Research on on-line identification of equivalent circuit model parameters and soc estimation for lithium-ion batteries

Abstract

The online identification model parameters can reflect the real terminal voltage state of the battery in real time and provide accurate observation data for battery SOC estimation. BMS is an important part of new energy vehicles, which supervises and controls the working process of the battery. The core of BMS is SOC estimation, and the accuracy of its estimation is related to whether the battery works efficiently and safely. Based on Thevenin model, FFRLS-EKF and KF-EKF were used to estimate the SOC of ternary lithium battery under DST condition. The estimation results show that FFRLS-EKF has a maximum error of 0.0079, which can estimate the SOC of the battery well.