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SOC Estimation of Lithium Battery Based on Resistance-capacitance Parameters Filtering Optimization UKF
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Jin HU1, Jingying ZHAO1, Shuailiang YAO2, Wenyu ZHANG2
Journal of Power Supply | 2025, 23(2) : 247 - 255
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Journal of Power Supply | 2025, 23(2): 247-255
• Battery and Energy Storage •
SOC Estimation of Lithium Battery Based on Resistance-capacitance Parameters Filtering Optimization UKF
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Jin HU1, Jingying ZHAO1, Shuailiang YAO2, Wenyu ZHANG2
Affiliations
  • 1 State Key Laboratory of Reliability and Intelligence of Electrical Equipment, College of Electrical Engineering, Hebei University of Technology, Tianjin 300130, China
  • 2 State Grid Jibei Zhangjiakou Wind-PV-Storage-Transportation New Energy Co., Ltd., Zhangjiakou 075000, China
Published: 2025-03-30 doi: 10.13234/j.issn.2095-2805.2025.2.247
Outline
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A fast and accurate estimation of the state-of-charge (SOC) of lithium batteries is critical for the battery management system. Aimed at the problem that the Kalman filter algorithm lacks reasonable constraints on the resistance-capacitance (RC) parameters when estimating the SOC of lithium batteries, an optimization method of RC parameters filtering is proposed, and it is combined with unscented Kalman filter (UKF) to achieve the fast and accurate convergence of lithium battery SOC estimation. First, an equivalent circuit model of lithium battery is established by combing the polynomial equation. Then, forgetting factor recursive least squares is used to obtain the time-varying and time-invariant model RC parameters. The expression of RC parameters filtering relationship is established by setting the Kalman gain threshold, and an RC optimization UKF algorithm is proposed for lithium battery SOC estimation. Finally, hybrid pulse-power characteristic experiment, intermittent constant-current discharge experiment and dynamic stress test experiment were designed to verify the convergence and robustness of the proposed algorithm. The maximum estimation error of SOC was less than 1.0%, and the reference range of gain threshold was also given.

Lithium battery  /  state-of-charge (SOC)  /  resistance- capacitance (RC) parameters  /  unscented Kalman filter (UKF)
Jin HU, Jingying ZHAO, Shuailiang YAO, Wenyu ZHANG. SOC Estimation of Lithium Battery Based on Resistance-capacitance Parameters Filtering Optimization UKF[J]. Journal of Power Supply, 2025 , 23 (2) : 247 -255 . DOI: 10.13234/j.issn.2095-2805.2025.2.247
Funding
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  • National Natural Science Foundation of China(5137704)
  • Natural Science Foundation of Hebei Province(E2019202481)
  • Natural Science Foundation of Hebei Province(E2017202284)
Appendix
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Year 2025 volume 23 Issue 2
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Article Info
doi: 10.13234/j.issn.2095-2805.2025.2.247
  • Receive Date：2022-06-22
  • Online Date：2025-07-01
  • Published：2025-03-30
Article Data
Affiliations
History
  • Received：2022-06-22
  • Revised：2022-08-27
  • Accepted：2022-09-13
Funding
National Natural Science Foundation of China(5137704)
Natural Science Foundation of Hebei Province(E2019202481)
Natural Science Foundation of Hebei Province(E2017202284)
Affiliations
    1 State Key Laboratory of Reliability and Intelligence of Electrical Equipment, College of Electrical Engineering, Hebei University of Technology, Tianjin 300130, China
    2 State Grid Jibei Zhangjiakou Wind-PV-Storage-Transportation New Energy Co., Ltd., Zhangjiakou 075000, China
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