Optimal Local and In-Route Charging Management of Electric Mobility-on-Demand Systems

On-Demand electric vehicle (EV) systems are expected to have a significantly increasing role in the future of transportation systems in urban areas, to cope with the tremendous increases in urban population and decrease global carbon emissions. An inconvenience in Mobility-on-Demand Electric Vehicle (MoD-EV) systems is the need for some customers to charge EVs before reaching their destinations, which may cause delays in the trip time. Local and in-route charging options are available but the system operator needs to manage the charging assignments of the different EVs as charging all EVs locally may result in large delays. Given a connected system, we propose a routing strategy that aims to decrease these charging delays for the customers by sending the customers to different charging stations either at the pick-up location or nearby charging stations to minimize their average total trip time while respecting the charging constraints and avoid roads congestion. The problem is then formulated by modeling the routing between multiple MoD-EV stations as a multi-server queuing system with an objective of minimizing the expected overall trip duration for all customers, relative to their actual trip time without charging as a convex optimization problem. Optimal routing decisions and actual trip times are then derived analytically and simulation results show the significant gains of our proposed model as compared to shortest path and random routing schemes.