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<p>State-of-charge (SOC) estimation of power battery is one of the important technologies of electric vehicles. In the SOC estimation process, estimation error can be adjusted by closed-loop compensation when the measured actual data deviates from the planned data. In this paper, the key parameters of the improved Nernst model of the lithium battery are identified by design of experiment and the least squares method. Based on this, a unified closed-loop filter algorithm model is established to compensate the error of the SOC estimation value, which can reduce the estimation error due to the noise and measurement accuracy and realize the high precision real-time estimation of lithium battery SOC. Finally, the accuracy of the battery model is verified by experiment, and the advantages of the proposed method in estimating the accuracy and robustness are verified.</p>

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Closed-Loop Compensation Soc Estimation Method Based on Nernst Equation

  • 期刊论文

  • 发表日期：

    2026年2月26日

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  • Yao He,
  • Junmin Zhao,
  • Xinxin Zheng,
  • Xintian Liu

摘要

State-of-charge (SOC) estimation of power battery is one of the important technologies of electric vehicles. In the SOC estimation process, estimation error can be adjusted by closed-loop compensation when the measured actual data deviates from the planned data. In this paper, the key parameters of the improved Nernst model of the lithium battery are identified by design of experiment and the least squares method. Based on this, a unified closed-loop filter algorithm model is established to compensate the error of the SOC estimation value, which can reduce the estimation error due to the noise and measurement accuracy and realize the high precision real-time estimation of lithium battery SOC. Finally, the accuracy of the battery model is verified by experiment, and the advantages of the proposed method in estimating the accuracy and robustness are verified.