Artificial Intelligence Based Hybrid EV Assistive System for Fuel and Electric Switching

For hybrid electric vehicles (HEVs), this study presents a novel energy management system that maximizes fuel economy and lowers pollution. Depending on the terrain and driving conditions, the system automatically switches between fuel and electric modes using sophisticated slope detection techniques. In addition, an RF-based speed control system modifies the speed of vehicles in specific regions, like schools, hospitals, and places where accidents are common. Technology guarantees more safety, lower pollutants, and better fuel efficiency by utilizing sensors and machine learning algorithms. The suggested solution promotes intelligent mobility for next-generation HEVs and sustainable transportation by smoothly fusing automated speed control with energy management.