Design and Modeling of a PV-Fed High-Gain DC–DC Converter for EV Charging

Abstract

This study describes a highly effective process innovation in power conversion architecture for Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G) electric vehicle (EV) application, by integrating a photovoltaic (PV) system, a single-ended primary inductor converter (SEPIC), intelligent control techniques, and bidirectional energy transfer capability. The PV system is coupled through a SEPIC converter with adaptive neuro fuzzy inference system based Grey wolf optimisation (ANFIS-GWO) maximum power point technique (MPPT) which effectively controls and maximizes the output voltage from PV under fluctuating irradiance situations, enabling constant direct current (DC) power for other converters. In order to satisfy the high-efficiency and high- voltage demands of EV charging applications, a new high-gain DC-DC converter with high voltage gain and reduced voltage stress across switching devices is proposed.  A cascaded ANFIS controller (CANFIS) is employed to control the proposed converter, which includes the outer voltage regulating system producing the reference current and the inner current regulating system producing the optimal duty ratio for interleaved phases, leading to better transient operation, enhanced reliability, and accurate balance current under fluctuating load conditions. The proposed design is further incorporating a bidirectional DC-DC converter and a grid connected voltage source inverter (VSI) to support G2V charging and V2G power transfer among the EV battery and grid. This improves stability of grid, permits demand-side control, and promotes integration of green energy. The efficacy of the proposed systems is confirmed through MATLAB/Simulink, revealing superior voltage gain, efficiency, and improved dynamic response provides a flexible and robust choice for the development of power-grid-integrated EV applications.