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Summary of Health-State Estimation of Lithium-Ion Batteries Based on Electrochemical Impedance Spectroscopy

Author

Listed:
  • Xinwei Sun

    (School of Electrical Engineering, Weihai Innovation Research Institute, Qingdao University, Qingdao 266000, China)

  • Yang Zhang

    (Machine Electric Soft Network Administration Capital (MESNAC) Cooperation, Qingdao 266042, China
    Strategy Research Institute, State Power Investment Cooperation, Beijing 100029, China)

  • Yongcheng Zhang

    (College of Physics, Weihai Innovation Research Institute, Qingdao University, Qingdao 266000, China)

  • Licheng Wang

    (School of Information Engineering, Zhejiang University of Technology, Hangzhou 310014, China)

  • Kai Wang

    (School of Electrical Engineering, Weihai Innovation Research Institute, Qingdao University, Qingdao 266000, China)

Abstract

With the increasing application of lithium-ion batteries, accurate estimation of the state of health (SOH) of lithium-ion batteries is of great significance for the safe operation of lithium-ion battery systems and the reduction of operation and maintenance costs. The complex physical and chemical reactions inside the lithium battery and the complex external working conditions make it challenging to achieve an accurate health-state estimation and life prediction. Therefore, the accurate estimation of the SOH of lithium-ion batteries is an important issue. At present, electrochemical impedance spectroscopy (EIS) is widely used in the study of battery-power impedance characteristics and battery-state estimation due to its advantage of nondestructive measurement. For this reason, this paper summarizes the research progress of lithium-ion SOH estimation based on EIS in recent years and details it layer by layer, mainly from two aspects: first, the quantitative relationship model between the characteristic parameters and SOH is established by constructing a frequency domain-equivalent circuit model. Secondly, we construct a quantitative relationship model between EIS data and SOH using the data-driven method. Finally, the advantages and disadvantages of different methods and estimation accuracy are analyzed and compared, and the future estimation of SOH based on EIS is prospected.

Suggested Citation

  • Xinwei Sun & Yang Zhang & Yongcheng Zhang & Licheng Wang & Kai Wang, 2023. "Summary of Health-State Estimation of Lithium-Ion Batteries Based on Electrochemical Impedance Spectroscopy," Energies, MDPI, vol. 16(15), pages 1-19, July.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:15:p:5682-:d:1205358
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    References listed on IDEAS

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