Abstract
ABSTRACT Modernizing the Electric Vehicle (EV) charging infrastructure is essential for the widespread adoption of electric mobility. This research addresses the imperative need for enhancing the power performance of photovoltaic (PV) grid-connected inverters for EV fast charging applications. The system integrates Voltage-Oriented Control (VOC) for the PV inverter, a High-Gain Interleaved (Single Ended Primary Inductance Converter) SEPIC-Cuk (HGISC) converter, and a Bald Eagle Search Optimized Adaptive Neuro Fuzzy Inference System (BESO-ANFIS)) algorithm. VOC with Proportional Resonant (PR) ensures optimized energy transfer to grid, while the HGIBC converter enhances power performance. The proposed BESO-ANFIS Maximum Power Point Tracking (MPPT) dynamically tracks the PV array’s Maximum Power Point (MPP) under varying conditions. Additionally, a bidirectional battery converter in the energy storage system optimizes power usage. The synergistic implementation of these advanced controller results in a comprehensive solution, showcasing improved power output, grid integration, and efficient solar energy utilization for EV fast charging. MATLAB simulations and experiments demonstrate 97% efficiency and reduced Total Harmonic Distortion (THD) of 0.98%, positioning this research as an advanced solution for EV charging infrastructure enhancement.
Published Version
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