Performance analysis of AI-based energy management in electric vehicles

This research delves into the realm of electric vehicle (EV) energy management, specifically exploring the efficacy of artificial intelligence (AI) in optimizing energy consumption and enhancing overall vehicle performance. The study employs a multifaceted approach, integrating AI algorithms to dynamically control and allocate energy resources within the EV system. Through extensive simulations and real-world experimentation, the research evaluates the effect of AI-driven energy management (AIEM) on performance metrics, including effectiveness, and charging patterns. Different driving conditions, environmental factors are examined to comprehensively analyze the adaptability of AI algorithms. The findings illuminate the revolutionary of AI in dynamically maximizing energy efficiency. The study provides nuanced insights into the balancing energy efficiency with computational challenges, addressing the real-world effectiveness of AIEM in EVs. As the automotive industry rapidly embraces AI technologies, this research contributes to the smart energy management, paving the way for more efficient, eco-friendly, and user-focused EVoperations. Additionally, the incorporation of a predictive maintenance module into the AI system enhances energy efficiency by forecasting potential component failures and maintenance needs, further improving overall vehicle performance. The outcomes presented herein offer an essential insight into performance dynamics, directing the creation and implementation of AIEM systems for electric vehicles.