Connectivity supported dynamic routing of electric vehicles in an inductively coupled power transfer environment

Abstract

Electric vehicle (EV) charging problem impedes its wide scale commercial adoption. In this study, the authors address this problem through an ant colony optimisation based multiobjective routing algorithm that is dedicated to accommodate EV trips. By using connectivity, EVs communicate with other vehicles and infrastructure components to transmit information in real time for finding the best route, and for intelligently recharging on the move using an inductively coupled power transfer system. Such connected EVs are capable of adapting each trip with the lowest travel time and/or the lowest recharge cost along with an optimal recharge plan to prevent a battery drain. As a case study, a real world roadway network in Charleston, South Carolina was simulated to examine the performance of the routing strategy. Simulation analysis revealed that connected EVs can reduce not only the total travel time and the energy consumption, but also the recharged volume of electricity and corresponding cost, thus significantly relieving the concerns of range anxiety of EV drivers. This routing approach potentially leads to a reduction in the EV battery capacity requirement, which in turn can reduce the cost of energy storage systems to a reasonable level.