This paper defines structural and dynamic analysis of a crane used for electric passenger vehicle fire scenarios. The crane model used in the study has a working radius of 9 meters, and under extreme conditions measured with real-world usage in mind, the load at the boom tip is 24.5kN. The boom is assumed to be made of ATOS80, and the pads are assumed to be made of Monomer Casting Nylon. Structural analysis was conducted based on the crane's materials and configuration, and dynamic analysis was performed by dividing the grab method into gripper and hinge types. In the structural analysis, the maximum stress increased as the telescopic boom faced upwards. In the dynamic analysis, the gripper type facing downward showed more stable stress. For the model with an added badge, the structural analysis showed an increase in maximum stress, but the value was negligible, and the maximum stress of the telescopic boom decreased in the dynamic analysis. Based on the analysis results, the suitable materials for the crane are ATOS80 for the lower articulated boom and the telescopic boom, and DOMEX1300 for the upper articulated boom. The gripper type grab method is more stable than the hinge type.

정부에서는 수송부분에서 발생하는 온실가스 감축을 위해 친환경자동차 구매보조금 지급, 개별소비세 감면, 취득세 감면 등의 정책 을 시행함으로 친환경자동차 등록대수는 매년 증가하고 있는 추세이다. 충전 수요에 따른 전기차 충전소 구축을 진행하고 있으나 충 전소 구축이 충전수요 대비 부족하여 충전관련 민원과 이용자들의 불편이 발생하고 있는 실정이다. 하지만 충전소 설치 시 소모되는 재화, 부지 등의 비용을 지속적으로 투입하기에는 한계가 있어 최대효과를 발생시키는 지역에 충전소를 설치하는 방법과 기존 충전소 를 효과적으로 이용하는 방안에 대한 중요성이 대두되고 있다. 따라서 본 연구에서는 급속충전소가 설치 되지 않았다는 가정하에 전 기차 급속충전소 최적입지를 도출하여 실제 충전소 입지와 최적입지를 비교하여 입지적정성을 분석하고, 최적입지에 입지한 충전소와 입지하지 않은 충전소의 충전량을 비교하여 도출된 최적입지의 충전효율성을 검증하고자 한다. 급속충전소 최적입지 선정에는 교통량 을 이용하였으며, 교통량을 “QGIS 생활 SOC 입지분석 툴킷”에 변수로 설정하여 급속충전소 접근성에 따른 최적입지를 1~10등급으로 나누어 도출하였다. 각 등급에 위치한 실제 충전소의 입지적정성을 평가하고 충전소별 충전량을 수집하여 비교하였다. 충전소 입지 등 급과 교통량간의 상관성을 확인하였다.

PURPOSES : This study is conducted to evaluate the development of materials for extinguishing ESS(Energy Storage System) fires in electric vehicles using industrial byproducts. METHODS : Grout containing an appropriate amount of fly ash, silica fume, blast furnace slag powder, and ferronikel slag, which are industrial byproducts, was prepared. The fluidity, stress, and mechanical properties were evaluated in accordance with standard test methods. RESULTS : The fluidity of the materials used for the evolution of ESS fires differed depending on the material of the industrial byproducts. In the case of blast furnace slag, its fluidity is low owing to viscosity even when it content is high, and the use of ferronikelsrag is shown to be suitable for the evolution of ESS fires in fluidity and curing tests. CONCLUSIONS : Fire-extinguishing materials using industrial byproducts require a long curing time but exhibit the fluidity required for ESS fire extinguishment. In particular, the curing and fluidity of Peronikel slag and fly ash are suitable for ESS fire extinguishing.

It is highly challenging to measure the efficiency of electric vehicle charging stations (EVCSs) because factors affecting operational characteristics of EVCSs are time-varying in practice. For the efficiency measurement, environmental factors around the EVCSs can be considered because such factors affect charging behaviors of electric vehicle drivers, resulting in variations of accessibility and attractiveness for the EVCSs. Considering dynamics of the factors, this paper examines the technical efficiency of 622 electric vehicle charging stations in Seoul using data envelopment analysis (DEA). The DEA is formulated as a multi-period output-oriented constant return to scale model. Five inputs including floating population, number of nearby EVCSs, average distance of nearby EVCSs, traffic volume and traffic congestion are considered and the charging frequency of EVCSs is used as the output. The result of efficiency measurement shows that not many EVCSs has most of charging demand at certain periods of time, while the others are facing with anemic charging demand. Tobit regression analyses show that the traffic congestion negatively affects the efficiency of EVCSs, while the traffic volume and the number of nearby EVCSs are positive factors improving the efficiency around EVCSs. We draw some notable characteristics of efficient EVCSs by comparing means of the inputs related to the groups classified by K-means clustering algorithm. This analysis presents that efficient EVCSs can be generally characterized with the high number of nearby EVCSs and low level of the traffic congestion.

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.

In this study, the deformation of friction stir welding on the aluminum battery housing material(AL6063-T5) applied to the electric vehicle was effectively predicted through experiments and numerical simulations. The temperature data were measured during the friction stir welding experiment, and the numerical simulation was carried out using the experimental temperature data. In the heat transfer analysis, the temperature distribution of the structure over time was calculated using the Reynolds equation. The final friction stir welding deformation was calculated by performing the structural analysis using the calculated temperature distribution data over time. The thermal elasto-plastic analysis was performed according to the friction stir welding process conditions and the welding sequences. Finally, the optimum welding condition was derived that the welding speed is 1000 mm/min and the rotation speed of the tool is 2000 RPM.

Excellent plastic moldings is possible through optimization of many molding parameters. In particular, the deformation of a plastic part is affected by various factors during molding. Therefore, it is very important to select the optimum molding conditions that minimize the deformation of the molded part. Experimental design is used to select optimal molding conditions. In this study, the molding conditions were selected to minimize the deformation of the electric plastic plug of the electric vehicle using the Taguchi method in the experimental design method. Using the Taguchi Method, we found that the deformation of the plug moldings was reduced by about 7.2% compared to before optimization.

This research has been conducted to design upright parts of hand-made vehicles with the purpose of reducing material and machining cost while ensuring structural safety. Aluminum knuckles were modelled with three parts in order to enhance design flexibility as well as to reduce CNC machining cost. A vehicle model was constructed in CAD program and simulated in ADAMS View in order to estimate joint forces developing during 20 degree step steering condition at 60km/h. The joint forces obtained in the vehicle dynamics simulation were used for the structural analysis in ANSYS and dimensions of knuckle parts were adjusted until the lowest safety factor reached 2.0. The weight of knuckle decreased by 50% compared to the previous version that was designed without the structural analysis. The overall manufacturing cost decreased by 33% due to the reduction in the material as well as the CNC machining effort.

In South Korea, Jeju Island has a role as a test bed for electric vehicles (EVs). All conventional cars on the island are supposed to be replaced with EVs by 2030. Accordingly, how to effectively set up EV charging stations (EVCSs) that can charge EVs is an urgent research issue. In this paper, we present a case study on planning the locations of EVCS for Jeju Island, South Korea. The objective is to determine where EVCSs to be installed so as to balance the load of EVCSs while satisfying demands. For a public service with EVCSs by some government or non-profit organization, load balancing between EVCS locations may be one of major measures to evaluate or publicize the associated service network. Nevertheless, this measure has not been receiving much attention in the related literature. Thus, we consider the measure as a constraint and an objective in a mixed integer programming model. The model also considers the maximum allowed distance that drivers would detour to recharge their EV instead of using the shortest path to their destination. To solve the problem effectively, we develop a heuristic algorithm. With the proposed heuristic algorithm, a variety of numerical analysis is conducted to identify effects of the maximum allowed detour distance and the tightness of budget for installing EVCSs. From the analysis, we discuss the effects and draw practical implications.

Since the so-called diesel gates of German automobiles, interest in environmentally-friendly vehicles has been rising, among other alternatives, hydrogen-fueled electric vehicles with 0% vehicle emissions are expected to replace a significant portion of passenger cars. Here, we analyze trends of US, Europe, PCT (WO) 3-patent offices application of hydrogen-fueled electric vehicles and analyze the patent application trends of national and individual companies, the patent application trend of detailed technology through clustering analysis, technology competitiveness. The global market for hydrogen-fueled electric vehicles, which is currently only 0.01% of other alternatives, is expected to grow to several percent in 2020. Major automobile makers such as Japan, United States of America, Germany, and Korea continue to fiercely compete for eco-friendly vehicles.