Optimization of Electric Vehicle Drives Using Ai-Based Control Systems

Abstract

Electric vehicle (EV) drives are rapidly evolving with the integration of artificial intelligence (AI)-based control systems. AI techniques, such as neural networks, fuzzy logic, and reinforcement learning, offer adaptive and predictive control mechanisms that improve motor efficiency, battery performance, and overall drive reliability. This paper explores AI-driven optimization strategies for motor control, regenerative braking, and energy management in EVs. The study also highlights the role of real-time data analytics in improving vehicle range and minimizing power losses. Various AI-based algorithms are analyzed, and experimental results demonstrate their effectiveness in optimizing drive performance while ensuring robustness against external disturbances.

Keywords: Electric Vehicle, AI-Based Control, Neural Networks, Motor Efficiency, Energy Management.