An optimized adaptive estimation of state of charge for Lithium-ion battery based on sliding mode observer for electric vehicle application

Abstract

As lithium-ion batteries have nonlinearities and also uncertainties in parameter identification in their dynamical model, accurate estimation of SoC requires robust and nonlinear estimators. Using a sliding mode observer, this paper presents an optimal adaptive estimator to measure the state of charge (SoC) of lithium-ion batteries (LIB). The conventional sliding mode observers have chattering phenomena and prolong convergence time in their performance, but the sliding mode observer proposed in this paper includes an adaptive gain which causes less chattering and convergence time. The simulation results and software in the loop (SIL) validation confirm the effectiveness of the proposed estimation method of SoC.