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Online impedance-based temperature and states co-estimation for sodium-ion batteries using fractional-order model

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  • Jiang, Cong
  • Wang, Yujie
  • Sun, Zhendong
  • Li, Mince
  • Chen, Zonghai

Abstract

Temperature and state estimation are of significant importance for ensuring the safe and efficient operation of batteries. This study proposes an online impedance-based temperature and states co-estimation method with temperature-adaptive fractional-order model for commercial sodium-ion batteries. Based on battery electrochemical impedance spectroscopy testing, we conducted analyses of impedance parameters versus frequency under varying temperatures, aging states, and state of charge (SOC) levels, along with investigation of charge/discharge rate effects. Subsequently, a temperature-impedance-SOC relationship model was established using multilayer perceptron fitting. Then, a fractional-order equivalent circuit model was developed based on impedance spectrum data, employing fractional-order extended Kalman filter for battery SOC estimation. A safe operating area border method considering voltage, current, and SOC limitations was adopted for state of power (SOP) estimation. Finally, the effectiveness of the proposed method was validated under variable-temperature dynamic stress test.

Suggested Citation

  • Jiang, Cong & Wang, Yujie & Sun, Zhendong & Li, Mince & Chen, Zonghai, 2025. "Online impedance-based temperature and states co-estimation for sodium-ion batteries using fractional-order model," Energy, Elsevier, vol. 334(C).
    • Handle: RePEc:eee:energy:v:334:y:2025:i:c:s0360544225030695
    DOI: 10.1016/j.energy.2025.137427
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