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- 저자 : 강영수(Yeong-Su Gang) (검색결과 4 건)
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이중 Gate를 갖는 Trench Emitter IGBT의 특성
강영수,정상구,Gang, Yeong-Su,Jeong, Sang-Gu 대한전기학회 2000 전기학회논문지C Vol.52 No.10
A dual gate trench emitter IGBT structure is proposed and studied numerically using the device simulator MEDICI. The on-state forward voltage drop latch-up current density turn-off time and breakdown voltage of the proposed structure are compared with those of the conventional DMOS-IGBT and trench gate IGBT structures. The proposed structure forms an additional channel and increases collector current level resulting in reduction of on -state forward voltage drop. In addition the trench emitter increases latch-up current density by 148% in comparison with that for the conventional DMOS-IGBT and by 83% compared with that for the trench gate IGBT without degradation in breakdown voltage when the half trench gate width(Tgw) and trench emitter depth(Ted) are fixed at $1.5\mum\; and\; 2\mum$, respectively
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손동훈(Dong-Hoon Son),강영수(Yeong-Su Gang),김화중(Hwa-Joong Kim) 한국산업경영시스템학회 2020 한국산업경영시스템학회지 Vol.43 No.3
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.
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다기간 자료포락분석을 이용한 전기차 충전소 효율성 변화 분석
손동훈(Dong-Hoon Son),강영수(Yeong-Su Gang),김화중(Hwa-Joong Kim) 한국산업경영시스템학회 2021 한국산업경영시스템학회지 Vol.44 No.2
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.
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