Evaluation of PV array MPPT algorithms’ efficiency for SEPIC based EV charging stations

Hazardous pollutants emitted by combustion engines include particulate matter and greenhouse gases, which are the main agents of smog and climate change. EVs (Electric Vehicle) are more economical, environmentally friendly, and efficient than combustion engines. EVs’ surge in electricity demand may strain infrastructure and increase costs. Integrating solar PV (photovoltaic) systems promotes sustainable EV growth and maintains stable pricing. By supplying renewable energy for EV charging, EVs become less dependent on the grid, reduce carbon emissions, and green transportation. Maximum Power Point Tracking (MPPT) is used in solar PV systems to maximize energy output by continuously operating the panels at their optimal power point under Standard Test Condition (STC). This study proposes several methods for determining the maximum power output from photovoltaic arrays, including Perturb and Observe (P&O), Particle Swarm Optimization (PSO), Fuzzy Logic Controller (FLC), and Genetic Algorithm (GA). A novel SEPIC converter in solar PV systems keeps the voltage from solar panels stable by adjusting the voltage step up or step down based on the requirements. The converter stores energy efficiently, even when sunlight changes. A comparative study of four popular MPPT methods has been conducted with MATLAB/Simulink.