Track: Mathematical Modeling and Heuristics

Abstract

Considering the long charging times, limited range of electric vehicles (EVs), and the limited number of charging stations, it is vital to check the feasibility of a route and make a charging plan, especially for long journeys. Charge planning of an EV includes the decisions of where, when, and how much the EV needs to be charged. Charging planning is one of the areas where decision support should be provided to EV drivers. Thanks to intelligent transportation system (ITS) technologies, it is now possible to receive information from charging stations, which plays an essential role in providing decision support to EV drivers. This study proposes an optimization model to find an optimal charge planning model for suitable routes that enable the EV to complete its journey without range anxiety. The proposed model determines where and how much charge is needed at the charging stations considering time-of-use (TOU) pricing. An integer linear programming model is developed based on the range coverage location model (RCLM), which determines the minimum number of charging stations the EV needs to visit. The proposed optimization model is tested on randomly generated problems. The test results show that the model can find the optimal charging plan in a reasonable time.