• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1789-1797
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• 2017

It is necessary to charge electric vehicles in order to drive them. Thus, it is essential to have electric vehicle charging facilities in place. In the case of a household battery charger, the power similar to that consumed by a household with a basic contract power of 3kW is consumed. In addition, many consumers who own an electric vehicle will charge their vehicles at the same time. The simultaneous charging of electric vehicles will cause the load to increase, which then will lead to the imbalance of supply and demand in the distribution system. Thus, a smart charging scheme for electric vehicles is an essential element. In this paper, simulated conditions were set up using real data relating to Korea in order to design a smart charging technique suitable for the actual situation. The simulated conditions were used to present a smart charging technique for electric vehicles that disperses electric vehicles being charged simultaneously. The EVs and Smart Charging Technique are modeled using the Electro Magnetic Transients Program (EMTP).

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.8
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• pp.1138-1143
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• 2013

In this paper, we propose a smartphone application based on a wireless fidelity(WiFi) in order to control the charging of electric vehicle(EV) and monitor the charging status together with the vehicle history information. The driver obtains much information on vehicle status through a smartphone application which communicates with the electric vehicle supply equipment(EVSE) management server while the EV also communicates with the EVSE for the authentification through controller area network(CAN). We also implement the simulator for the EV charging control system to verify the functions of the proposed application where the simulator consists of an EV model, an EVSE, and a smartphone. It is shown by the simulator that the proposed smartphone application allows the driver to control and to monitor the charging process of an EV conveniently and, moreover, it can provide the driver with vehicle information stored in the EVSE management server.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.5
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• pp.31-37
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• 2012

In this paper, we present a smart grid monitoring system connected with electric vehicle charging system using anti-islanding method. Electric vehicles can be charged through remote control of smart grid monitoring system and the charging process may be more stable and more efficient by wireless communication between the Local Area Module and End Modules. It is illustrated by some experiments that electric vehicle charging process may not be interrupted without any serious fault even though the islanding phenomena occurred in the grid if the presented monitoring system was applied to the smart grid system.

• Journal of IKEEE
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• v.22 no.2
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• pp.369-374
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• 2018

In this paper, the energy cost saving in multi-channel electric vehicle charging system. Joint use of the electric car charger battery state of charging proposed a method based charging. A linear programming with two type is used for optimal control, and the time-of-use price is included to calculate the energy costs. Simulation results show that the reductions of energy cost and peak power can be obtained using proposed method.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.451-458
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• 2017

An Electric Vehicle (EV) is operated with the electric energy of a battery in place of conventional fossil fuels. Thus, a suitable charging infrastructure must be provided to expand the use of electric vehicles. Because the battery of an EV must be charged to operate the EV, expanding the number of EVs will have a significant influence on the power supply and demand. Therefore, to maintain the balance of power supply and demand, it is important to be able to predict the numbers of charging EVs and monitor the events that occur in the distribution system. In this paper, we predict the hourly charging rate of electric vehicles using transformation matrix, which can describe all behaviors such as resting, charging, and driving of the EVs. Simulation with transformation matrix in a specific region provides statistical results using the Monte-Carlo Method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.669-674
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• 2017

Due to the depletion of fossil fuels and the increase in environmental pollution, electric vehicles are attracting attention as next-generation transportation and are becoming popular all over the world. As the interest in electric vehicles and the penetration rate increase, studies on the charging infrastructure with vehicle-to-grid (V2G) technology and information technology are actively under way. In particular, communication with the grid network is the most important factor for stable charging and load management of electric vehicles. However, with the existing centralized infrastructure, there are problems when control-message requests increase and the charging infrastructure cannot efficiently operate due to slow response speed. In this paper, we propose a new charging infrastructure using mobile edge computing (MEC) that mitigates congestion and provides low latency by applying distributed cloud computing technology to wireless base stations. Through a performance evaluation, we confirm that the proposed charging infrastructure (with low latency) can cope with peak conditions more efficiently than the existing charging infrastructure.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.2
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• pp.1-10
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• 2017

The high costs of electric vehicle supply equipment (EVSE) and installation are currently a stumbling block to the proliferation of electric vehicles (EVs). The cost-effective solutions are needed to support the expansion of charging infrastructure. In this paper, we develope EV charging system based on the big data analysis of the power consumption patterns. The developed EV charging system is consisted of the smart EV outlet, gateways, powergates, the big data management system, and mobile applications. The smart EV outlet is designed to low costs of equipment and installation by replacing the existing 220V outlet. We can connect the smart EV outlet to household appliances. Z-wave technology is used in the smart EV outlet to provide the EV power usage to users using Apps. The smart EV outlet provides 220V EV charging and therefore, we can restore vehicle driving range during overnight and work hours.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.12
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• pp.1866-1872
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• 2017

This paper presents the design of in-wheel type Switched Reluctance Motor (SRM) which can be used as both traction motor and power pickup device in a wireless charging system of electric vehicles. The SRM acts as a traction drive in driving mode and a power receiver in charging mode to avoid any additional weights. Double stator axial field SRM is used due to its structure that can be mounted inside the wheel. The charging circuit is integrated with the asymmetric converter and phase windings of SRM, reducing the cost and size of the system. Magnetic resonance is implemented to increase the efficiency. Simulations done in Maxwell and Simplorer verify the effectiveness of the proposed system.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.1855-1860
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• 2010

Electric vehicles have reached a new level of development with introductions by Chrysler, Ford, Honda and Toyota. Today's charging technology includes conductive and inductive charging systems. There are three standardized charging levels: Level 1: charging can be done from a standard, grounded AC 120V, 3-prong outlet available in all homes; Level 2: charging is at AC 240V, 40 amp charging station with special consumer features to make it easy and convenient to plug in and charge EVs at home or at an EV charging station; Level 3: a high-powered charging "fast charge" technology currently under development that will provide a charge in less than 15 minutes. The incoming AC power is converted to DC and stored in the vehicle's batteries. In this paper, we investigated the application of urban railway DC electric power for electric car charging system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.3
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• pp.53-60
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• 2020

Evaluating the operational efficiency of electric vehicle charging stations (EVCSs) is important to understand charging network evolution and the charging behavior of electric vehicle users. However, aggregation of efficiency performance metrics poses a significant challenge to practitioners and researchers. In general, the operational efficiency of EVCSs can be measured as a complicated function of various factors with multiple criteria. Such a complex aspect of managing EVCSs becomes one of the challenging issues to measure their operational efficiency. Considering the difficulty in the efficiency measurement, this paper suggests a way to measure the operational efficiency of EVCSs based on data envelopment analysis (DEA). The DEA model is formulated as constant returns of output-oriented model with five types of inputs, four of them are the numbers of floating population and nearby charging stations, distance of nearby charging stations and traffic volume as desirable inputs and the other is the traffic speed in congestion as undesirable one. Meanwhile, the output is given by the charging frequency of EVCSs in a day. Using real-world data obtained from reliable sources, we suggest operational efficiencies of EVCSs in Seoul and discuss implications on the development of electric vehicle charging network. The result of efficiency measurement shows that most of EVCSs in Seoul are inefficient, while some districts (Nowon-gu, Dongdaemun-gu, Dongjak-gu, Songpa-gu, Guro-gu) have relatively more efficient EVCSs than the others.