Improving electric vehicle utilization in carsharing: A framework and simulation of an e-carsharing vehicle utilization management system

Rapid economic growth and urbanization have motivated economists and researchers to seek innovative solutions for the many challenges that accompany these trends. This can be observed in upcoming research in sustainable transportation services where potential solutions to urban mobility issues are being explored. For example, e-carsharing, which involves the joint ownership or use of battery electric vehicles (BEVs) does not only mitigate the environmental and infra structural hazards of privately owned internal combustion engine vehicles (ICEVs) through reduction of emissions and urban traffic, but also alleviates many barriers such as high costs, battery life limitations, and suboptimal charging infrastructures that have prevented privately owned BEVs from reaching their full potential. In response, we present a framework for a battery electric vehicle utilization management system (BEVUMS) for automated optimization of operational decisions regarding the usage of electric vehicles in mixed vehicle-type fleets. The framework consists of four modules: energy demand prediction, battery charge scheduling, vehicle selection, and vehicle relocation. We assess the validity and capabilities of the system by simulating an e-carsharing system with data sets of 2,000 and 20,000 vehicle rental data points. Our findings suggest opportunities for prevention of charging related problems, increased BEV rental ratios, and lengthened BEV rental periods. Thus, the proposed system leads to improved BEV utilization and prolonged BEV battery life. In addition to these opportunities for increased potential sustainability provided by our proposed BEVUMS, this study further contributes to current research in the field by providing a framework and a benchmark setting for future research.