Government policies strive to encourage a shift from internal combustion engine vehicles to electric-powered vehicles, yet EV market penetration has been lackluster. The current limited number of charging stations leads to driving range anxiety, depressing sales. Of the three main types of static charging stations, the fast-charging technology used in Level 3 makes it ideal to meet demand and map the way forward.

Deciding where to place charging stations is the key to balancing the level of investment with the potential usage. New research explores the best placement of EV charging stations during the transition period between today and full EV adoption. In “Robust Design of Electric Charging Infrastructure Locations under Travel Demand Uncertainty and Driving Range Heterogeneity” in the Journal of Infrastructure Systems, authors Mohammadhosein Pourgholamali, Gonçalo Homem de Almeida Correia, Mahmood Tarighati Tabesh, Sania Esmaeilzadeh Seilabi, Mohammad Miralinaghi, and Samuel Labi propose a model for mapping Level-3 electric charging stations that will satisfy the charging demand of travelers for intercity trips in the short term. This research can provide guidance to road agencies in long-term planning and budgeting. Learn more about this research at The abstract is below.


The rising demand for electric vehicles (EVs), motivated by their environmental benefits, is generating an increased need for EV charging infrastructure. Also, it has been recognized that the adequacy of such infrastructure helps promote EV use. Therefore, to facilitate EV adoption, governments seek guidance on continued investments in EV charging infrastructure development. Such investment decisions, which include EV charging station locations and capacities, and the timing of such investments require robust estimates of future travel demand and EV battery range constraints. This paper develops and implements a framework to establish an optimal schedule and locations for new charging stations and decommissioning gasoline refueling stations over a long-term planning horizon, considering the uncertainty in future travel demand forecasts and the driving range heterogeneity of EVs. A robust mathematical model is proposed to solve the problem by minimizing not only the worst-case total system travel cost but also the total penalty for unused capacities of charging stations. This study uses an adaptation of the cutting-plane method to solve the proposed model. Based on two key decision criteria (travelers’ cost and charging supply sufficiency), the results indicate that the robust scheme outperforms its deterministic counterpart.

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