Intelligent Charge Controllers for EVs Using Whale Optimization Algorithm for Demand Management

This paper proposes the development of a smart charge controller for electric vehicles that may take advantage of the Whale Optimization Algorithm (WOA) to improve on energy efficiency and demand management. The technology optimized charging parameters through dynamic adjustment of the charging process in relation to the energy demand from the grid, SOC, and power pricing. This ability of WOA to balance between exploration and exploitation allows the controller to minimize thermal losses in systems and prevent battery degradation. Moreover, energy wastage is avoided so that the controller can ensure efficient energy utilization. The experiment results show that compared to the current charge controllers, a WOA-based controller would improve grid load management by 10%, reduce battery degradation by 15%, and increase efficiency in the utilization of energy by 20%. This system has the scalability as well as the real-time adaptability to changing requirements of batteries and grid conditions that would make it suitable for areas with high penetration of electric vehicles. This system outperforms the others by optimizing the load distribution necessary for optimal charging.