Sustainable EV Charging: Renewable Energy Integration with DC-DC Fast Charging Systems

With the growing adoption of Electric Vehicles (EVs), the need for efficient and reliable charging infrastructure has become more urgent, particularly as the number of EVs on the power grid increases. This paper addresses the challenges posed by the expansion of EV charging networks and grid congestion, proposing a fast and reliable Level 3 DC-DC charger integrated into solar-powered EV charging systems. The system can charge LTO and NMC-based batteries up to $60-80 \text{kWh}$ within 45-60 minutes, leveraging advanced power electronics and optimization algorithms to enhance charging efficiency. By incorporating solar energy, the system not only promotes renewable energy usage but also helps alleviate the pressure on the grid during peak demand periods. Furthermore, to ensure stable and efficient power management, this study introduces a hybrid optimization framework that combines Fuzzy Logic with the Sparrow Search Algorithm (SSA) to optimize power distribution in DC microgrids. The proposed microgrid, which integrates renewable energy sources (RES) and battery storage systems (BSS), is designed to maintain a stable power balance despite fluctuations in energy generation and dynamic load conditions. The Fuzzy-SSA-based energy management system is evaluated through MATLAB Simulink simulations and compared to the Particle Swarm Optimization (PSO) method. The results show that the hybrid approach outperforms PSO in terms of convergence speed, stability, and cost-efficiency, with a $\mathbf{7. 7 7 6 \%}$ reduction in annual electricity costs. This approach offers a promising solution to enhancing the sustainability, reliability, and efficiency of microgrids, supporting a renewable energy-driven future while minimizing the impact of EV charging on the grid.