Optimization of charging infrastructure planning for plug-in electric vehicles based on a dynamic programming model
Abdul Haseeb Khan Babar and
Ali Yousaf
Transportation Planning and Technology, 2022, vol. 45, issue 1, 59-75
Abstract:
Electric vehicles (EV) are a new mode of transportations that are replacing conventional vehicles. However, EVs face the problem of insufficient charging infrastructure which limits their drive range. Furthermore, the limited resources of countries are also a major problem faced by EVs in infrastructure planning and development. To overcome this problem, this paper proposes a model, comprising several techniques that allocate the limited resources optimally. Moreover, the model also identifies the location and number of stations required for maximizing the drive range of EVs. The methods used in the model are Activity Relationship Chart (ARC) for the recording of data, Dynamic Programming (DP) for optimal allocation of resources, and the center of gravity (COG) method to check the feasibility of the results obtained by DP. The model is applied to a case study of a motorway system in Pakistan to identify and optimally allocate charging stations along the route that connects the four major cities of Pakistan. The optimized allocation of limited resources using the proposed model simultaneously takes into account the flow, distance, resource limit, and range limit of EVs while building charging infrastructure plans.
Date: 2022
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/03081060.2021.2017207 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:transp:v:45:y:2022:i:1:p:59-75
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/GTPT20
DOI: 10.1080/03081060.2021.2017207
Access Statistics for this article
Transportation Planning and Technology is currently edited by Dr. David Gillingwater
More articles in Transportation Planning and Technology from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().