• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권3호
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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.

• 산업경영시스템학회지
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• 제42권4호
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• pp.23-30
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• 2019

Automobiles are largely divided into passenger cars with less than five passengers and commercial vehicles such as construction machines, trucks, mixers, special lorries, and large buses. Automobile maintenance companies are also divided into passenger cars and commercial vehicles. Because commercial vehicles are the livelihood vehicles of individual carriers engaged in cargo transportation, passenger transportation, and construction, fast and accurate maintenance is important. Access to the expressway is also important because the car is large and uses highways. In addition, the time required for troubleshooting is long, so sufficient space must be secured for parking the vehicle, and ease of entry and exit of the vehicle in the maintenance shop should be fully considered. For this reason, commercial vehicle maintenance companies have higher initial investment costs than car maintenance companies, and it is difficult to supply and maintain maintenance personnel. Therefore, it is necessary to carefully examine and analyze various related factors for successful commercial vehicle maintenance company selection. However, most existing commercial vehicle maintenance companies often choose their location based on the empirical judgment of the founder, the customs and the case, without a clear analysis. In this study, we show how to derive the location selection factors to be considered when establishing professional maintenance company for commercial vehicles and to select the optimal location by using AHP (Analytic Hierarchy Process) method.

• International Journal of Internet, Broadcasting and Communication
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• 제9권2호
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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.

• International Journal of Computer Science & Network Security
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• 제24권4호
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• pp.87-106
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• 2024

Vehicle-to-Home (V2H) and Home Centralized Photovoltaic (HCPV) systems can address various energy storage issues and enhance demand response programs. Renewable energy, such as solar energy and wind turbines, address the energy gap. However, no energy management system is currently available to regulate the uncertainty of renewable energy sources, electric vehicles, and appliance consumption within a smart microgrid. Therefore, this study investigated the impact of solar photovoltaic (PV) panels, electric vehicles, and Micro-Grid (MG) storage on maximum solar radiation hours. Several Deep Learning (DL) algorithms were applied to account for the uncertainty. Moreover, a Reinforcement Learning HCPV (RL-HCPV) algorithm was created for efficient real-time energy scheduling decisions. The proposed algorithm managed the energy demand between PV solar energy generation and vehicle energy storage. RL-HCPV was modeled according to several constraints to meet household electricity demands in sunny and cloudy weather. Simulations demonstrated how the proposed RL-HCPV system could efficiently handle the demand response and how V2H can help to smooth the appliance load profile and reduce power consumption costs with sustainable power generation. The results demonstrated the advantages of utilizing RL and V2H as potential storage technology for smart buildings.

• The Journal of Asian Finance, Economics and Business
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• 제8권10호
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• pp.269-283
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• 2021

The government policies and initiatives to guarantee sustainable energy and clean environmental conditions contributed to the introduction of green technology electricity appliances in the market. This study sought to determine the physiological and socio-economics-demographic factors driving residential electricity consumers to use green technology electricity appliances, mainly solar PV, smart meter, electric vehicle, and battery storage technology. By understanding consumer intention, the investors of solar PV, battery storage, electric vehicle, and smart meter can estimate the demand and upscale the market for the corresponding products. For that purpose, the intention to use the solar PV, smart meter, electric vehicle, and battery storage function is developed by utilizing the combination of the theory of planned behavior, technology acceptance, and reasoning action. A reliable and valid structured online questionnaire and stepwise multiple regression are used to identify the possible factors that drive consumer behavior intention. The results show that the social influence, knowledge on RE, and perceived price significantly influence residential consumers' willingness to adopt the technologies offered. The findings of this study suggest that the involvement of NGOs, public figures, and citizens' cooperation are all necessary to spread information about the government's objectives and support Malaysia's present energy and environmental policies.

• Journal of information and communication convergence engineering
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• 제8권6호
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• pp.665-670
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• 2010

This paper suggests the vehicle remote control on the basis of Smart Phone. In general, most smart phone is mounted with G-sensor to control the motion. G-sensor is able to control several directions and movements of velocity along with X, Y, and Z axis. To access remote location and data system, we can also utilize Wi-Fi communication as well as bluetooth communication. In this study, we propose the scheme that is the car management application by remote control via real-time monitoring on mobile device for user convenience.

• 한국방재안전학회논문집
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• 제14권2호
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• pp.35-42
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• 2021

본 논문은 전기자동차 충전시설 확충계획에 중요한 요소인 전기자동차 전력 수요량 예측정보를 생산하기 위하여 Exponential Smoothing를 이용하여 전력 수요량 예측 모형을 제안하였다. 모형의 입력자료 구축을 위하여 종속변수로 월별 시군구 전력수요량을 독립변수로 월별 시군구 충전소 보급대수, 월별 시군구 전기자동차 충전소 충전 횟수, 월별 전기자동차 등록대수 자료를 월 단위로 수집하고 수집된 7년간 자료 중 4년간 자료를 학습기간으로 3년간 자료를 검증 기간으로 적용하였다. 전기자동차 전력 수요량 예측 모형의 정확성을 검증하기위하여 통계적 방법인 Exponential Smoothing(ETS), ARIMA모형의 결과와 비교한 결과 ETS, ARIMA 각각의 오차율은 12%, 21%로 본 논문에서 제시한 ETS가 9% 더 정확하게 분석되었으며, 전기자동차 전력 수요량 예측 모형으로써 적합함을 확인하였다. 향후 이 모형을 이용한 전기자동차 충전소 설치 계획부터 운영관리 측면에서 활용될 것으로 기대한다.

• 예술인문사회 융합 멀티미디어 논문지
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• 제8권2호
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• pp.33-40
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• 2018

현재 산업계와 학계에서는 커넥티드 카(connected car) 시스템에 대한 연구가 활발하게 진행되고 있다. 커넥티드 카는 IT기술이 융합된 스마트(smart)한 자동차로서 사람, 차량, 교통관리 시스템과 모두 연결되어 있다. 커넥티드 카의 주행을 위해 차량과 인프라(infrastructure) 간의 연결 기술인 V2I(vehicle to infrastructure) 통신이 중요하다. CIM(cooperative intersection management)은 차량과 인프라 사이에서 통신을 관리하는 장치이다. 본 논문에서는 CIM을 사용해 교차로에서 차량을 제어하는 두 가지 기법에 대해 분석한다. 첫 번째 기법은 자원화 된 교차로 예약을 통해 교차로를 지나간다. 두 번째 기법은 미리 계획된 차량의 궤도 패턴을 분류하여 교차로를 통과한다. 이러한 자원예약과 궤도계획을 DP(dynamiac programming)기법과 ACO(ant colony optimization)기법으로 차량을 제어하는 사례연구에 대해 분석한다. 본 기법은 차량에게 중요도를 부여하거나 속도를 조절하여 상황에 맞게 합리적으로 기법을 향상시킬 수 있다.

• 디지털산업정보학회논문지
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• 제14권1호
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• pp.15-25
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• 2018

ISO/IEC 15118 is a standard for communications and services for electric vehicle charging infrastructure. Although this standard deals only with data communication between an electric vehicle and a charge station, communication with the outside is essential for establishing an authentication system for vehicle certification and V2G service for electric power transmission. In this study, it was designed to verify the information of electric car charging infrastructure in electric power system through communication link between ISO/IEC 15118 electric vehicle model and IEC 61850 standard MMS protocol. This is demonstrated in the field so that the electric vehicle communication data is linked with the micro grid management system. This could be used as an element technology in other distributed power sources as well as electric cars in the future.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2007년도 추계 종합학술대회 논문집
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• pp.193-196
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• 2007

최근 무선 통신 기술과 초소형화 기술의 진보로 지능형 센서 (smart sensor)를 이용한 무선 센서 네트워크의 구축이 가능해 졌으며 무선 센서 네트워크를 우리 생활 전반에 걸친 다양한 분야에 응용하려는 연구가 활발하게 진행되고 있다[1]. 본고에서는 무선 센서 네트워크의 응용분로서 무선센서노드를 활용한 캠퍼스 차량 관리 시스템 구축 방안에 대하여 기술하였다. 이를 위하여 무선센서노드의 전송전력제어 및 개별 노드 인식 방안을 고찰하였으며 실제 적용 시스템의 구성 및 동작 절차를 제안하였다.