On the selection of charging facility locations for EV-based ride-hailing services: A computational case study


The uptake of Electric Vehicles (EVs) is rapidly changing the landscape of urban mobility services. Transport Network Companies (TNCs) have been following this trend by increasing the number of EVs in their fleets. Despite the amount of new charging infrastructure being installed in recent years in most major cities, there are not sufficiently many Charging Stations (CSs) to meet the massive demand. For the purpose of economic operations, TNCs tend to couple such charging facilities location problem with EV fleets operations. More recently major TNCs have explored the prospect of establishing privately owned charging facilities. Given the scale and complexity of TNC operations, such decisions need to consider both the requirements of TNCs and local planning regulations. An optimisation approach is presented to model the placement of CSs with the objective of minimising the empty time travelled to the nearest CS for recharging as well as the installation cost. An agent based simulation has been set in the area of Chicago to derive the recharging spots of the TNC vehicles, and in turn derive the charging demand. The optimisation problem is solved approximately by a genetic algorithm.Our results indicate that nearly 180 CSs need to be installed to handle the demand of a TNC fleet of 3000 vehicles in Chicago.