This paper proposes a Monarch Butterfly Optimization (MBO)-based energy management strategy and a fuzzy logic-based nonlinear controller for electric vehicles (EVs). The MBO algorithm optimizes energy sharing between the battery, electric motor, and regenerative braking system, while the fuzzy logic controller compensates for nonlinearities and uncertainties in EV operations. The objectives are to minimize energy wastage, reduce emissions, and enhance efficiency. The MBO algorithm tunes the fuzzy logic controller to meet energy demands under varying driving conditions. Simulation results show that the proposed approach outperforms traditional methods in efficiency and reliability. The paper also explores the combination of MBO and fuzzy logic for hybrid energy storage systems in photovoltaic-powered EVs, focusing on optimizing battery and supercapacitor performance. The main goal is to improve energy management system performance for cost-effective operation and enhanced EV stability and reliability.