Characterization and implementation of battery management system

The security, operation reliability along with the assurance of optimal charging of any battery energy storage system (BESS), are the main objectives and the key features of the battery management system (BMS). This paper proposed a modern technique in controlling the charging of the battery by estimating and monitoring the state of charge (SOC), starting by considering one of the most complex and sophisticated battery model, that imitates the battery in real life, which is the second-order RC battery model, that uses the Open Circuit Voltage (OCV) in order to estimate the SOC. In addition to that, the model was enhanced with the introduction of hysteresis effect that would imitates the previous charging history. The Kalman Filter is a robust method that is widely applied in modern BMS by researchers, which can provide real time estimation for both battery parameters and states. In this paper the Double Extended Kalman Filter (DEKF), which is the nonlinear form of the KF is used to determine battery's impedance parameters, as well as the battery's SOC. By combining the proposed model, with the power of DEKF to identify the circuit parameters and the estimation of SOC it was possible to develop more reliable and robust charging system. The efficiency of the proposed control strategy was confirmed through MATLAB simulation, along with the validation using Real Time Digital Simulator (RTDS) based system to achieve the best control of BESS within the required SOC.