery management system for state of health estimation. (C) 2020 Elsevier Ltd. All rights reserved.
引用
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页数:12
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