An IoT Based Cloud Integrated State of Charge Estimation of Battery Pack in Simulink Platform

Battery Management Systems (BMSs) of an Electric Vehicle (EV) plays an important role to optimize the range performance and safety of the vehicle. To develop the BMS, an accurate measurement of battery terminal voltage, load current, and also temperature parameters are required. In general, state of charge (SoC) of a battery is an estimated parameter from the measured values of battery voltage, load current, and temperature. So accurate estimation algorithm is required to estimate the battery performance parameters like SoC and state of health (SoH). Many estimation algorithms like extended Kalman filter(EKF), Machine learning based algorithms, and also some optimization algorithm are used. In all these algorithms, high computation and data storage are involved. In this work, a cloud based computation system is proposed to minimize the computation burden on the processor. Here, the real time data acquisition is carried out by the processor with suitable sensors and the processed data stored in the real-time cloud environment. In this work, a MATLAB/SIMULINK cloud computing platform is used to compute the EKF algorithm to estimate the SoC in real time. A Raspberry Pi 3B is used to send real time data to ThingSpeak cloud. The SoC parameter is also monitored in mobile APP.