Simulink Model for SoC Estimation using Extended Kalman filter

State of Charge (SoC) estimation of battery plays a key role in strategizing the power distribution across the vehicle in Battery Management System. In this paper a model for SoC estimation using Extended Kalman Filter (EKF) is developed in Simulink using Simscape library. This model uses second order Resistance-Capacitance (2RC) Equivalent Circuit Model (ECM) of Lithium Iron Phosphate (LFP) cell to simulate the cell behaviour. The parameter identification experiments were performed on a new and a used LFP cell respectively to identify two sets of parameters of ECM. The cell parameters are identified for the range of 0% to 100% SoC and it was found that the cell parameters vary as a function of SoC. Hence, variable resistance and capacitance blocks were used in the cell model so that the cell parameters can vary as a function of SoC. This facilitates the simulation of voltage drop due to internal resistances of the cell at the whole range of SoC, as it is impractical to measure the internal resistances of the cell online. In the EKF algorithm, Coulomb Counting model equation is used to predict the SoC. In the Measurement Updating step of the algorithm, the predicted SoC is used to calculate the Open Circuit Voltage (OCV) using a SoC-OCV Lookup table. Using the calculated OCV and the simulated voltage drop due to internal resistances of the cell, the Terminal Voltage of the cell model is calculated and compared with the measured Terminal Voltage and then the SoC is estimated. The results for SoC estimation using the two different sets of cell parameters were compared with experimental SoC.