Study on Second-order RC Model Charge State Estimation Method for Lithium Battery Based on EKF Algorithm

Changchang Li

doi:10.54097/xt521f94

Authors

Changchang Li

DOI:

https://doi.org/10.54097/xt521f94

Keywords:

Lithium battery, state of charge, battery equivalent circuit model, extended Kalman filter algorithm.

Abstract

In order to improve the estimation accuracy of the state of charge (SOC) of lithium-ion batteries, this paper proposes a SOC estimation method based on the second-order RC equivalent circuit model and the extended Kalman filter (EKF) algorithm. Firstly, the second-order RC equivalent circuit model is selected as the research object in this paper, and the parameters of the second-order RC model are identified by combining the hybrid pulse charging and discharging test and the 1stopt software, and then the extended Kalman filtering algorithm is applied under the MATLAB environment to estimate the SOC based on the second-order RC equivalent circuit model. The simulation results show that the adopted estimation method can accurately track the SOC trend of the battery compared with the actual state-of-charge (SOC) reference value. Through experimental analysis, the estimation results of the EKF algorithm combined with the second-order RC equivalent circuit model have a small error with the actual value, and the estimation accuracy is high and ideal.

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