• 한국기계가공학회지
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• 제19권5호
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• pp.8-13
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• 2020

In this paper, the electric vehicle (EV) and internal combustion engine vehicle (ICEV) are compared for different driving cases. The EV exhibits a lower powertrain efficiency when driven on the aggressive driving cycle than when driven on the moderate cycle. In particular, EV powertrain efficiency is low when the battery state of charge (SOC) is low, but ICEV efficiency increases when the driving cycle changes from the moderate cycle to the aggressive cycle. Based on these results, attempts can be made to increase EV powertrain efficiency. EV charging before the battery power drops to a low charging state can reduce energy consumption by 2.7% for an urban area. Furthermore, ECO driving has a more significant effect on EVs than on ICEVs.

• 한국수소및신에너지학회논문집
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• 제30권6호
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• pp.505-512
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• 2019

According to the "hydrogen economy roadmap" announced recently by the government, fuel cell electric vehicle diffusion and hydrogen refueling station construction are actively being carried out to prepare for the hydrogen economy era. The station will be expanded by introducing various charging station models such as hydrogen complex charging station, package, and mobile. Accordingly, the study on the safety demonstration of the charging station and related regulations should be compromised. The purpose of this study is to collect monitoring data during charging according to the distinct four seasons in Korea, and to use it as safety demonstration data by analyzing the charging status, charging rate and charging time during charging.

• 전력전자학회논문지
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• 제18권1호
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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.

• 한국항행학회논문지
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• 제18권4호
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• pp.393-400
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• 2014

선진 각국과 더불어 국내에서 전기자동차에 대한 보급 및 개발이 급속도로 진행되고 있다. 현재 충전기 규격 및 충전방법, 통신 프로토콜에 대한 표준화가 각국에서 진행 중이며 많은 회사들이 사업에 참여하고 있다. 이러한 전기자동차가 보급되어 기존의 자동차와 같은 양상으로 대중화되기 위해서는 국내 환경에 맞는 인프라 및 네트워크가 구축되어야 할 필요성이 있다. 또한 충전기와 상위 단 서버와의 프로토콜 구축을 넘어 실제 주택환경에서 사용되어질 수 있는 표준화된 프로토콜을 개발하여 관련 산업분야에 적용할 수 있도록 해야 한다. 따라서 본 논문에서는 전기자동차충전시스템 연구에 대한 필요성을 제기하고 우리나라에 주택환경에 맞는 멀티충전시스템과 M2M 기술을 이용한 전기자동차 홈 네트워크 모델을 제안하였다.

• 인터넷정보학회논문지
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• 제21권5호
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• pp.119-127
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• 2020

국내 전기차 (EV: Electric Vehicle) 시장이 성장함에 따라, 빠르게 증가하는 EV 충전 수요에 대응하기 위한 충전설비의 확충이 요구되고 있다. 이와 관련하여, 종합적인 설비 계획을 수립하기 위해서는 미래 시점의 충전 수요량을 예측하고 이를 바탕으로 전력설비 부하에 미치는 영향을 체계적으로 분석하는 것이 필요하다. 본 논문에서는 한국전력공사의 EV 충전 데이터를 이용하여 충전소 단위의 일별최대부하를 예측하는 LSTM(Long Short-Term Memory) 신경망 모델을 설계 및 개발한다. 이를 위해, 먼저 데이터 전처리 및 이상치 제거를 통해 정제된 데이터를 얻는다. 다음으로, 충전소 단위의 일별 특징들을 추출하여 훈련 데이터 집합을 구성하여 일별 최대 전력부하 예측 모델을 학습시킨다. 마지막으로 충전소 유형 별 테스트 집합을 이용한 성능 분석을 통해 예측 모델을 검증하고 이의 한계점을 논의한다.

• Journal of Electrical Engineering and Technology
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• 제8권6호
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• pp.1269-1275
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• 2013

Recently, many studies have suggested that an electric vehicle (EV) is one of the means for increasing the reliability of power systems in new energy environments. EVs can make a contribution to improving reliability by providing frequency regulation in power systems in which the Vehicle-to-Grid (V2G) technology has been implemented and, if economically viable, can be helpful in increasing power system reliability. This paper presents a stochastic method for optimal coordination of charging and frequency regulation decisions for an EV aggregator using the Least Square Monte-Carlo (LSMC) with modeling of electricity price uncertainty. The LSMC can be used to assess the value of options based on electricity price uncertainty in order to simultaneously optimize the scheduling of EV charging and regulation service for the EV aggregator. The results of a numerical example show that the proposed method can significantly improve the expected profits of an EV aggregator.

• Current Photovoltaic Research
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• 제11권4호
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• pp.124-133
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• 2023

In order to deploy the large-scale energy storage (ES) service in the various industry, it is very important to develop a business model with high technological and economic feasibility through detailed valuation of cost and expected benefits. In relation to this, this paper established an optimal scheduling plan for electric vehicle charging stations connected with photovoltaic (PV) and ES technologies in Korea using the distributed energy resource valuation tool and analyzed the feasibility of the project. In addition, the impact of incentives such as REC (Renewable Energy Certificate) to be given to electric vehicle charging stations in accordance with the relevant laws to be revised in the future was analyzed. As a results, the methodology presented in this paper are expected to be used in various ways to analyze the feasibility of various business models linked to renewable energy and ES technologies as well as the electric vehicle market.

• Journal of Communications and Networks
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• 제14권6호
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• pp.672-681
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• 2012

A potential breakthrough of the electrification of the vehicle fleet will incur a steep rise in the load on the electrical power grid. To avoid huge grid investments, coordinated charging of those vehicles is a must. In this paper, we assess algorithms to schedule charging of plug-in (hybrid) electric vehicles as to minimize the additional peak load they might cause. We first introduce two approaches, one based on a classical optimization approach using quadratic programming, and a second one, market based coordination, which is a multi-agent system that uses bidding on a virtual market to reach an equilibrium price that matches demand and supply. We benchmark these two methods against each other, as well as to a baseline scenario of uncontrolled charging. Our simulation results covering a residential area with 63 households show that controlled charging reduces peak load, load variability, and deviations from the nominal grid voltage.

• Journal of Communications and Networks
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• 제14권6호
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• pp.662-671
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• 2012

Plug-in hybrid electric vehicles (PHEVs) will be widely used in future transportation systems to reduce oil fuel consumption. Therefore, the electrical energy demand will be increased due to the charging of a large number of vehicles. Without intelligent control strategies, the charging process can easily overload the electricity grid at peak hours. In this paper, we consider a smart charging and discharging process for multiple PHEVs in a building's garage to optimize the energy consumption profile of the building. We formulate a centralized optimization problem in which the building controller or planner aims to minimize the square Euclidean distance between the instantaneous energy demand and the average demand of the building by controlling the charging and discharging schedules of PHEVs (or 'users'). The PHEVs' batteries will be charged during low-demand periods and discharged during high-demand periods in order to reduce the peak load of the building. In a decentralized system, we design an energy cost-sharing model and apply a non-cooperative approach to formulate an energy charging and discharging scheduling game, in which the players are the users, their strategies are the battery charging and discharging schedules, and the utility function of each user is defined as the negative total energy payment to the building. Based on the game theory setup, we also propose a distributed algorithm in which each PHEV independently selects its best strategy to maximize the utility function. The PHEVs update the building planner with their energy charging and discharging schedules. We also show that the PHEV owners will have an incentive to participate in the energy charging and discharging game. Simulation results verify that the proposed distributed algorithm will minimize the peak load and the total energy cost simultaneously.

• 센서학회지
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• 제25권2호
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• pp.155-159
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• 2016

In this work, we have developed a test system to examine whether the charge indicator of the plug-in hybrid electric vehicle (PHEV) works properly or not. In PHEV, the driver should charge the necessary electricity by plugging in manually and be able to know the charging status through the charge indicator conveniently located for the charging individual. Our system used the CAN bus to transmit the same commands from ECU to the indicator to test the proper operation of the indicator lights. It measured the electric current values during operation and analyzed to determine the quality of the indicators. The inspection items included the proper packaging, the electrical shorts, the LED lighting during charging, the LED lighting for charging failure, and the LED lighting when errors occur. We developed the system for the operators in the factory allowing them to approve the test results at the site. We developed the hardware, the control software, and the software to store the test results and the history of the products in the database. Serial numbers were given to the good quality products and the bar code labels were printed to trace the products afterwards. Through this work, we developed a system to inspect the electric parts in real time upon fabrication. We are planning to further improve our system to inspect the brightness of the indicator by adding the vision inspection in future.