Design and Simulation of a Small-scale Solar-Powered Charging System for Electric Vehicles with MPPT Optimization under Varying Conditions

The global shift towards Electric Vehicles (EVs) necessitates the development of efficient and sustainable charging infrastructures. This dissertation explores the design and simulation of a small-scale solar-powered charging system for EVs, leveraging the capabilities of MATLAB. The proposed system aims to charge a 12V, 4.5Ah lithium-ion battery using a 20W solar panel, with a Maximum Power Point Tracking (MPPT) charge controller to optimize power extraction under varying irradiance conditions. The system design involves modeling the solar panel's I-V characteristics using the Shockley diode equation, implementing an MPPT controller based on the Perturb & Observe (P&O) algorithm, employing a buck converter for voltage regulation, and utilizing a Battery Management System (BMS) for safe and efficient battery charging. Mathematical models for each component facilitate accurate simulation, and the system is implemented in MATLAB with subsystems for the solar panel, MPPT controller, DC-DC converter, and battery. Simulations conducted under various conditions, including ideal (1000 W/m² irradiance and 25°C temperature) and partially cloudy weather (400 W/m² irradiance), as well as different initial state-of-charge (SOC) levels (20%, 50%, 80%), demonstrate the system's performance in terms of SOC progression, charging current, and power output. Results show that under ideal conditions, the battery reaches 100% SOC in approximately 2.84 hours, whereas under partially cloudy conditions, it only reaches around 70% SOC in 5 hours. These findings highlight the feasibility and efficiency of solar-powered EV charging systems, with the MPPT controller effectively optimizing power output to adapt to varying environmental conditions.