• Research Area 1 :

    Systems Optimization of Wireless Charging Electric Vehicles

    Online electric vehicles (OLEV) constitute an innovative electric-powered transportation system that picks up electricity remotely from power transmitters buried underground. In this research, we developed an optimal design algorithm and operational policy for OLEV-based urban transportation. We considered an OLEV-based public bus system as a vehicle-road integrated system operating on multiple fixed routes in an urban environment. The battery in this OLEV system is charged remotely from transmitters installed along the road. The allocation of transmitters on routes was therefore a critical design parameter in system design. In addition, such operational policies as stopping time at stations, vehicle velocities on each segment of routes, and idle downtime for charging are crucial determinants of the system’s overall performance. The algorithm we developed evaluates the optimal design parameters and policies analytically while satisfying passenger demand and the geographic requirements of the urban environment. It is used as a primary engine for the operational support software of the OLEV-based transportation system.

     

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    Figure 1: System design and optimization of OLEV-based transportation system

    The OLEV hardware has been successfully developed, and the system is now being considered as a potential solution for the next generation of electric-powered public bus systems by several metropolitan governments in South Korea, including that of Gumi City. The next step in commercializing the OLEV-based system for public transportation use is to achieve economical system design, in particular to determine how to economically allocate the power transmitters on roads and how to evaluate the right battery capacity. Figure 1 shows the decision variables in the optimization problem: maximum battery capacity Imax and the allocation of the power transmitters described by the start and end positions of each transmitter we denoted by x0i and xfi, respectively. The problem involves searching for the optimal decision variables that give the minimum total cost.

    Previous results

    We have developed the optimal design algorithm for allocating the transmitters and determining the right battery size in given routes on a public transportation system operating on a single route in a closed environment in which vehicles operate under regulated velocity and a low traffic flow. The OLEV shuttle bus currently operating at KAIST is a good example of such a closed environment system. we have been proposed sereval optimization methods in previous research, including the mixed integer programming model, meta-heuristics model with the particle swarm optimization technique, and rule-based heuristic model [1].

    We have shown that these algorithms can reliably find the optimal economic solution for the allocation of the power transmitters and size of the battery, and have also discovered the characteristics of the system that are important in designing the OLEV-based transportation system. The major distinction of this research is that we have applied the inventory control optimization concept to the energy flow of a vehicle. Inventory control and optimization have been popular research topics in industrial engineering in the past decade, and we have successfully applied them to a vehicle energy dynamics model to develop the analytical energy flow model of the OLEV system.

    Accomplishments

    The following are among the accomplishments of current research on this approach.

    • Best paper award from the International Conference on Intelligent Manufacturing and Logistics 2013 for “Optimal Economic Design of Wireless Powered Transportation System.”
    • Publication in a prestigious international journal: Young Dae Ko and Young Jae Jang, “The Optimal System Design of the Online Electric Vehicle Utilizing Wireless Power Transmission Technology, IEEE Transactions on Intelligent Transportation Systems, Vol. 14, No. 3, September 2013, pp. 1255-1265 (SCI IF: 3.064, SCOPUS ranking: 3 out of 154 transportation/construction journals). More journal papers are currently being processed.
    • Research grants: Three research grant awards.
      • National Research Foundation of Korea funded by the Korean Ministry of Education through the Basic Science Research Program: KRW100,000,000 grant awarded in 2011 (2011-2013).
      • National Research Foundation of Korea funded by the Korean Ministry of Education through the Basic Science Research Program: KRW100,000,000 grant awarded in 2013 (2013-2014).
      • Korea Transportation Research Institute – Advanced Research on Electric Vehicles: KRW50,000,000 grant awarded in 2012.
    • Patents: Three patents have been granted, and three more are under review.

     

    Current and Future Research

    We are currently extending this research to an open environment system (the macro model). Compared to a closed environment system, an open system exhibits more complex behavior that must be incorporated into the analysis, for example, traffic volume and passenger demand from one station to another; geographic information such as the location of traffic lights, intersections, and up- and downhill angles on routes; vehicle velocity requirements/regulations in an urban environment; power grid locations; and initial investment costs such as installation and battery costs.

    This research addresses the following questions.

    • Where is the optimal installation location for power transmitters in various traffic conditions?
    • What is the best power distribution strategy for the vehicle given real-time traffic information?
    • What is the optimal velocity/acceleration profile for maximizing the performance of the transportation system?

    In the next project phase, we will develop an algorithm and policies under the assumption that the OLEV-based transportation system is being installed in a newly constructed urban area. We will develop methods for optimal transportation route design and operational policies specialized for the OLEV system. We will consider three main system-related issues in algorithm development: traffic light rules; optimal route design; and operational policies such as stopping time at stations, base station locations, and recommended velocity profiles on routes.

    In developing the optimal energy strategy, we will use analytical modeling with dynamic programming, a widely used approach in investigating an optimal strategy or policy with limited current information. We will also undertake the integrated simulation modeling of the OLEV system. A detailed energy flow model with continuous simulation will be developed at the vehicle level and then integrated with discrete event simulation to capture the behavior of urban traffic. This integrated simulation will capture both the dynamic behavior of the energy flow in an individual vehicle and macro-level traffic system behavior.

    Once the proposed algorithm and methodologies have been successfully developed, they can be used as decision-support tools in the design of new bus routes. For example, as shown in Figure 1, Gumi City has plans to adopt a new OLEV-based public transportation system. The algorithm developed in this project will evaluate the optimal routes and economic operational policies for the OLEV system analytically while meeting traffic demands.

     

    [1] Young, Dae Ko & Jang, Young Jae, “The Optimal System Design of the Online Electric Vehicle Utilizing Wireless Power Transmission Technology,”­ IEEE Transactions on Intelligent Transportation Systems, Vol. 14, No. 3, September 2013, pp. 1255-1265.

     

     

    Last update : 2014/03/14