IPOD Abstract for presentation (Poster or Podium)
Infrastructure Systems
Mohammadhosein Pourgholamali, n/a
Graduate research assistant
Purdue University
West Lafayette, Indiana, United States
Mohammad Miralinaghi, n/a
Assistant Professor
Illinois Institute of Technology, United States
Samuel Labi, n/a
Professor
Purdue University
west lafayette, Indiana, United States
Mohammadhosein Pourgholamali, n/a
Graduate research assistant
Purdue University
West Lafayette, Indiana, United States
This paper proposes a framework which can be considered as a part of a larger strategy to curb vehicular emissions in urbanized regions by promoting electric vehicles (EVs) as an alternative to internal combustion engine vehicles (ICEVs) over a long-term planning horizon. This study incorporates the vehicle-purchasing behavior in combination with charging/refueling station locations and route decision-making behavior of travelers. In this framework, the transport agency decision-maker seeks to gradually (through the private sector) provide new electric charging stations at selected locations and/or repurposing existing gas stations. It is anticipated that an efficiently-designed EV charging network will significantly reduce urban emissions. A bi-level mathematical model is developed to capture the decision-making process of both the transport agency decision-maker and the travelers, thereby providing a solid theoretical foundation for the EV charging network design. At the upper level, the transport decision-maker seeks to minimize vehicular emissions by determining the optimal locations of the electric charging stations and their optimal capacities subject to a budget constraint. At the lower level, travelers choose the vehicle type (ICEV vs. EV) and routes, and a diffusion model is used to characterize such choices. In the diffusion model, the choice depends on the EV market penetration rate and the net benefit (of using EVs compared to ICEVs) earned by travelers relative to the previous period. The bi-level model is solved using an active-set algorithm. The results of the numerical experiments suggest that urban EV patronage, and hence, vehicular emissions, are very sensitive to the availability and capacity of EV charging stations. The results of the paper can be used by transport agencies to achieve optimal design (location and capacities) of EV charging stations and to support transport vehicle policies that contribute to the long-term reduction of urban emissions.