Optimized fuzzy-MPPT approach for superior solar power management in EV battery charging systems

An electric vehicle (EV) represents a mode of transportation which is propelled by the utilization of one or more electric motors. Both electric vehicles (EVs) and microgrids rely on the use of an energy storage system for their functioning. The device can operate autonomously using a battery, which may be recharged through the utilization of a solar photovoltaic (PV) panel. In this context, EVs powered by Renewable Energy Sources (RES) have many advantages over traditional vehicles based on Internal Combustion Engines (ICE). The nonlinear features exhibited by solar PV panels are produced by using environmental changes. Therefore, the development of the Maximum Power Point Tracking (MPPT) approach is proposed to find the stable maximum power from solar PV panels. This method is recommended to optimize the effectiveness of solar PV systems by maximizing the utilization of available solar radiation (SR). This article poses an investigation of the optimized fuzzy logic controller (FLC) approach for solar output power management in EV battery charging systems. The proposed work is established as a charging station in order to charge the battery banks, which improves the effectiveness of EV charging. The simulation of a novel system has been conducted in various working environments, and the resulting data has been thoroughly analyzed. PV frameworks produced output responses of voltage, current and power are 26.15 V, 7.702 A and 201.4 W respectively in steady-state conditions using novel FLC MPPT and produced output responses of voltage, current and power are 23.95 V, 7.663 A, and 183.5 W, respectively using conventional P&O MPPT. The proposed PV frameworks using novel FLC MPPT are greater than the conventional P&O MPPT by 9.8 %. Further research can be developed in favour of electronic power-based regulators using novel AI-based hybrid MPPT controllers, which effectively control the battery charging system for EVs.