Photovoltaic integrated optimized energy storage drives for electric vehicles

With the increasing demand for sustainable transportation solutions, electric vehicles (EVs) have gained significant attention in recent years. One of the key challenges in advancing EV technology is enhancing energy efficiency and range while minimizing environmental impact. This paper proposes a novel approach to address this challenge through the integration of photovoltaic (PV) systems and optimized energy storage drives in EVs, facilitated by a Dove-based Fractional Order-Proportional Integral (DBFO-PI) controller. The integration of PV systems into EVs allows for the harnessing of solar energy to supplement the vehicle's power requirements, reducing dependency on traditional grid-based charging. However, the intermittent nature of solar energy necessitates efficient energy storage solutions to ensure continuous and reliable power supply. To address this, optimized energy storage drives are employed, utilizing advanced control algorithms to manage energy flow and storage effectively. The DBFO-PI controller, based on the dove optimization algorithm and fractional-order calculus, is proposed as a robust control strategy for optimizing the performance of the integrated PV and energy storage system in EVs. By leveraging the advantages of fractional-order control and the optimization capabilities of the dove algorithm, the controller aims to achieve improved energy efficiency, battery longevity, and overall vehicle performance. The finest Total Harmonic Distortion (THD) prediction, accuracy, lowest error, and power loss were obtained, which is much better than other models. Such as the Genetic based Exchange Marketing Algorithm (GEMA), the Genetic Algorithm Model (GAM) and the Genetic Particle Swarm Model (GPSM).