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Lead-acid battery is an important part of power system substation, which has an important impact on the safety and stability of the power system. To address the health status of lead-acid batteries for substations, this paper builds an experimental platform for EIS testing, selects 27 lead-acid batteries, extracts the equivalent circuit model parameters of valve-regulated lead-acid batteries through curve fitting, and realizes an accurate assessment of lead-acid battery SOH based on the Support Vector Regression (SVR) model of the Simulated Annealing (SA) algorithm. The final experiment shows that the maximum absolute error of the estimation error of SOH for the battery does not exceed 1.05%, and the absolute value of the average deviation does not exceed 0.20%, which proves the validity of the EIS health state assessment method for lead-acid batteries.

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Research on SOH Based on Electrochemical Impedance Spectroscopy and SA-SVR Algorithm

  • 会议论文

  • 发表日期：

    2025年

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  • Di Hu,
  • Cheng Xie,
  • Tao Li,
  • Zhong Chen,
  • Wei Yang,
  • Ziying Wang

摘要

Lead-acid battery is an important part of power system substation, which has an important impact on the safety and stability of the power system. To address the health status of lead-acid batteries for substations, this paper builds an experimental platform for EIS testing, selects 27 lead-acid batteries, extracts the equivalent circuit model parameters of valve-regulated lead-acid batteries through curve fitting, and realizes an accurate assessment of lead-acid battery SOH based on the Support Vector Regression (SVR) model of the Simulated Annealing (SA) algorithm. The final experiment shows that the maximum absolute error of the estimation error of SOH for the battery does not exceed 1.05%, and the absolute value of the average deviation does not exceed 0.20%, which proves the validity of the EIS health state assessment method for lead-acid batteries.