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Degradation and Dependence Analysis of a Lithium-Ion Battery Pack in the Unbalanced State

Author

Listed:
  • Xiaohong Wang

    (School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China)

  • Shixiang Li

    (School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China)

  • Lizhi Wang

    (Institute of Unmanned System, Beihang University, Beijing 100191, China
    Key Laboratory of Advanced Technology of Intelligent Unmanned Flight System of Ministry of Industry and Information Technology, Beijing 100191, China)

  • Yaning Sun

    (School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China)

  • Zhongxing Wang

    (Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China)

Abstract

Lithium-ion batteries are widely used in the energy field due to their high efficiency and clean characteristics. They provide more possibilities for electric vehicles, drones, and other applications, and they can provide the higher requirements necessary for the reliability of battery pack systems. However, it is easy for a battery pack to be unbalanced because of the dependence between the cells. The unbalanced state will make the degradation process more complex and cause abnormal discharge parameters, which brings challenges in the analysis of the state of health (SOH) of battery packs. In order to study the degradation process in the unbalanced condition, in this study, a degradation test of four different configurations of battery packs was designed and implemented, and the degradation process was primarily studied from the perspective of dependence. First, the degradation characteristics and dependency degree of different configurations of the unbalanced state were discussed. Second, a hypothesis test and a linear regression analysis were used to analyze the degradation process and the acceleration effect of a battery pack in the unbalanced state. Finally, partial least squares regression was used to establish the dependence model of battery packs in the unbalanced state. A high regression coefficient (R 2 > 0.9) and low p -value < 0.0001 indicated that the correlation of the degradation process was effectively quantified. The results provide a reference for optimizing a consistent design of battery packs and managing the SOH of battery packs.

Suggested Citation

  • Xiaohong Wang & Shixiang Li & Lizhi Wang & Yaning Sun & Zhongxing Wang, 2020. "Degradation and Dependence Analysis of a Lithium-Ion Battery Pack in the Unbalanced State," Energies, MDPI, vol. 13(22), pages 1-25, November.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:22:p:5934-:d:444669
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    References listed on IDEAS

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