Elaborated EECM parameter identification reflecting adaptive weight for achieving a high‐accuracy SOC estimator

In this paper, a combined method is proposed to improve the accuracy of an electrical equivalent circuit model (EECM) and state-of-charge (SOC) estimation in situations where lithium-ion battery frequently charged discharged. To calculate terminal voltage dynamic region, charging discharging are repeated at 0.1 s intervals, specific region determined historical weight selected, based on amount charge that reflect parameters. The weights applied parameters estimated performance EECM estimating battery. Also, improved extended Kalman filter SOC estimation. A 21,700 cylindrical lithium nickel manganese cobalt oxide-type was used for verification, required modeling were extracted through experiments conducted determine characteristics. This paper compared two models not considering history or characteristics with verify results. result shows errors lowest three cases.