Systems optimization of charging infrastructure for electric vehicles

Abstract

The large advances in new battery technology has made Electric Vehicles (EV) more attractive and feasible. As the cost and weight of batteries decreases, and the EV range increases, more individuals and companies will consider investing in these vehicles. However, one potential obstacle is the lack of ubiquitous charging locations. Many individuals would be uncomfortable purchasing a vehicle which limits longer trips and constrains their travel close to charging stations. To overcome this obstacle, a specific market segment, taxi drivers, which make many shorter trips typically near large cities, could be early adopters of EV technology and help justify and establish the charging infrastructure which could be used by others later on. With a large potential investment, this system and infrastructure needs to be analyzed and optimized for performance, cost, and other stakeholder objectives. This paper investigates the location and number of charging stations that would be required to meet the demands of a subset of the New York City taxi cab system. An operations model is developed applying the fare data available from the NYC Taxi and Limousine Commission to evaluate the impact on the schedule and performance of individual taxi drivers with EVs. Next, thousands of taxi driver shifts are simulated within the system defined by various numbers and locations of charging stations. Following the initial exploratory assessment, optimization of the system is implemented, from which the result could be used to inform city officials and stakeholders on key decisions during a system implementation phase.