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Mechanism and analytical modeling of high-rate discharge aging in lithium-ion batteries: Emphasizing cathode current collector dissolution and particle fracture

Author

Listed:
  • Han, Jingbo
  • Li, Guoliang
  • Zhu, Chong
  • Wang, Yansong
  • Fan, Guodong
  • Guo, Bangjun
  • Zhang, Xi

Abstract

Energy-type batteries with cathode materials of LiMnxNiyCozO2 (NMC) are widely utilized in electric vehicles (EVs) owing to their excellent energy density characteristics. With the increasing number of high-power application scenarios, it has become crucial to investigate the aging mechanisms of energy-type batteries under high-rate discharge conditions and to quantitatively analyze the aging phenomena. This study first conducts accelerated aging tests at 1C, 2C, and 3C discharge rates, and employs various macro and micro testing techniques to thoroughly analyze the physical processes of battery aging. The results indicate that cathode current collector dissolution, Al deposition on the anode, and cathode particle fracture are the primary causes of capacity decay. Additionally, by integrating the modified Butler-Volmer (BV) equation with the existing extended single particle model (ESPM), the accuracy of voltage simulation at high discharge rates is enhanced. Finally, combining the aforementioned aging mechanisms, the electrochemical model, and the thermal resistance network model, a comprehensive electrochemical-thermal-aging coupled model is established. Validation results at different discharge aging rates demonstrate that the model can achieve high-accuracy state of health (SOH) estimation throughout the entire battery lifecycle and accurately simulate discharge curves at various rates.

Suggested Citation

  • Han, Jingbo & Li, Guoliang & Zhu, Chong & Wang, Yansong & Fan, Guodong & Guo, Bangjun & Zhang, Xi, 2025. "Mechanism and analytical modeling of high-rate discharge aging in lithium-ion batteries: Emphasizing cathode current collector dissolution and particle fracture," Applied Energy, Elsevier, vol. 393(C).
    • Handle: RePEc:eee:appene:v:393:y:2025:i:c:s0306261925007780
    DOI: 10.1016/j.apenergy.2025.126048
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    References listed on IDEAS

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    1. Gao, Yizhao & Liu, Chenghao & Chen, Shun & Zhang, Xi & Fan, Guodong & Zhu, Chong, 2022. "Development and parameterization of a control-oriented electrochemical model of lithium-ion batteries for battery-management-systems applications," Applied Energy, Elsevier, vol. 309(C).
    2. Li, J. & Adewuyi, K. & Lotfi, N. & Landers, R.G. & Park, J., 2018. "A single particle model with chemical/mechanical degradation physics for lithium ion battery State of Health (SOH) estimation," Applied Energy, Elsevier, vol. 212(C), pages 1178-1190.
    3. Li, Changlong & Cui, Naxin & Wang, Chunyu & Zhang, Chenghui, 2021. "Reduced-order electrochemical model for lithium-ion battery with domain decomposition and polynomial approximation methods," Energy, Elsevier, vol. 221(C).
    4. Liu, Yang & Zhang, Caiping & Jiang, Jiuchun & Zhang, Linjing & Zhang, Weige & Lao, Li & Yang, Shichun, 2023. "A 3D distributed circuit-electrochemical model for the inner inhomogeneity of lithium-ion battery," Applied Energy, Elsevier, vol. 331(C).
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