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Electrochemical impedance characteristics at various conditions for commercial solid–liquid electrolyte lithium-ion batteries: Part. 2. Modeling and prediction

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  • Feng, Fei
  • Yang, Rui
  • Meng, Jinhao
  • Xie, Yi
  • Zhang, Zhiguo
  • Chai, Yi
  • Mou, Lisha

Abstract

Solid–liquid electrolyte lithium-ion batteries (SLELBs) have good commercial viability in electric vehicle applications because they combine the safety of solid electrolyte lithium-ion batteries with the high ionic conductivity of liquid electrolyte lithium-ion batteries (LELBs). The safe and efficient operation of electric vehicles is inseparable from the key battery management algorithms such as battery state of charge (SOC), state of health and state of power estimation. In the process of designing battery management algorithms for SLELBs, it is essential to have an accurate understanding of battery behavior under different influencing factors and to build a high-fidelity battery simulation model. Electrochemical impedance spectroscopy (EIS) can be used to study the electrode process dynamics and ion transport mechanism in lithium-ion batteries. It is an urgent challenge to use EIS to experiment and analyze the characteristic impedances of SLELBs under the full-scale factors and to construct the battery model and simulate the battery impedance under the premise of a reasonable number of tests.

Suggested Citation

  • Feng, Fei & Yang, Rui & Meng, Jinhao & Xie, Yi & Zhang, Zhiguo & Chai, Yi & Mou, Lisha, 2022. "Electrochemical impedance characteristics at various conditions for commercial solid–liquid electrolyte lithium-ion batteries: Part. 2. Modeling and prediction," Energy, Elsevier, vol. 243(C).
    • Handle: RePEc:eee:energy:v:243:y:2022:i:c:s0360544221033405
    DOI: 10.1016/j.energy.2021.123091
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    2. Tian, Jiaqiang & Liu, Xinghua & Li, Siqi & Wei, Zhongbao & Zhang, Xu & Xiao, Gaoxi & Wang, Peng, 2023. "Lithium-ion battery health estimation with real-world data for electric vehicles," Energy, Elsevier, vol. 270(C).
    3. Liu, Xinghua & Li, Siqi & Tian, Jiaqiang & Wei, Zhongbao & Wang, Peng, 2023. "Health estimation of lithium-ion batteries with voltage reconstruction and fusion model," Energy, Elsevier, vol. 282(C).
    4. Lai, Xin & Zhou, Long & Zhu, Zhiwei & Zheng, Yuejiu & Sun, Tao & Shen, Kai, 2023. "Experimental investigation on the characteristics of coulombic efficiency of lithium-ion batteries considering different influencing factors," Energy, Elsevier, vol. 274(C).
    5. Kang, Jihyeon & Atwair, Mohamed & Nam, Inho & Lee, Chul-Jin, 2023. "Experimental and numerical investigation on effects of thickness of NCM622 cathode in Li-ion batteries for high energy and power density," Energy, Elsevier, vol. 263(PE).

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