Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/83236
Title: Locating multiple types of charging facilities for battery electric vehicles
Authors: Liu, Haoxiang
Wang, David Zhi Wei
Keywords: Wireless charging
Battery electric vehicle
Issue Date: 2017
Source: Liu, H., & Wang, D. Z. W. (2017). Locating multiple types of charging facilities for battery electric vehicles. Transportation Research Part B: Methodological, in press.
Series/Report no.: Transportation Research Part B: Methodological
Abstract: To reduce greenhouse gas emissions in transportation sector, battery electric vehicle (BEV) is a better choice towards the ultimate goal of zero-emission. However, the shortened range, extended recharging time and insufficient charging facilities hinder the wide adoption of BEV. Recently, a wireless power transfer technology, which can provide dynamic recharging when vehicles are moving on roadway, has the potential to solve these problems. The dynamic recharging facilities, if widely applied on road network, can allow travelers to drive in unlimited range without stopping to recharge. This paper aims to study the complex charging facilities location problem, assuming the wireless charging is technologically mature and a new type of wireless recharging BEV is available to be selected by consumers in the future other than the traditional BEV requiring fixed and static charging stations. The objective is to assist the government planners on optimally locating multiple types of BEV recharging facilities to satisfy the need of different BEV types within a given budget to minimize the public social cost. Road users’ ownership choice among multiple types BEV and BEV drivers’ routing choice behavior are both explicitly considered. A tri-level programming is then developed to model the presented problem. The formulated model is first treated as a black-box optimization, and then solved by an efficient surface response approximation model based solution algorithm.
URI: https://hdl.handle.net/10356/83236
http://hdl.handle.net/10220/42501
ISSN: 0191-2615
DOI: 10.1016/j.trb.2017.01.005
Schools: School of Civil and Environmental Engineering 
Rights: © 2017 Elsevier Ltd. This is the author created version of a work that has been peer reviewed and accepted for publication by Transportation Research Part B: Methodological, Elsevier. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/10.1016/j.trb.2017.01.005].
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:CEE Journal Articles

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