• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1674-1688
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• 2019

As environmental pollution and fossil fuel energy problems from fuel vehicle have occurred, the interest of electric vehicle(EV) has increased. EV industry and energy industry have grown dynamically in these days. It is expected that the next generation of primary transportation will be EV, and it is necessary to prepare EV infra and efficient energy management such as EV communication protocol, EV charge station, and smart grid. Those EV and energy industry fields are now on growth. Also, the study and development of them are now in progress. In this paper, distributed charge signal processing software for smart slow and quick EV charge is proposed and designed for dealing with EV charge demand. The software consists of smart slow and quick EV charge schedule engine and EV charge power distribution core. The software is designed to support two charge station types. One is normal EV charge station and the other is bus garage EV charge station. Both two types collect the data from EV charge stations, and then analyze the collected data. The software suggests optimized EV charge schedule and deliveries EV charge power distribution information to power switchboard system, and the designed software is implemented on embedded system. It is expected that the software provides efficient EV charge schedule.

• Journal of Internet Computing and Services
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• v.21 no.5
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• pp.119-127
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• 2020

As the electric vehicle (EV) market in South Korea grows, it is required to expand charging facilities to respond to rapidly increasing EV charging demand. In order to conduct a comprehensive facility planning, it is necessary to forecast future demand for electricity and systematically analyze the impact on the load capacity of facilities based on this. In this paper, we design and develop a Long Short-Term Memory (LSTM) neural network model that predicts the daily peak electric load at each charging station using the EV charging data of KEPCO. First, we obtain refined data through data preprocessing and outlier removal. Next, our model is trained by extracting daily features per charging station and constructing a training set. Finally, our model is verified through performance analysis using a test set for each charging station type, and the limitations of our model are discussed.

• Journal of Korea Water Resources Association
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• v.35 no.6
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• pp.797-805
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• 2002

The EV ROM, a joint reservoir operation model for flood control that accounts for the downstream flow condition, has been introduced in the preceding article (Shin et al, 2000). A joint reservoir operation model computer program for the Geum river basin, developed by FORTRAN Power Station 4.0 using the EV ROM, is hereby presented. Three case studies of flood control by joint operation of the Yongdam and Daechung Multipurpose Dams in the Geum river basin revealed that the performance of the EV ROM was superior to the existing Rigid ROM and Technical ROM. This is because the EV ROM can account for the downstream flow condition as well as the upstream inflow and the reservoir water level. In order to apply for various floods events in the future, consistent improvement of the developed EV ROM and efforts for more accurate rainfall prediction are required.

• The Transactions of the Korean Institute of Power Electronics
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• v.22 no.5
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• pp.414-422
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• 2017

This paper reviews the core technical trends of TESLA EV Motors. The TESLA EV Motors is explosively popular with a considerable recharging infrastructure, a wide 17-[inch] touch display, 417 [HP], and 378 [km] going distance. The object of this study analyzes the body appearance, motor and, battery cooling system, battery arrangement, battery management system, super charging station, power electronics, and induction motor.

• Journal of Internet Computing and Services
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• v.21 no.5
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• pp.39-48
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• 2020

Recently, the study and development of environment-friendly energy technique have increased in worldwide due to environmental pollution and energy resources problems. In vehicle industry, the development of electric vehicle(EV) is now on progress, and also, many other governments support the study and development and make an effort for EV to become widely available. In addition, though they strive to construct the EV infra such as a charge station for EV, the techniques related to managing charge demand and peak power are not enough. The standard of EV communication has been already established as ISO/IEC 15118, however, most of implemented EVs and EV charge stations do not support any communication between each of them. In this paper, an improved slow charge scheme for non-communication EVs is proposed and designed by using predicting charge demand. The proposed scheme consists of distributed charge model and charge demand prediction. The distributed charge model is designed to manage to distribute charge power depending on available charge power and charge demand. The charge demand prediction is designed to be used in the distributed charge model. The proposed scheme is based on the collected data which were from EV slow charge station in business building during the past 1 year. The system-level simulation results show that the waiting time of EV and the charge fee of the proposed scheme are better than those of the conventional scheme.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.57-69
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• 2022

Even though demand to charge EV(electric vehicles) is increasing, there are some problems to construct EV charging stations and problems from deficient them. Typical problem of EV charging stations is discordance for EV charging station location with its demand. This study investigates methods to determine the optimized location for fast EV charging stations considering charging demand in Seoul. Firstly, variables influencing on determination of determine the optimized location for fast EV charging stations were decided, and then evaluation of weights of the variables and data collection were conducted. Using the weights, location potential scores for each area-cell were calculated and optimized locations for fast EV charging stations were resulted.

• Journal of Electrical Engineering and Technology
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• v.8 no.5
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• pp.1234-1242
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• 2013

To verify the effectiveness of the proposed system, the charges in power demand are analyzed for an AC and DC distribution system for the existing V2G concept and electric vehicle charging stations connected to a Battery Energy Storage System. In addition, since many power-converter-based chargers are operated simultaneously in an EV charging station, the change in the system harmonics when several EV chargers are connected at a single point is analyzed through simulations.

• Proceedings of the KIPE Conference
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• 2017.07a
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• pp.64-65
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• 2017

This paper review the core technical trends of TESAL EV(Electric Vehicle) Motors. The object of this study analyzes electric vehicle's body appearance, motor cooling system, battery arrangement, battery management system (BMS), and super charging station etc.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.742-751
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• 2018

Electric vehicles (EV) are emerging as the future transportation vehicle reflecting their potential safe environmental advantages. Vehicle to Grid (V2G) system describes the hybrid system in which the EV can communicate with the utility grid and the energy flows with insignificant effect between the utility grid and the EV. The paper presents an optimal power control and energy management strategy for Plug-In Electric Vehicle (PEV) charging stations using Wind-PV-FC-Battery renewable energy sources. The energy management optimization is structured and solved using Multi-Objective Particle Swarm Optimization (MOPSO) to determine and distribute at each time step the charging power among all accessible vehicles. The Model-Based Predictive (MPC) control strategy is used to plan PEV charging energy to increase the utilization of the wind, the FC and solar energy, decrease power taken from the power grid, and fulfil the charging power requirement of all vehicles. Desired features for EV battery chargers such as the near unity power factor with negligible harmonics for the ac source, well-regulated charging current for the battery, maximum output power, high efficiency, and high reliability are fully confirmed by the proposed solution.

• Journal of Hydrogen and New Energy
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• v.28 no.6
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• pp.642-648
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• 2017

The use of fossil is causing enviromental all over the world. So hydrogen energy is attracting attention as one of the alternative. The government announced that 30% of the air pollution is because of the Internal Combustion Engine Vehicle. In addition, they plans to reduce Internal Combustion Engine Vehicles by 2030 and increase (electric vehicles, EV) or (fuel cell vehicle, FCV). The FCV is evaluated as a next-generation green car because it has a long driving distance and short charging time. However, the hydrogen industry is not able to expand due to the lack of refueling infrastrucutre. This paper predicts the site of hydrogen refueling stations for the expansion of the hydrogen industry and proposes a method to supply hydrogen multi energy filling stations.