4.7 Article

The Optimal System Design of the Online Electric Vehicle Utilizing Wireless Power Transmission Technology

Journal

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TITS.2013.2259159

Keywords

Electric vehicle; optimization; particle swarm optimization (PSO); transportation system design; wireless power transmission

Funding

  1. National Research Foundation of Korea
  2. Korean Ministry of Education, Science, and Technology [2011-0015075]
  3. National Research Foundation of Korea [2011-0015075] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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The Online Electric Vehicle (OLEV) is an innovative electric transportation system developed by the Korea Advanced Institute of Science and Technology (KAIST), Daejon, Korea, which remotely picks up electricity from power transmitters buried underground. Unlike a conventional electric vehicle that requires significant recharging downtime, the battery in the OLEV can be charged while the vehicle is in motion. Selected as one of the 50 Best Innovations of 2010 by TIME Magazine, the OLEV is considered as a potential solution for the next-generation electric public transportation system in South Korea. The prototype of the OLEV has been developed, and the commercialization process is now in progress. One of the main tasks to achieve the successful commercialization of the system is to determine economically how to allocate the power transmitters on the given routes and how to evaluate the right battery capacity for the vehicle. The allocation of the power transmitters and the size of the battery capacity directly affect the initial infrastructure cost. In this paper, we first introduce the system design issues of the mass transportation system operating with OLEV. We then present a mathematical model and an optimization method to allocate economically the power transmitters and to determine the battery capacity of the OLEV-based mass transportation system. The particle swarm optimization (PSO) algorithm is used as the solution method for the optimization problem. Numerical problems with sensitivity analysis are presented to show the validity of the mathematical model and solution procedure.

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