Route planning for electric vehicles

Abstract

This work addresses the multi-objective route planning and charging problem for Battery Electric Vehicles (BEVs). The proposed solution is based on the NSGA-II algorithm to derive the Pareto-optimal set of eco-routes with the minimum travel and charging time, distance, energy consumption and charging costs while complying with the constraints related to the battery State of Charge (SoC) and the status of charging stations. Influencing factors, such as, vehicle and battery parameters, weather conditions, driver behaviour, road grade, Time Of Use (TOU) electricity cost, and Charging Stations (CS) status and type, are taken into account. The final results of the proposed method are compared with the well-established simulator SUMO.