Multi-objective optimization of charging infrastructure to improve suitability of commercial drivers for electric vehicles using real travel data

Abstract

Electric mobility has gained much interest in the automotive industry and with commercial customers. A well-developed charging infrastructure is necessary to meet the rising customer demand for electricity. The aim of this paper is to evaluate how the suitability of commercial customers for the conversion to electric vehicles (EVs) is improved by the expansion of new charging stations. Here, the impact of an expanded charging infrastructure is measured by a multi-objective genetic algorithm. The location and type of charging stations is optimized with respect to the number of failed trips, due to empty batteries, and the total cost of infrastructure. Travel data from commercial vehicle fleets is approximated to EVs and discloses a pareto front to support decision makers in placing optimal public charging stations.