Due to government incentives, environmental concerns, and lower operating costs, there has been a significant increase in the adoption of Electric Vehicles (EVs). Consequently, supporting the rapid growth of the EV market trend requires the availability of fast charging stations. However, traditional grid-based charging stations are unsustainable as they increase their carbon footprint and strain the grid, potentially causing power outages. This paper proposes a solar-powered EV DC fast charging station that utilizes a buck converter with Particle Swarm Optimization (PSO) trained Neural Network (NN) for maximum power point tracking (MPPT) and Model Predictive Control (MPC) as the controller. The proposed system aims to provide fast and reliable EV charging while minimizing the impact on the grid during daylight hours. Results obtained via MATLAB simulation demonstrate the effectiveness, stability, reliability, and robustness of the proposed system. Therefore, this study presents a promising direction toward developing sustainable and efficient DC EV charging infrastructure using clean and green energy.
DOI: https://doi.org/10.1109/apsit58554.2023.10201780
Publish Year: 2023
