Optimizing Electric Vehicle Charging with Moth Flame Control Algorithm of Boost-KY Converter

Abstract

Electric vehicles have assumed a prominent role in future transport system due to the diminishing availability and escalating costs of fossil fuels, coupled with growing concerns about the impact of global warming. The purpose of the work consists in addressing the pressing need for efficient and sustainable solutions in the realm of electric vehicles and renewable energy integration. The tasks solved in the article to achieve the given goal are the following: an improved Boost-KY converter has been introduced to counter the inherent limitation of low PV panel voltage output. This converter effectively mitigates voltage and current ripples, thereby ensuring a stable power supply for EV charging. Additionally, the Moth Flame Optimized Proportional Integral (MFO-PI) controller has been implemented to regulate converter operation, demonstrating exceptional proficiency in mitigating PV output unpredictability. MATLAB simulation is done to validate the proposed system's performance. The most important results are the achievement of impressive maximum efficiency of 96.21% and remarkably low Total Harmonic Distortion (THD) value of 1.04%. The system maintains consistent voltage and current levels for PV panels and EV battery, ensuring dependable energy supply. The significance of the results obtained consists in their potential to revolutionize the intersection of renewable energy integration, electric vehicle (EV) adoption, and sustainable transportation practices.The PV-based EV charging system not only reduces dependence on finite fossil fuel resources but also contributes to environmental preservation, aligning with global efforts to combat climate change. Furthermore, system adheres to stringent requirements of IEEE 519 standards, positioning it as a catalyst for the adoption of clean energy solutions within the future transport system. Keywords: PV system, electric vehicle, improved Boost-KY converter, Moth Flame optimized PI controller.