Abstract
The state of charge (SOC) is one of the important performance indicators of battery, which provides an important basis for the management and control of Battery Management System (BMS). In view of the characteristics of lithium iron phosphate battery, considering the model accuracy and calculation amount, the equivalent circuit model of improved PNGV was selected. Based on that, an improved Extended Kalman Filter (EKF) algorithm was adopted to estimate the state of charge (SOC) of Li-ion battery, which covariance matrix was modified by the Levenberg-Marquardt method. At the end of this paper, the SOC estimation algorithm was verified by MATLAB simulations. The results show that compared with the standard EKF, the improved EKF has higher estimation accuracy and anti-interference ability, and has better convergence in the estimation process.
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Huang, Z., Fang, Y. & Xu, J. SOC Estimation of Li-ION Battery Based on Improved EKF Algorithm. Int.J Automot. Technol. 22, 335–340 (2021). https://doi.org/10.1007/s12239-021-0032-4
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DOI: https://doi.org/10.1007/s12239-021-0032-4