Sustainable EV Charging Infrastructure with Res Integration and Intelligent ANN Controller for SOC Monitoring

The explosive growth of Electric Vehicles (EVs) necessitated the development of sustainable and efficient EV charging infrastructure. Hence, this paper proposes an EV charging infrastructure by integrating Renewable Energy Sources (RES) and an intelligent Artificial Neural Network (ANN) controller for State of Charge (SOC) monitoring. By integrating RES such as solar, system reduces dependency on grid, lowers charging costs, and contributes to clean energy adoption. The Quasi Z-Source Converter (qZSC) is DC-DC converter used in EV charging infrastructure to enhance the performance, and efficiency of charging systems. Further, it helps in maintaining the quality of power delivered to the EV and also minimizes any negative effects on the grid. Boost converters are capable of handling wide variations in input voltage and providing a stable output voltage. The Maximum Power Point Tracking (MPPT) used to extract the highest power and it tracks maximum power point from PV. The intelligent ANN controller is employed to accurately monitor and manage SOC, using real-time data to control charging rates, prevent overcharging, and maximize charging efficiency based on dynamic conditions like grid demand and battery status. Overall, it optimizes energy usage, enhances battery life, and ensures efficient power delivery while maintaining environmental sustainability.