State of Charge estimation in Lithium-Ion Battery using model based method in conjunction with Extended and Unscented Kalman Filter

Abstract

Lithium-ion battery became popular because of its high power density, high energy density and long life. Battery is a complex system, it has very strict restrictions on temperature, current and voltage. In order to monitor and control these parameters, there will be a controller called battery management system. State of charge(SoC) shows the level of charge remained in the battery. As battery is a chemical system, direct measurement of SoC is not possible, and hence accurate estimation of SoC is necessary. In this paper, estimation of SoC and terminal voltage of Lithium-Ion battery using model based method in conjunction with Extended Kalman filter(EKF) and Unscented Kalman filter(UKF) is presented. The two RC electrical equivalent circuit is considered for state space modelling of Li-ion battery. The estimated SoC and terminal voltage are compared with those obtained through Coulomb counting and true model. MATLAB simulations are done for both charging and discharging characteristics of the battery for different C-Rates. Comparison of SoC with EKF and UKF for different chargeRates is presented. Simulation results are presented to validate the proposed methodology. © 2020 IEEE.