Self-Sustaining AI-Optimized Electric Vehicle a Multi-Source Energy Regeneration and AI-Driven Power Management Approach

Electric Vehicles (EVs) are becoming more and more popular, which has increased demand for sustainable mobility solutions and effective energy utilization. This study introduces an innovative approach to multi source energy regeneration and Artificial Intelligence (AI) driven power management for EVs. It presents a sustainable energy system that integrates Renewable Energy Sources (RES), primarily solar power, to enhance energy harvesting and boost the self sufficiency of EVs. A key aspect of this framework is an AI powered battery management system, which intelligently controls the Battery Energy Storage System (BESS) to optimize energy consumption in real time. Additionally, the proposed solution incorporates an automatic battery swapping mechanism within a dual battery architecture. One battery actively powers the vehicle while the other undergoes charging, ensuring uninterrupted operation. AI algorithms analyse historical and real time data to predict battery lifespan, regulate charge cycles, and improve energy efficiency. Cloud based data storage facilitates predictive maintenance, reducing downtime and enhancing overall system reliability. Experimental simulations and prototype testing demonstrate that this AI driven power management system enhances energy efficiency by 96%, minimizes dependence on external charging infrastructure, and supports long term environmental sustainability. By integrating AI with advanced battery management, the system paves the way for more sustainable, autonomous, and intelligent EV operations, revolutionizing the future of electric mobility.