An Optimization Model and a Decision Support System to Optimize Car Sharing Stations with Electric Vehicles

Abstract

An increasing environmental awareness, rising energy cost, progressing urbanization, and shortage of space cause to rethink individual mobility behavior and personal car ownership in cities. Car sharing is a sustainable mobility concept that allows individuals to satisfy their mobility needs without owning a car and addresses modern mobility. Car sharing is particularly suitable to cover medium-range distances and can be linked to the public transport of major cities (intermodal mobility). Within this context, the integration of electric vehicles represents an opportunity to further protect the environment and potentially save energy cost. In order to create an efficient car sharing transportation network, the location of stations, the number of vehicles and the availability of electric fast charging infrastructure are critical success factors. We provide a decision support system (DSS) to plan and optimize car sharing stations for electric vehicles. An optimization model and the DSS OptCarShare 1.1 enable to optimize stations and visualize results. Parameters, such as the annual lease payment for charging infrastructure, the expected travel time of consumers, the charging time of electric vehicles dependent on available charging infrastructure, affect the decision variables such as the number of car sharing stations, vehicles and fast chargers. On the basis of evaluations and benchmarks for the cities of Hannover and Zürich, we establish generalizations for the parameters of the model. The results show a high impact of fast chargers (half an hour to fill 80 % of the battery) on the current model and the optimal solution.