• Journal of international Conference on Electrical Machines and Systems
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• 제2권2호
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• pp.171-178
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• 2013

This paper discusses to conduct experimental verification of two types of micro electric vehicles (EV) in order to realize improvement in electric mileage and shorten a charging time of the battery. First, electric double layer capacitor (EDLC) systems to use as a secondary battery are proposed. The internal resistance of EDLC is small compared with a rechargeable battery, and it is suitable for momentary charge-discharge of EV. Next, control circuits of the capacitors to increase the regenerative electric power are utilized. Then, a novel method to charge a main battery of the EV is introduced. Finally, experimental results demonstrate the validity of the proposed method.

• 전기학회논문지
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• 제60권3호
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• pp.566-571
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• 2011

As Plug-in Hybrid Vehicle and Electric Vehicle (PHEV/EV) take a greater share in the personal automobile market, their high penetration levels may bring potential challenges to electric utility especially at the distribution level. Thus, there is a need for the flexible charging management strategy to compromise the benefits of both PHEV/EV owners and power grid side. There are many different management methods that depend on the objective function and the constraints caused by the system. In this paper, the schema and dispatching schedule of centralized PHEV/EV charging spot network are analyzed. Also, we proposed and compared three power allocation strategies for centralized charging spot. The first strategy aims to maximize state of vehicles at plug-out time, the rest methods are equalized allocation and prioritized allocation based on vehicles SoC. The simulation results show that each run of the optimized algorithms can produce the satisfactory solutions to response properly the requirement from PHEV/EV customers.

• Journal of Electrical Engineering and Technology
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• 제12권1호
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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.

• 한국자동차공학회논문집
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• 제22권3호
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• pp.250-256
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• 2014

EV(Electric Vehicle) has many benefits such as prevention of global warming and so on. But due to driving source changing from combustion engine to battery and e-motor, new R&D difficulties have arisen which changing of desired vehicle performance and multidisciplinary design constraints by means of strong coupled multi-physics domain problems. Additionally, dynamics performances of EV becomes more important due to increasing customer's demands and expectations for EV in compare with internal combustion engine vehicle. In this paper suggests model based development platform of EV through integrated simulation environment for improving analyse & design accuracy in order to solve multi-physics problem. This simulation environment is integrated by three following specialized simulation tools IPG CarMaker, AVL Cruise, DYMOLA that adapted to each purpose. Furthermore, control algorithm of TV(Torque Vectoring) system is developed using independent driven e-motor at rear wheels for improving handling performance of EV. TV control algorithm and its improved vehicle performances are evaluated by numerical simulation from standard test methods.

• Journal of Electrical Engineering and Technology
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• 제8권1호
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• pp.1-10
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• 2013

The power industry is currently facing many challenges, due to the new environment created by the introduction of smart grid technologies. In particular, the large-scale deployment of electric vehicles (EVs) may have a significant impact on demand for electricity and, thereby, influence generation and transmission system planning. However, it is difficult to deal with uncertainties in EV charging loads using deterministic planning methods. This paper presents a two-stage stochastic decomposition method with Latin-hyper rectangle sampling (LHRS) to solve the integrated generation and transmission planning problem incorporating EV deployment. The probabilistic distribution of EV charging loads is estimated by Latin-hyper rectangle sampling (LHRS) to enhance the computational performance of the proposed method. Numerical results are presented to show the effectiveness of the proposed method.

• 한국자동차공학회논문집
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• 제20권2호
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• pp.38-46
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• 2012

This paper discusses the energy consumption for a mid-size electric vehicle(EV) under various conditions. In order to analyze which driving style is more efficient in terms of the system of the EV, we develop the electric vehicle model and apply several types of speed profiles such as different steady speeds, acceleration/deceleration, and a real world driving cycle including the elevation profile obtained from a GPS device. The results show that the energy consumption of the EV is affected by the operating efficiency of components when driving at low speed, while it depends on required power at wheels when driving at high speed. Also this paper investigates the effect of the elevation of a road and the rate of electrical braking on the energy consumption as well as the fuel economy of a conventional vehicle model under the same conditions.

• 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.

• International Journal of Advanced Culture Technology
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• 제11권2호
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• pp.330-344
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• 2023

This research report cuts across management sciences (market strategy entry mode development) and innovative technology (Electric Vehicle (EV)) alongside measures to submerge global warming. The development of a successful entry mode for the electric Vehicle into the African continent is the main objective of the study. The study focuses on an analysis of how electric car manufacturers can enter the African market in other to achieve global sustainability and social responsibility. The methodology is based on identifying the factors that affect the choice of an entry mode into international markets by multinational companies desiring to leverage their revenue through a foreign market. It also offered a quantitative approach that can support the economic and sustainability entry mode model for EVs and a qualitative approach of Porter's five forces analysis as an entry mode coaching tool for EVs. These proxies are used in quite a wide range of multivariate statistical methods (trend analysis, ratio, and probability, comparative t-test technique, auto-regression, and ordinary least square technique). The result acknowledges joint venture and setting of the plant (physical presents) as the optimal entry mode in African EV market. It requires the EV manufacturers a tire-free emission innovation technology in order to optimize the global sustainability initiative.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 A
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• pp.288-290
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• 1995

The new power train system for electric vehicle is introduced in this paper. This system includes two light weighted and high-efficient motor, two space vector PWM inverter, one system controller using CAN controller and DSP320C50. These are developed by KERI cooperated with 5 major industry companies, 5 universities including 2 foreign universities. The reliability and performance are proven by the test rig. The reference data will be collected for further researches.

• 한국가스학회지
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• 제23권1호
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• pp.54-61
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• 2019

휴대용 전자기기의 시장이 성장함에 따라서 Lithium Ion Battery(LIB)의 수요 또한 증가하고 있다. LIB는 다른 2차 전지에 비해 높은 효율성을 보이지만 열 폭주(Thermal runaway)로 인한 폭발/화재의 위험성이 있다. 특히나 대용량 LIB cell을 탑재한 Electric Vehicle(EV)의 경우 화재로 발생하는 대량의 독성 가스로 인한 위험성 또한 존재한다. 따라서 사고 피해를 최소화하기 위한 EV 화재로 발생하는 독성 가스의 위험성 분석이 필요하다. 이 연구에서는 EV의 화재로 발생하는 독성 가스의 유동을 전산유체역학(Computational Fluid Dynamic; CFD)을 이용하여 해석하였다. 문헌 조사 결과와 국내 EV 자료를 기반으로 시나리오를 설정하여 시나리오 발생 경과시간에 따른 독성 가스의 확산을 수치 해석하여 위험성에 대하여 분석 하였다. 이 연구는 EV 화재로 인한 독성 가스의 위험성을 분석하여 사고 발생에 의한 인명, 재산피해를 최소화하는데 의의를 가진다.