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The Strategic Planning of the Fast Charging Infrastructure to Alleviate Long Distance Electric Vehicle Range Anxiety

Dr. Fei Xie Photo-Fei_Xie
Research Associate
Center for Transportation Analysis, ORNL
September 9, 2016
2:20-3:25pm, JDT 410

 

Abstract:

This study focuses on the long-term strategic planning of the battery electric vehicle (BEV) inter-city fast charging infrastructure systems to alleviate long distance range anxiety problems. A multistage mixed integer model will be developed to answer: (1) where and when to build charging stations, and (2) how charging capacity shall be expanded with the growing BEV travel demand. In particular, to model charger capacity, a set of linear chance constraints are derived based on the M/M/c queuing model with the Erlang-C formula. A genetic algorithm based heuristic is developed to efficiently solve the large scale problem. The model is applied to a case study of California BEV transportation systems, and this study will help to address important policy questions such as: (1) what is the BEV infrastructure requirement to comply with the emerging California Zero Emission Vehicle (ZEV) plan, and (2) what is the tradeoff between high infrastructure capital cost and the high manufacture cost of larger batteries to extend BEV range.

Bio:

Dr. Fei Xie is a post-doctorate research associate at Center for Transportation Analysis of Oak Ridge National Laboratory. His research interests are transportation/energy systems modeling and policy analysis, advanced vehicle technologies, CAFE standards, and operations research. He received his PhD in Transportation Engineering from Clemson University in 2015 and MS in Transportation Engineering from Oregon State University in 2011.

 

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