A novel photovoltaic (PV)-based electric vehicle (EV) charging system has demonstrated significant advancements in power conversion efficiency and grid integration, according to recent experimental validations. The system, developed to address the escalating environmental concerns and the rapid global expansion of EVs, integrates a Single Ended Primary Inductance Converter (SEPIC) Integrated Isolated Flyback Converter (SIIFC) with a Machine Learning Radial Basis Function Neural Network (ML RBFNN) Maximum Power Point Tracking (MPPT) algorithm.

The core innovation lies in its ability to maximize solar power extraction and deliver high-quality power to both EV motors and the grid. Experimental results confirm that the proposed SIIFC achieves an impressive efficiency of 95.4%, while the RBFNN MPPT boasts a 96% efficiency in tracking the maximum power point of PV arrays. This high efficiency is crucial for optimizing energy yield from solar panels, which traditionally suffer from low conversion rates and inconsistent power generation due to varying environmental conditions.

Further enhancing the system's performance is a reduced-switch 31-level inverter, which powers the EV motor, and a 1-phase Voltage Source Inverter (VSI) for grid synchronization. This inverter design significantly increases reliability and reduces Total Harmonic Distortion (THD) to a remarkably low 2.16%. The low THD is vital for maintaining grid stability and ensuring the longevity of connected electrical equipment, a common challenge with conventional power conversion systems. An adaptive Proportional-Integral (PI) controller ensures effective synchronization with grid voltage and precise control over EV motor speed.

Existing PV-based EV charging systems often struggle with limitations such as low voltage gain, oscillations around the Maximum Power Point (MPP) under dynamic conditions, and high component counts in their inverter topologies. This new integrated approach overcomes these issues by providing enhanced voltage boosting capabilities, faster and more precise MPP tracking, and a simplified yet highly efficient inverter architecture. The SIIFC addresses the need for high step-up voltage without the efficiency losses associated with traditional boost converters, while the RBFNN MPPT offers superior adaptability compared to conventional or fuzzy logic controllers.

The system's ability to seamlessly transition between powering the EV motor directly from PV during daylight hours and drawing power from the grid at night, coupled with its robust grid synchronization capabilities, positions it as a critical enabler for the widespread adoption of PV-powered EV charging stations. This development marks a significant step towards a more sustainable and resilient energy infrastructure for electric mobility.