The Nature and Strategy of Minimizing the Total Travel Time for Long-Distance Driving of an EV

The famous Cannonball Run, a cross-country driving challenge from New York City to Los Angeles, highlights the unique challenges of long-distance electric vehicle (EV) route planning. The time record for an internal combustion vehicle is 25 h and 39 min. Comparing this to the EV record of 42 h and 17 min achieved with Tesla Model S, which elucidates the complexities inherent to optimal EV route planning. To bridge this divide, our study introduces a system designed for real-time vehicle-to-cloud (V2C) interaction aimed at enhancing online long-distance EV route planning. Our approach integrates four pivotal components: 1) a real-time route data processing module; 2) an energy consumption module that works for different road conditions; 3) an EV charge time prediction module grounded on real EV charging data; and 4) a comprehensive optimization module using mixed-integer linear programming (MILP). In applying this system to the Cannonball Challenge, our simulation results surpass the real-world EV time record. Importantly, our integrated system’s potential extends beyond this challenge, offering robust solutions for personal and commercial EV long-distance drives.