The optimal economic design of the wireless powered intelligent transportation system using genetic algorithm considering nonlinear cost function

• Present a new type of electric vehicle called On-Line Electric Vehicle (OLEV).
• Battery in OLEV charged wirelessly from charging infrastructure under the road.
• Propose a mathematical model to optimally allocate the charging infrastructure.
• Propose a mathematical model to evaluate the economic battery size of OLEV.
• We propose Genetic Algorithms (GA) as the solution methodology.

We present a new type of electric vehicle called the On-Line Electric Vehicle (OLEV™), developed by the Korea Advanced Institute of Science and Technology (KAIST). The OLEV uses an innovative wireless charging technology that enables the battery in the vehicle to be charged through a charging infrastructure installed under the road. The vehicle can be charged while stationary or moving. The OLEV is considered a revolutionary transport solution, as it overcomes the problems facing conventional battery-powered electric vehicles, such as long charging times and the need to stop frequently to charge. Several commercial versions of the OLEV have been successfully deployed, including the trolleys serving in Seoul Grand Park and the KAIST campus shuttles. In this paper, we propose a mathematical model to optimally allocate the charging infrastructure on the route, and to determine the vehicles battery size. The model is specifically concerned with the OLEV system applied to mass transport buses such as those used in Seoul Grand Park and on the KAIST campus. This paper deals with the optimization problem considering nonlinear cost function where the cost of the power transmitter is nonlinear. We propose Genetic Algorithms (GAs) as the solution methodology for this problem.