Paper Info
Title
Plug-in Electric Vehicle Charging Congestion Analysis Using Taxi Travel Data in the Central Area of Beijing.
Abstract
Recharging a plug-in electric vehicle is more time-consuming than refueling an internal combustion engine vehicle. As a result, charging stations may face serious congestion problems during peak traffic hours in the near future with the rapid growth of plug-in electric vehicle population. Considering that driversu0027 time costs are usually expensive, charging congestion will be a dominant factor that affect a charging stationu0027s quality of service. Hence, it is indispensable to conduct adequate congestion analysis when designing charging stations in order to guarantee acceptable quality of service in the future. This paper proposes a data-driven approach for charging congestion analysis of plug-in electric vehicle charging stations. Based on a data-driven plug-in electric vehicle charging station planning model, we adopt the queuing theory to model and analyze the charging congestion phenomenon in these planning results. We simulate and analyze the proposed method for charging stations servicing shared-use electric taxis in the central area of Beijing leveraging real-world taxi travel data.
Year
Venue
Field
2017
arXiv: Systems and Control
Automotive engineering,Population,Internal combustion engine,Control theory,Charging station,Electric vehicle,Taxis,Quality of service,Queueing theory,Mathematics,Beijing
DocType
Volume
Citations 
Journal
abs/1712.07300
0
PageRank 
References 
Authors
0.34
4
6
Name
Order
Citations
PageRank
Huimiao Chen121.38
Hongcai Zhang2144.09
Zechun Hu38014.70
Yunyi Liang400.34
Haocheng Luo521.38
Yinhai Wang629239.37