Seungmin Jeong

Economic Analysis of the Dynamic Charging Electric Vehicle

A wireless charging or inductive charging electric vehicle (EV) is a type of EVs with a battery that is charged from a charging infrastructure, using a wireless power transfer technology. Wireless charging EVs are classified as stationary or dynamic charging EVs. Stationary charging EVs charge wirelessly when they are parked, and dynamic charging EVs can charge while they are in motion. The online electric vehicle developed at the Korea Advanced Institute of Science and Technology is an example of a commercially available dynamic charging transportation system. Numerous studies have reported that one of the benefits of dynamic charging is that it allows smaller and lighter batteries to be used, due to frequent charging using the charging infrastructure embedded under roads. In this paper, we quantitatively analyze the benefits of dynamic charging with an economic model of battery size and charging infrastructure allocation, using a mathematical optimization model. Particularly, we analyze by how much battery size can be reduced and what the cost saving of reducing the battery size is with the model. We also show that the dynamic charging can be beneficial to battery life.

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.

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.

M&S Verification, Validation and Accreditation Research Direction Considering the Characteristics of Defense M&S

In this paper, we first present an in-depth survey of the research on Verification, Validation and Accreditation (VV&A) applied in various areas. Then we introduce the characteristics of the military and defense Modeling and Simulation (M&S) and propose the direction of method for VV&A with the identified characteristics. The M&S has been widely used in many different applications in the military and defense area including training, analysis, and acquisition. Methods and processes of VV&A have been proposed by researchers and M&S practitioners to guarantee the correctness of the M&S. The idea of applying the formal credibility assessment in VV&A is originated from the Software Engineering Reliability Test and Systems Engineering Development Process. However, the current VV&A techniques and processes proposed in the research community have not utilized the military-and-defense specific characteristics. We identify the characteristics and issues that can be found in the military and defense M&S. Then propose the direction of techniques and methods for VV&A considering the characteristics and issues. Also, possible research direction on the development of VV&A is proposed.

Design Optimization of the OLEV System Considering Battery Lifetime

We present recent developments in the wireless powered On-Line Electric Vehicle (OLEV) developed by the Korea Advanced Institute of Technology (KAIST). Using advanced wireless power transfer technology, a battery in the vehicle can be charged remotely from the wireless power transmitters embedded in the road. However, the battery lifetime varies depending on the charge and discharge cycles, which are decided by installation of the wireless power transmitters. In this paper, we briefly introduce the system design issues of the OLEV and identify relation between the OLEV system design and the batterys lifetime. We then present the battery state model and the battery lifetime prediction model under given set of wireless power transmitters. In proposed battery lifetime prediction model, we apply a fatigue aging approach of the battery. The optimization problem is set to find economical allocation of the wireless power transmitters. The particle swarm optimization (PSO) algorithm is implemented as the solution approach for the optimization problem. The KAIST campus shuttle system is used as numerical case result and comparison with previous approach of the OLEV system design is presented.

New Opportunity in ITS - Transportation Systems with Wireless Power Transfer Technology

In this industry application paper, we present the wireless power electric vehicle called On-Line Electric Vehicle (OLEV) developed at Korea Advanced Institute of Technology (KAIST). With the advanced wireless power transfer technology, the battery in the vehicle is charged remotely from the power transmitters embedded in the road. This road-way charging capability enables the vehicle to be charged while they are in motion and therefore the vehicle does not need to make frequent stops to charge the battery. In this paper, the wireless power transfer technology applied to the OLEV system is described. Also, the recent advances of the OLEV technology and commercialization processes are presented. Then the economical design method of the mass transportation system based on the OLEV technology is discussed. There is strong potential for further development of the OLEV system if the system effectively utilizes advanced information systems and real-time traffic data. This industry application oriented paper provides researchers and engineers with an opportunity to learn about the emerging transportation system, which could be further progressed with various methods developed in ITS.

System model and simulation for optimal parameter design of dynamic wireless charging EVs

In this paper, we provide the numerical analysis of the charging states for the dynamic wireless charging (DWC) electric vehicles (EVs), or simply called DWC-EVs, which charge the their batteries from the power source embedded under the road while the vehicles are in motion. The previous studies suggested the optimal allocation of the wireless power source called power track and economic size of the battery. However, these studies used the assumption that the vehicles are driving with a predetermined speed. This study relaxes the nominal speed assumption and instead assumes that the uncertainty in the vehicle speed. The goal of this study is to understand the how the uncertainty in driving causes the performance of the charging and operation of the vehicles for the DWC-EV based public transportation system. In this study, we used the operation data collected from the KAIST On-line Electric Vehicle (OLEV) currently operating in a Gumi City in South Korea, which is one of the first commercialized DWC-EVs. With the data, energy states are generated from the Markov-based energy consumption simulation model. The simulation results indicate that there is significant risk of running out of battery if the power tracks are allocated and battery size is selected with the nominal speed assumption.