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Li-ion battery individual electrode state of charge and degradation monitoring using battery casing through auto curve matching for standard CCCV charging profile

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  • Rahman, Ashikur
  • Lin, Xianke

Abstract

The internal status, such as the state of charge and degradation of lithium-ion batteries, should be carefully monitored to ensure battery performance and safety. However, this task is challenging due to the weak observability. Estimating the state and degradation of each individual electrode (cathode and anode) is advantageous for battery management systems yet even more challenging. To address these challenges, this paper presents a novel method of using battery casing as a reference electrode to calculate the state of lithiation of both electrodes and the degradation status (including the storage capacity fade of each electrode and the total cyclable lithium in the battery). First, we introduced an innovative approach of using battery casing as the reference electrode and collected experimental data. The reference electrode provides valuable information on the anode and cathode potential, which can be used to extract internal information, including the state of charge of each electrode and its degradation status. Then, we calculated the transferred lithium ions between the electrodes by matching the anode and cathode voltage curves to the standard potential curves of graphite anode and lithium nickel manganese cobalt oxide (NMC) cathode, respectively. Next, we calculated the capacity of the electrodes using the state of lithiation of the electrodes and the total charge transferred. Last, we analyzed the battery degradation status by comparing the capacity fade of individual electrodes to the total charge transferred to the cell. The proposed method can easily calculate each electrode’s capacity, state of lithiation, and remaining cyclable lithium ions in the battery using the curve matching algorithm, which can be used to monitor battery degradation in real-time.

Suggested Citation

  • Rahman, Ashikur & Lin, Xianke, 2022. "Li-ion battery individual electrode state of charge and degradation monitoring using battery casing through auto curve matching for standard CCCV charging profile," Applied Energy, Elsevier, vol. 321(C).
    • Handle: RePEc:eee:appene:v:321:y:2022:i:c:s0306261922007115
    DOI: 10.1016/j.apenergy.2022.119367
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    References listed on IDEAS

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    1. Xinghao Zhang & Yan Huang & Zhaowei Zhang & Huipin Lin & Yu Zeng & Mingyu Gao, 2022. "A Hybrid Method for State-of-Charge Estimation for Lithium-Ion Batteries Using a Long Short-Term Memory Network Combined with Attention and a Kalman Filter," Energies, MDPI, vol. 15(18), pages 1-26, September.
    2. Zha, Yunfei & Meng, Xianfeng & Qin, Shuaishuai & Hou, Nairen & He, Shunquan & Huang, Caiyuan & Zuo, Hongyan & Zhao, Xiaohuan, 2023. "Performance evaluation with orthogonal experiment method of drop contact heat dissipation effects on electric vehicle lithium-ion battery," Energy, Elsevier, vol. 271(C).
    3. Ashikur Rahman & Xianke Lin & Chongming Wang, 2022. "Li-Ion Battery Anode State of Charge Estimation and Degradation Monitoring Using Battery Casing via Unknown Input Observer," Energies, MDPI, vol. 15(15), pages 1-19, August.

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