Volume II-2
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-2, 41-46, 2014
https://doi.org/10.5194/isprsannals-II-2-41-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-2, 41-46, 2014
https://doi.org/10.5194/isprsannals-II-2-41-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

  11 Nov 2014

11 Nov 2014

Considering the dynamic refueling behavior in locating electric vehicle charging stations

K. Liu1 and X.H. Sun2 K. Liu and X.H. Sun
  • 1School of Transportation and Logistics, Dalian University of Technology, Dalian, China
  • 2Dept. of Civil Engineering, Nagoya University, Furo-cho, Chikusa-ku, Ngoya 464–8603, Japan

Keywords: Electric Vehicle, Recharging Stations, Location Model, Time-spatial Constraints, Waiting Time, Detour Behavior

Abstract. Electric vehicles (EVs) will certainly play an important role in addressing the energy and environmental challenges at current situation. However, location problem of EV charging stations was realized as one of the key issues of EVs launching strategy. While for the case of locating EV charging stations, more influence factors and constraints need to be considered since the EVs have some special attributes. The minimum requested charging time for EVs is usually more than 30minutes, therefore the possible delay time due to waiting or looking for an available station is one of the most important influence factors. In addition, the intention to purchase and use of EVs that also affects the location of EV charging stations is distributed unevenly among regions and should be considered when modelling. Unfortunately, these kinds of time-spatial constraints were always ignored in previous models. Based on the related research of refuelling behaviours and refuelling demands, this paper developed a new concept with dual objectives of minimum waiting time and maximum service accessibility for locating EV charging stations,named as Time-Spatial Location Model (TSLM). The proposed model and the traditional flow-capturing location model are applied on an example network respectively and the results are compared. Results demonstrate that time constraint has great effects on the location of EV charging stations. The proposed model has some obvious advantages and will help energy providers to make a viable plan for the network of EV charging stations.