System optimization of the On-Line Electric Vehicle operating in a closed environment

• Introduce a new type of electric vehicle called On-line Electric Vehicle (OLEV).
• The battery in the OLEV is charged wirelessly while the vehicle is in motion.
• The charge is done from the power transmitter installed under the road.
• Optimal allocation of the power transmitters is presented.
• The MIP model is solved using CPLEX and provides insights into system design.

We introduce a new type of electric-powered transportation system called the On-Line Electric Vehicle (  OLEVTMOLEVTM) developed by Korea Advanced Institute of Science and Technology (KAIST). The battery in the OLEV is charged remotely from power transmitters installed under the road using the innovative wireless charging technology. One of the successful commercial applications of the OLEV is the KAIST shuttle bus system operating on the KAIST campus. In this paper, we address the OLEV’s system design issues. The key design and economic parameters of the OLEV are the battery size and the allocation of the power transmitters that wirelessly supply the electric energy to the vehicle. We first construct a general mathematical model for optimally allocating the power transmitters and determining the size of the battery for a transportation system with wireless charging electric vehicles. Then we apply the model to a specific model that is currently operating. We are particularly interested in the OLEV system operating in a closed environment in which vehicles operate under regulated velocity and less traffic. The OLEV shuttle bus currently operating at KAIST is a good example of the system under a closed environment. We are particularly concerned about the closed environment system since it is the potential application area where the OLEV-based transportation is effectively commercialized. The optimization problem is constructed in the form of a Mixed Integer Programming (MIP) model. The sensitivity analysis is presented using the vehicle operational data collected from the OLEV shuttle buses. The sensitivity analysis provides meaningful insight into the OLEV-based transportation system design. We also explain how the general model can be extended to different transportation systems other than the closed environment.