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An all coupled electrochemical-mechanical model for all-solid-state Li-ion batteries considering the effect of contact area loss and compressive pressure

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  • Shao, Yu-qiang
  • Liu, Huan-ling
  • Shao, Xiao-dong
  • Sang, Lin
  • Chen, Zeng-tao

Abstract

A fully coupled electrochemical-mechanical theoretical model for all-solid-state Li-ion batteries (ASSLBs) is established considering the effects of contact areas and compressive pressure. The influences of contact area loss and compressive pressure on the electrical and mechanical properties of the ASSLB are numerically studied in the charging process. The results indicate that the loss of contact area may result in poor electrical performance. The contact area loss of cathode/SE interface can lead to the lithium concentration reaching the minimum value earlier, which brings about the decreases of both voltage and capacity, while that of anode/SE interface enables the ASSLB to attain the charging cut-off voltage in advance. Therefore, a lower capacity of ASSLB is found. The battery performance can be reduced for both higher (more than 1 MPa) and lower (0.05–0.4 MPa) compressive pressures, while the optimal charging performance can be obtained for medium (0.4–1 MPa) compressive pressures. Meanwhile, the stress-drop at the electrode/SE interfaces can reach the minimum. The charge and discharge experiments with 0.4 MPa compressive pressure are carried out. The maximum error between the experimental results and simulation results is 8.12%, which verified the accuracy of the simulated method.

Suggested Citation

  • Shao, Yu-qiang & Liu, Huan-ling & Shao, Xiao-dong & Sang, Lin & Chen, Zeng-tao, 2022. "An all coupled electrochemical-mechanical model for all-solid-state Li-ion batteries considering the effect of contact area loss and compressive pressure," Energy, Elsevier, vol. 239(PA).
    • Handle: RePEc:eee:energy:v:239:y:2022:i:pa:s0360544221021770
    DOI: 10.1016/j.energy.2021.121929
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    Cited by:

    1. Chen, Lin & Yu, Wentao & Cheng, Guoyang & Wang, Jierui, 2023. "State-of-charge estimation of lithium-ion batteries based on fractional-order modeling and adaptive square-root cubature Kalman filter," Energy, Elsevier, vol. 271(C).
    2. Hamed Sadegh Kouhestani & Xiaoping Yi & Guoqing Qi & Xunliang Liu & Ruimin Wang & Yang Gao & Xiao Yu & Lin Liu, 2022. "Prognosis and Health Management (PHM) of Solid-State Batteries: Perspectives, Challenges, and Opportunities," Energies, MDPI, vol. 15(18), pages 1-26, September.

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