This study presents a full design and validation method for an independent PV-battery-based Electric Vehicle (EV) charging station in Benban, Aswan. Using HOMER Pro, the system's techno-economic sizing is done. MATLAB/Simulink simulations are used to check its dynamic operation and MPPT performance. A realistic EV profile is considered (600 kWh per day, with a peak demand of 48.9 kW). Simulink uses population-based algorithms like Gazella Optimization Algorithm (GOA), Grey Wolf Optimization (GWO), and Particle Swarm Optimization (PSO) to improve dual PI controllers. The study looks at how well the system works for both the economy and the environment. The best setup has an Levelized Cost of Energy (LCOE) of $0.111/kWh, a Net Present Cost (NPC) of $430,468, and saves about 212 tons of CO₂ per year, with an unmet load of less than 2%. The results of the simulation show that the DC bus voltage is stable, the MPPT tracking is efficient, and the battery can be charged and discharged reliably even when the sun is not shining. In general, the results show that the proposed off-grid EV charging system is both technically sound and economically competitive for areas with high solar potential.