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Integer variable-order equivalent circuit model and switching strategy for lithium-ion power batteries for vehicles based on information criterion under dynamic and static working conditions

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  • Zhu, Guangyao
  • Hu, Minghui
  • Qiu, Chengyang
  • Deng, Kejun

Abstract

Accurately description of the dynamic and static characteristics of lithium-ion batteries using a single model is difficult under complex and variable charging and discharging conditions. Based on the lithium-ion equivalent circuit model and distribution characteristics of the battery voltage platform, this study proposes an integer variable-order RC equivalent circuit model and uses the variable forgetting factor least squares method to complete the online identification of model parameters. The best system characterization model was selected according to the information criterion of different-order equivalent circuit models at each state of charge, and the switching strategy of different current directions was formulated. The particle swarm optimisation algorithm was used to explore the best parameters for the fitting degree and complexity evaluation index of the information criteria, to realise the optimal switching and accurate output of the integer variable order RC equivalent circuit model. The experimental results show that the output error of the end-voltage calculation of the integer variable-order RC equivalent circuit model based on information criterion switching can be maintained within 17.60 mV under dynamic and static conditions of various environmental temperatures, demonstrating good accuracy, robustness and potential for practical applications.

Suggested Citation

  • Zhu, Guangyao & Hu, Minghui & Qiu, Chengyang & Deng, Kejun, 2025. "Integer variable-order equivalent circuit model and switching strategy for lithium-ion power batteries for vehicles based on information criterion under dynamic and static working conditions," Energy, Elsevier, vol. 322(C).
    • Handle: RePEc:eee:energy:v:322:y:2025:i:c:s0360544225013362
    DOI: 10.1016/j.energy.2025.135694
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