Smart Integrated Trip Planner for Optimized Driving and Charging of Connected Electric Vehicles

초록

This paper presents an integrated trip planner for electric vehicles (EVs) that jointly optimizes driving and charging strategies using real-time V2X data and energy consumption prediction. The method formulates a mixed-integer nonlinear program (MINLP) to minimize charging events while satisfying terminal state-of-charge (SoC) constraints. A detailed battery charging model and a real-world battery thermal management (BTM) system are incorporated to capture nonlinear charging dynamics and cooling energy consumption. Case studies using a receding horizon framework and real-world driving scenarios demonstrate improved energy efficiency, accurate battery temperature prediction, and enhanced trip planning performance. © 2025 IEEE.