Efficient Route Selection for Airborne-based Dynamic Energy Charging of Electric Vehicles

Roadway-based wireless charging (RWC) transfers energy through radio signals. Recent advances in RWC and IoT technology have made airborne energy delivery to electric vehicles (EVs) a reality. The coordinated use of an airborne-based energy charger (AEC) allows vehicles to replenish supply during trips without the need to stop. However, efficient AEC scheduling will be necessary to better serve EVs and optimize the AEC operation. In this paper, we model such an optimization as a variant of the Hamiltonian cycle or path formation problem. Since the latter is an NP-hard problem, we propose heuristics for scheduling the charging service while factoring in the request parameters. The approach is based on prioritizing EV requests and forming a schedule based on a descending order of priorities. The proposed heuristics mainly differ in the way the priority is defined based on: (i) an earliest deadline first (EDF) strategy factors in the charging urgency, (ii) proximity to AEC, and (ii) a balanced flying trip (BFT), where the AEC flight time (distance) is to be minimized while factoring in the EV's charging emergency. We validate the performance of the three heuristics through extensive simulation experiments.