Enhanced MPPT Control with Hardware Implementation for PV-Powered EV Charging

This work introduces an advanced approach to optimizing energy harvesting from photovoltaic (PV) systems using an Artificial Neural Network (ANN)-based Enhanced Maximum Power Point Tracking (MPPT) control strategy. Efficient solar power utilization is the key to sustainable charging solutions as the need for electric vehicles (EVs) and renewable energy sources continues to grow. The proposed system corrects this by leveraging ANN's learning adaptability to determine the PV system's optimal operating points based on current factors such as load conditions, temperature, and solar irradiation. The enhanced energy harvesting of the system provides reliable and efficient EV charging. Based on experimental results, the MPPT based on ANN significantly enhances power harvesting compared to conventional methods, particularly in solar conditions that are variable. This paper illustrates how ANN-controlled MPPT methods can enhance solar energy utilization and enable more effective renewable energy implementations.