Young Dae Ko

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

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.

Optimal design of the wireless charging electric vehicle

The On-Line Electric Vehicle (OLEV) is an electric vehicle system is that utilizes the innovative wireless charging solution developed at Korea Advanced Institute of Science and Technology (KAIST) in South Korea. The OLEV system consists of vehicles and road-embedded power transmitters. The battery in the vehicle is charged remotely from the transmitters buried under the road and the charge can be done even while the vehicle is moving. The prototype of the OLEV has been successfully developed and the process of developing a commercial version is in progress. The OLEV has been considered as one of the leading green mass transportation solutions in Seoul. The key issue in the commercialization of the OLEV is to determine the battery size and the allocation of the power transmitters on the route. This paper describes a method of allocating the power transmitters and evaluating the battery size using a mathematical optimization technique. Although the presented method is motivated from the actual design issue of the OLEV, the concept and approach can be applied to any electric vehicle system utilizing a wireless charging technology.

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 ( OLEV TM ) 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 OLEVs 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.

Cost benefits from standardization of the packaging glass bottles

This study deals with an integrated recycling system where two competing brewers standardize their glass bottles to implement the producer responsible recycling system. Immediate benefits from the standardization are three folds. Firstly, the sorting and exchange processes of the bottles collected for reuse by each brewer become no longer necessary. Secondly, cost reduction is achieved through streamlining of collection and reuse processes. Finally, under the stochastic demand of glass bottles their inventory holding costs and lost sales cost are reduced via inventory pooling. Through the development of the mathematical models we determine an optimal operation policy of two brewers that maximizes the sum of benefits obtained from standardization. Numerical examples are solved to show the validity of the model.

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.

System architecture and mathematical model of public transportation system utilizing wireless charging electric vehicles

In this paper the recent progress of the wireless charging electric transportation system developed at Korea Advanced Institute of Technology (KAIST) called On-Line Electric Vehicle (OLEV) is introduced. The system architecture and mathematical model describing the cost issue of the OLEV based public transportation system are presented. The OLEV is the vehicle and road integrated transportation system. The vehicle operates with an electric motor and battery. However, unlike conventional electric vehicles, the battery in the OLEV is charged remotely from the power transmitters installed in the road. The innovative wireless power transfer mechanism equipped in the OLEV system enables the vehicle to be charged while it is moving. Therefore, the long re-charging vehicle down time, which is the major problem of the conventional electric vehicle, is eliminated. The first commercial version of OLEV was deployed at the Seoul Grand Park. Moreover, activities to apply the OLEV technology to the public mass transportation system are being progressed. In this paper, we conceptually illustrate the design architecture of the wireless power transportation system. Also we discuss the economical design issue for applying the OLEV to the mass transportation system. In particular, with the mathematical model, we explain the cost trade off between the battery size and the power transmission allocation in the road for the OLEV based transportation system.

A closed-loop recycling system with a minimum allowed quality level on returned products

This paper deals with a closed-loop recycling system in which a stationary demand is satisfied by remanufactured products as well as newly manufactured products. In this system, only those used products that satisfy a minimum allowed quality level are bought back from customers for recycling. Thus the collection rate of used products is expressed as a function of the quality level and the unit bought-back price. It is assumed that the cycle consists of a single remanufacturing run and a single manufacturing run, both in Economic Production Quantity settings. Treating the quality of recycled products as a random variable, we develop a mathematical model with the objective of minimising the production and inventory costs. The decision variables are the length of the cycle, the minimum allowed quality level and the unit bought-back price of used products. To illustrate the validity of the model, sample problems are solved.

The design of capacitated facility networks for long term care service

Current research results are extended by allowing more than one type of facilities.Also, the capacity of facilities is considered with closest assignment requirement.A branch and bound algorithm is developed for exact solution with pruning rules, lower bound and upper bound.A genetic algorithm is presented for solving large sized problem. Life expectancy is going up and the demand of long term care facilities is increasing in most countries. This study deals with designing problem of facility networks for long-term care services in a city consisting of a number of regions. Assuming that in each region a candidate site for long-term care facility exists, we seek to identify regions where opening of a long-term care facility is desirable and also determine the type of new facility. For the problem, an integer programming model is formulated with the objective of minimizing the total construction cost. The closest assignment rule is adopted to reflect the preference of patient in choosing long term care facility by assigning patient to an open facility closest from his home. To solve the model, we develop a branch and bound algorithm for exact solution and a genetic algorithm to solve large sized problem. The validity of the mathematical model and the proposed algorithms are illustrated through a number of problem instances.

System Optimization for Dynamic Wireless Charging Electric Vehicles Operating in a Multiple-Route Environment

Dynamic wireless charging (DWC) technology, a novel way of supplying vehicles with electric energy, allows the vehicle battery to be recharged remotely while it is moving over power tracks, which are charging infrastructures installed beneath the road. DWC systems mitigate the range limitation of electric vehicles by using power tracks as additional sources of electric energy. This paper proposes a model and algorithm for optimally designing DWC electric vehicle (EV) systems, particularly those operating in multiple-route environments. Multi-route system comprises several single routes that share common road segments, and the vehicles operating on a specific route are equipped with identical batteries. We build a general model to optimally allocate power tracks and determine the vehicle battery size for each route. Then, we apply a particle swarm optimization algorithm to solve the given multi-route DWC-EV system optimization problem. A numerical example is solved to illustrate the characteristics of the multi-route model, and we show that the proposed modeling approach and algorithm are effective, compared with a mixed integer programming-based exact solution approach. We also conduct a sensitivity analysis to examine the solution behavior of the problem.

Mathematical modeling and optimization of the automated wireless charging electric transportation system

In this paper, we introduce the automated wireless charging solution in the revolutionary transportation system called On-Line Electric Vehicle (OLEV). Also, we present the mathematical model and optimization method to evaluate the optimal key parameters in the automated system. The OLEV, recently developed by Korea Advanced Institute of Science and Technology (KAIST), is the transportation system utilizing the innovative wireless charging technology. The OLEV operates with an electric motor and a battery. Unlike conventional electric vehicles which rely on manual cable-plug-in operations for charging, the battery in the OLEV system is charged remotely from the power transmitters buried under the road. Also the charge can be done automatically while the vehicle is in motion. As a result, the re-charging down-time, which is the major drawback of the conventional electric vehicle, is significantly reduced and the operational efficiency is dramatically improved. The OLEV is selected as one of “the 50 Best Innovations of 2010” by TIME Magazine and it is now being considered for a next generation green transportation system in several metropolitan cities in Korea. In this paper, we present an mathematical model to optimize the key parameters of the automated charging solution in the OLEV. The Mixed Integer Programming (MIP) algorithm is used for the optimization model. Numerical results are also presented.