Charging Electric Vehicle Sharing Fleet

36 Pages Posted: 15 Aug 2018

See all articles by Long He

Long He

National University of Singapore (NUS) - Department of Decision Sciences

Guangrui Ma

Tianjin University - College of Management and Economics

Wei Qi

McGill University - Desautels Faculty of Management

Xin Wang

University of Wisconsin-Madison

Date Written: July 31, 2018

Abstract

Many cities worldwide are embracing electric vehicle (EV) sharing as a flexible and sustainable means of urban transit. A recent setback, however, occurred in San Diego, California, where car2go ceased its EV sharing operations because it could not sufficiently charge its fleet. Motivated by the challenges that struck car2go, our goal is to propose models and managerial insights for designing a viable and profitable EV sharing business model. In addition to vehicle repositioning and charger siting problems that received great attention in literature, our modelling approach emphasizes customer's EV picking behavior and the operator-controlled charging operations, which are both central to EV sharing but was largely overlooked. In particular, motivated and calibrated using actual data of car2go, our model explicitly characterizes how customers endogenously pick EVs based on EV energy levels, and how the operator dispatch EV charging under a targeted charging policy. With close tracking of EV energy levels, our integrated EV sharing system design problem is formulated as a nonlinear optimization program with fractional constraints. To deal with its intractability, we then develop both lower- and upper-bound formulations in the form of mixed-integer second order cone programs, which are computationally tractable with small optimality gap (1.008% for the proposed design). Contrary to car2go's practice, we show that the viability of EV sharing can be enhanced by concentrating limited charger resources at selected locations and charging EVs in a proactive fashion (rather than not charging until the energy level drops to a certain level). We also find that ensuring sufficient charger availability is crucial when collaborating with a public charger network. Finally, increasing the rated charging power relieves the charger resource constraint, whereas extending per-charge range or adopting unmanned repositioning improves profitability.

Keywords: smart city operations, electric vehicles, car sharing, charging infrastructure

Suggested Citation

He, Long and Ma, Guangrui and Qi, Wei and Wang, Xin, Charging Electric Vehicle Sharing Fleet (July 31, 2018). Available at SSRN: https://ssrn.com/abstract=3223735 or http://dx.doi.org/10.2139/ssrn.3223735

Long He

National University of Singapore (NUS) - Department of Decision Sciences ( email )

15 Kent Ridge Drive
Mochtar Riady Building, BIZ1 #8-73
Singapore, 119245
Singapore

Guangrui Ma

Tianjin University - College of Management and Economics ( email )

NO.92 Weijin Road
Nankai District
Tianjin, 300072
China

Wei Qi (Contact Author)

McGill University - Desautels Faculty of Management ( email )

1001 Sherbrooke Street West
Montreal, Quebec H3A 1G5
Canada

Xin Wang

University of Wisconsin-Madison ( email )

Madison, WI Wisconsin 53706
United States
2178982195 (Phone)

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