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Integrated Decision Making in Electric Vehicle and Charging Station Location Network Design

[+] Author Affiliations
Namwoo Kang, Fred M. Feinberg, Panos Y. Papalambros

University of Michigan, Ann Arbor, MI

Paper No. DETC2014-35270, pp. V02AT03A035; 12 pages
  • ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 2A: 40th Design Automation Conference
  • Buffalo, New York, USA, August 17–20, 2014
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-4631-5
  • Copyright © 2014 by ASME


A major barrier in consumer adoption of electric vehicles (EVs) is ‘range anxiety,’ the concern that the vehicle will run out of power at an inopportune time. Range anxiety is caused by the current relatively low electric-only operational range and sparse public charging station infrastructure. Range anxiety may be significantly mitigated if EV manufacturers and charging station operators work in partnership using a cooperative business model to balance EV performance and charging station coverage. This model is in contrast to a sequential decision making model where manufacturers bring new EVs to the market first and charging station operators decide on charging station deployment given EV specifications and market demand. This paper proposes an integrated decision making framework to assess profitability of a cooperative business models based on a multi-disciplinary optimization model that combines marketing, engineering, and operations. This model is demonstrated in a case study involving battery electric vehicle design and direct-current fast charging station location network in the State of Michigan. The expected benefits can motive both government and private enterprise actions.

Copyright © 2014 by ASME



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