State-of-charge Estimation of Lithium-ion Batteries Using Extended Kalman Filter

The lithium-ion technology has rapidly imposed it self in the world of electronics consumer and electric vehicles. It offers high energy density, very good durability and is not subject to the memory effect. Determining some parameters such as the batteries state of charge (SoC), and obtaining an accurate battery model is mandatory in this field. In this paper, an improved algorithm is proposed to estimate the SoC of a cylindrical lithium cell type 18650 with the help of Matlab/Simulink using experimental data. To simulate the battery behaviour, a mathematical model of a second-order Thevenin circuit is developed. For the internal parameters identification, the (Lookup Table) method is used under Simulink. The aim of this work is to approximate to the most accurate values of the internal parameters of this nonlinear system in order to increase the accuracy of the SoC estimation process based on the advantages of the EKF algorithm.