Analyzing the Impact of AI-Powered Energy Optimization in Electric Vehicles

This research work explores electric vehicle (EV) energy management by assessing how artificial intelligence (AI) optimizes energy use and enhances vehicle performance. It employs AI algorithms to dynamically control and distribute energy resources within the EV system. The AI system incorporates machine learning techniques to predict and adapt to driver behavior patterns for improved energy efficiency. Through simulations and real-world experiments, the research evaluates AI-based energy management’s impact on critical performance metrics such as range, efficiency, and charging behavior. Various driving conditions, environmental factors, and user preferences are analyzed to assess how well AI algorithms adapt and perform in different scenarios. The findings highlight AI’s potential to efficiently optimize energy usage in real-time, considering its ability to adapt to varying conditions and user behaviors. The research also discusses the balance between energy optimization and computational complexity, addressing the practical feasibility of AI-driven energy management solutions in EVs. As the automotive industry increasingly adopts AI, this research contributes valuable insights into intelligent energy management, promoting more sustainable and user-oriented EV operations. The findings provide a foundational understanding of performance dynamics, guiding the development and integration of AI-powered energy management systems for future EVs.