SOC Estimation using Coulomb Counting and Fuzzy Logic in Lithium Battery

Abstract

The popularity for Electric Vehicles (EV's) is in-creasing at high slope because EV's operates by an electric motor powered by battery rather than IC engine which uses conventional fuels. Enormous advantages of EV's have increase craze among users. The most important one is that, these types of vehicles are environment friendly. To manage the functions of EV's, Battery Management system (BMS) is required. BMS is an electronic system that controls the rechargeable battery to ensure that it operates safely and efficiently. It is used for estimation of various primary and secondary parameter. Primary criteria like State of Charge (SOC), State of Health, and primary parameters like current and voltage (SOH). The most prevalent approach for estimating SOC among the numerous techniques is Coulomb Counting (CC). Coulomb Counting fails to predict accurate value of SOC if we are uncertain about initial battery SOC. The data-driven approach is future. In order to improve the accuracy of SOC estimate, this study introduces the CC-FL (Coulomb Counting and Fuzzy Logic) combination. Error between the SOC predicted by CC and actual SOC is propagated to fuzzy logic controller along with rate of change error. Simulation and validation of proposed approach is performed in MATLAB/Simulink. Proposed method is able to reduces error and increase accuracy in SOC estimation as compared to coulomb counting alone. Accurate estimation of SOC will avoid battery undercharging or overcharging leading to enhance lifespan of the battery.