An Enhanced Equivalent Circuit Model With Real-Time Parameter Identification for Battery State-of-Charge Estimation

This article introduces an efficient modeling approach based on the Wiener structure to reinforce capacity of classical equivalent circuit models (ECMs) in capturing nonlinearities lithium-ion (Li-ion) batteries. The proposed block-oriented architecture is composed a simple linear ECM followed by static output nonlinearity block, which helps achieving superior nonlinear mapping property while maintaining real-time efficiency. observability established battery model analytically proven. also parameter estimator extended-kernel iterative recursive least squares algorithm for estimation parameters model. applied state-of-charge (SoC) 3.4-Ah 3.6-V nickel-manganese-cobalt-based Li-ion cells using extended Kalman filter (EKF). results show about 1.5% improvement SoC accuracy compared with EKF second-order ECM. A series tests are carried out demonstrate computational efficiency method.