Optimal Eco-Driving and User Preference Integration for Enhanced Energy Efficiency in AWD Electric Vehicles

Reducing carbon emissions from transportation is essential for achieving net-zero goals, and improving energy efficiency in electric vehicles (EVs) plays a significant role in this transition. This research presents an optimal control problem aimed at minimizing energy consumption in EVs through ecodriving techniques. The study focuses on developing an AllWheel Drive (AWD) EV model and implementing an optimization strategy to achieve energy efficiency while maintaining driving performance for trajectory tracking. The aim is to blend the objective of energy saving with driver preference using optimal control model. By ‘driver preference’ we refer to the natural driving behaviour that a driver would exhibit without considering energy efficiency. The proposed model was evaluated in various driving scenarios, including stop-and-go traffic, a $\mathbf{2 5 0}$-second-long section of the NYCC drive cycle, and a real-world driving cycle. Results indicate that the ego vehicle achieved a $22 \%$ reduction in energy consumption while following a lead vehicle on a realworld drive cycle using the developed optimal control approach, while maintaining acceptable speeds and following distances. The findings establish a foundation for the future development of realtime eco-driving systems for both human-driven and autonomous electric vehicles.