Optimal Battery Management System Utilized in Electric Vehicle Using Fuzzy Logic Controller (FLC) and Artificial Eco-System Algorithm (AEO)

Abstract

In real life applications, using electronics switch in high voltage and high current applications is very challenging due to limitation of hardware and safety. In this manuscript, a hybrid system is proposed for battery management system (BMS) used in electric vehicle (EV) is a critical part for effective utilization of the energy storage. The proposed hybrid technique is joint performance of fuzzy logic controller (FLC) and Artificial eco-system algorithm (AEO), hence it is called FLTAEO technique. The existing battery management control system is not effective for the Induction motor drive based solar PV powered electric vehicle system. In this manuscript, the control strategies of charging with discharging of Li-ion batteries coupled Induction motor with solar PV power are used with proposed technique. Here, the introduced FLC and AEO are discussed with detailed control abilities for charging/discharging. The simulations are done in MATLAB platform to analyze the superiority of the proposed method. Here, BESS life comparison, fitness function for charging, fitness function for discharging, error Distribution, RMSE calculation for 1 hour and 5 minutes ahead prediction interval (PI) are analyzed and compared with various existing techniques, like Emperor Penguin Algorithm (EPA) and Seagull Optimization Algorithm (SOA).