• 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.

• Proceedings of the KIPE Conference
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• 2011.07a
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• pp.429-430
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• 2011

This paper presents a simple and cost-effective stand-alone rapid battery charging system of 30kW for electric vehicles. The proposed system mainly consists of active front-end rectifier of neutral point clamped 3-level type and non-isolated bi-directional dc-dc converter of multi-phase interleaved half-bridge topology with coupled inductors. The charging system is designed to operate for both lithium-polymer and lithium-ion batteries. The complete charging sequence is made up of three sub-interval operating modes; pre-charging mode, constant-current mode, and constant-voltage mode. The pre-charging mode employs the staircase shaped current profile to accomplish shorter charging time while maintaining the reliable operation of the battery. The proposed system is able to reach the full-charge state within less than 16min for the battery capacity of 8kWh by supplying the charging current of 67A. The optimal discharging algorithm for Vehicle to the Grid (V2G) operation has been adopted to maintain the discharging current of 1C. Owing to the simple and compact power conversion scheme, the proposed solution has superior module-friendly mechanical structure which is absolutely required to realize flexible power expansion capability in a very high-current rapid charging system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.632-639
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• 2018

Recently, a policy has been enforced to supply Plug-in Electric Vehicles (PEVs) but this may require reinforcement of the power system depending on its clustering because PEVs are charged directly from power systems. On the other hand, as the reinforcement of power system is limited by time and budget, it is important to supply the charging demand of PEVs efficiently using the existing power systems to increase the diffusion of PEVs. This paper establishes a charging schedule for Plug-in Electric Vehicles (PEVs) considering the power system constraints. For this, the required amount and time of the charging demand for an individual PEV was modeled to integrate into power systems based on the driving pattern and charging tariff of PEV. Furthermore, the charging schedule of PEVs was established to meet the power system constraints by calculating the operating conditions of the power systems with PEVs.

• The Transactions of the Korean Institute of Power Electronics
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• v.18 no.1
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• pp.26-36
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• 2013

This paper presents a simple and cost-effective stand-alone rapid battery charging system of 30kW for electric vehicles. The proposed system mainly consists of active front-end rectifier of neutral point clamped 3-level type and non-isolated bi-directional dc-dc converter of multi-phase interleaved half-bridge topology. The charging system is designed to operate for both lithium-polymer and lithium-ion batteries. The complete charging sequence is made up of three sub-interval operating modes; pre-charge mode, constant-current mode, and constant-voltage mode. The pre-charge mode employs the stair-case shaped current profile to accomplish shorter charging time while maintaining the reliable operation of the battery. The proposed system is specified to reach the full-charge state within less than 16min for the battery capacity of 8kWh by supplying the charging current of 78A. Owing to the simple and compact power conversion scheme, the proposed solution has superior module-friendly mechanical structure which is absolutely required to realize flexible power expansion capability in a very high-current rapid charging system.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.3
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• pp.228-236
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• 2022

The charging methods of electric vehicles are divided into wired charging and wireless charging. Restrictions on the use of charging infrastructure for wireless charging vehicles currently exist because most charging infrastructure uses the wired charging method. Thus, wired and wireless integrated charging system has been studied. In this system, a wireless charging system especially requires a control method for high-efficiency operation in consideration of a change in a coupling coefficient. Therefore, this paper introduces two control methods for the high-efficiency operation of wireless charging that can be applied to wired and wireless integrated charging systems. In addition, loss analysis is performed through PSIM simulation to select a more advantageous method for high-efficiency operation among the two control methods. To verify the simulation-based loss analysis result, the two control methods are applied to the actual wireless charging system, and the efficiency is compared through the experiments Based on the experimental results, a control method suitable for high-efficiency operation of the wireless charging method is selected.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.9
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• pp.1577-1582
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• 2016

Now we are facing severe environmental issues such as global warming. Due to these, the concerns about eco-friendly energy have been increased. Kyoto protocol and Copenhagen climate change conference are circumstantial evidence of it. With these trends, the interests for the Electric Vehicles(EVs) which do not emit any harmful gases have gradually been raised. Unfortunately, however, massive connection of EVs to the power system could cause negative impacts such as voltage variations, frequency variations and increase of demand power. To prevent the mentioned issues, KEPCO adopts Time-of-Use(ToU) price for EVs charging. Nevertheless, it is important to verify the propriety of the charging system. In this paper, therefore, we used pre-introduced price elasticity concept to predict possible Demand Response(DR) on charging of EVs. And analyzed possible demand power increase according to various price elasticities. Simulation results show that given ToU based charging system would not enough to control the increase of demand power by EVs on the power system. It is concluded, therefore, additional methods and/or algorithms are required.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.10
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• pp.1911-1915
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• 2009

The problem of determining the proper capacity of electric vehicle charging station is studied in the presented paper. Based on the expected arrival rate and the expected charging time, we calculate the proper capacity that guarantees electric vehicles get service better than a given lower bound which is termed the loss of charging probability. The problem is studied by using certain queueing models. We first formulate the problem as a queueless model of type M/M/n/n, known as the Erlang loss system. And then the M/M/n/K type queueing model is formulated to consider the parking space constraint. Results of the study may be used for designing the electric vehicle charging station.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.937-944
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• 2022

Electric vehicles (EVs) have been growing to reduce energy consumption and greenhouse gas (GHG) emissions in the transportation sector. The increasing number of EVs requires adequate recharging infrastructure, and at the same time, adopts low- or zero-emission electricity production because the GHG emissions are highly dependent on primary sources of electricity production. Although previous research has studied solar photovoltaic (PV) -integrated EV charging stations, it is challenging to optimize spatial areas between where the charging stations are required and where the renewable energy sources (i.e., solar photovoltaic (PV)) are accessible. Therefore, the primary objective of this research is to support decisions of siting EV charging stations using a spatial data clustering method integrated with Geographic Information System (GIS). This research explores spatial relationships of PV power outputs (i.e., supply) and traffic flow (i.e., demand) and tests a community in the state of Indiana, USA for optimal sitting of EV charging stations. Under the assumption that EV charging stations should be placed where the potential electricity production and traffic flow are high to match supply and demand, this research identified three areas for installing EV charging stations powered by rooftop PV in the study area. The proposed strategies will drive the transition of existing energy infrastructure into decentralized power systems. This research will ultimately contribute to enhancing economic efficiency and environmental sustainability by enabling significant reductions in electricity distribution loss and GHG emissions driven by transportation energy.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.1-2
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• 2015

In this paper, a 2-phase feeder system for wireless vehicle charging is investigated, which generates moving magnetic field with nearly constant magnitude using 2-phase currents. A moving field is very useful to magnetizing pickups mounted on underneath of electric vehicles.

• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1276-1282
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• 2013

This paper proposes a stochastic modeling of plug-in electric vehicles (PEVs) distribution in power systems, and analyzes the corresponding clustering characteristic. It is essential for power utilities to estimate the PEV charging demand as the penetration level of PEV is expected to increase rapidly in the near future. Although the distribution of PEVs in power systems is the primary factor for estimating the PEV charging demand, the data currently available are statistics related to fuel-driven vehicles and to existing electric demands in power systems. In this paper, we calculate the number of households using electricity at individual ending buses of a power system based on the electric demands. Then, we estimate the number of PEVs per household using the probability density function of PEVs derived from the given statistics about fuel-driven vehicles. Finally, we present the clustering characteristic of the PEV distribution via case studies employing the test systems.