전동식 과급시스템을 이용한 HEV전용 고효율/고성능 밀러싸이클 엔진 연구

홍승우(Seungwoo Hong),한동희(Donghee Han),이관희(Kwanhee Lee),강현진(Hyunjin Kang),김재헌(Jaehun Kim),구자언(Jaeon Gu),임종석(Jongsuk Lim),박한용(Hanyong Park),김도완(Dowan Kim),팽용석(Yongsuk Pang),박귀열(Guiyeol Park) 한국자동차공학회 2020 한국자동차공학회 부문종합 학술대회 Vol.2020 No.7

A Miller Cycle engine based on a hybrid electric vehicle (HEV) dedicated boosting system, working in great synergy with a HEV abundant in electric power capacity, has been studied to improve the efficiency and performance of the HEV. Conventional turbocharged boosting system in an internal combustion engine dedicated vehicle grants fuel economy benefits thanks to engine downsizing. In a HEV, an electric motor governs the operating region of the engine, limiting the fuel economy benefits of said downsizing approach. Moreover, turbocharging reduces exhaust energy for the catalytic converter while increasing the back pressure, leading to adverse effects on emissions and fuel economy. This paper discusses the HEVdedicated Miller Cycle engine, which can boost the intake pressure without increasing the back pressure. In addition, the energy of the exhaust gas can be used in its entirety for the catalytic converter, thus favorable for emission reduction. An intake manifold integrated with a water-cooled intercooler was used, lowering the volumetric efficiency while realizing high charge cooling effects. The HEV-dedicated Miller Cycle engine was tested in a vehicle for fuel consumption in various drive cycles. In comparison to the base HEV, a similar level of fuel economy was achieved for the FTP-75 and HWFET combined drive cycle. For the more aggressive US-06 drive cycle, a 4.1% fuel economy improvement was realized. Furthermore, a 20% improvement in vehicle dynamic performance was observed in various conditions; a result of both engine output increase by the HEV-dedicated boosting system and the fast response of the electric supercharger.

승용디젤엔진 EGR 및 VGT 제어시스템의 동적특성을 고려한 Decoupler 설계 연구

홍승우(Seungwoo Hong),박인석(Inseok Park),손정원(Jeongwon Sohn),선우명호(Myoungho Sunwoo) 한국자동차공학회 2014 한국 자동차공학회논문집 Vol.22 No.2

This paper proposes a decoupler design method to reduce interaction between exhaust gas recirculation (EGR) and variable geometry turbocharger (VGT) systems in passenger car diesel engines. The EGR valve and VGT vane are respectively used to control air-to-fuel ratio (AFR) of exhaust gas and intake pressure. A plant model for EGR and VGT systems is defined by a first order transfer function plus time-delay model, and the loop interaction between these systems is analyzed using a relative normalized gain array (RNGA) method. In order to deal with the loop interaction, a design method for simplified decoupler is applied to this study. Feedback control algorithms for AFR and intake pressure are composed of a compensator using PID control method and a prefilter. The proposed decoupler is evaluated through engine experiment, and the results successfully showed that the loop interaction between EGR and VGT systems can be reduced by using the proposed decoupler. Furthermore, it presents stable performance even off from the designed operating point.

승용디젤엔진의 과도구간 입자상물질 저감 및 운전성능 향상을 위한 연료분사량 및 커먼레일압력 제어전략

홍승우(Seungwoo Hong),정동혁(Donghyuk Jung),선우명호(Myoungho Sunwoo) 한국자동차공학회 2015 한국 자동차공학회논문집 Vol.23 No.6

This study proposes a control strategy of the common rail pressure with a fuel injection limitation algorithm to reduce particulate matter (PM) emissions under transient states. The proposed control strategy consists of two parts: injection quantity limitation and rail pressure adaptation. The injection limitation algorithm determines the maximum allowable fuel injection quantity to avoid rich combustion under transient states. The fuel injection quantity is limited by predicting the burned gas rate after combustion; however, the reduced injection quantity leads to deterioration of engine torque. The common rail pressure adaptation strategy is designed to compensate for the reduced engine torque. An increase of the rail pressure under transient states contributes to enhancement of the engine torque as well as reduction of PM emissions by promoting atomization of the injected fuel. The proposed control strategy is validated through engine experiments. The rail pressure adaptation reduced the PM emission by 5-10% and enhanced the engine torque up to 2.5%.

지문 영상 품질을 고려한 WSQ 최대 압축

홍승우(Seungwoo Hong),이성주(Sungju Lee),정용화(Yongwha Chung),최우용(Wooyong Choi),문대성(Daesung Moon),문기영(Kiyoung Moon),김장룡(Changlong Jin),김학일(Hakil Kim) 한국정보보호학회 2010 정보보호학회논문지 Vol.20 No.3

지문 인식 시스템이 보편화되면서 출입국 관리 등 국가 단위의 대규모 시스템 구축이 활발히 논의되고 있다. 이러한 대규모 지문 인식 시스템의 효율적인 자원 활용을 위해 영상 압축 성능을 향상시키는 방법이 연구되고 있다. 본 논문에서는 지문 영상 압축 표준인 FBI WSQ(Wavelet Scalar Quantization)의 압축 성능을 극대화하기 위한 최대 압축비 결정 방법을 제안한다. 지문 영상 압축을 고려하지 않는 기존 지문 영상 품질 평가 방법의 단점을 해결하기 위해, 지문 영상 품질 점수와 FBI WSQ 압축 인자가 인식률에 미치는 영향을 분석한다. 또한, 회귀분석 방법으로 영상 압축의 영향까지 고려한 인식률 예측 모델을 추정하고, 입력으로 주어진 최저 지문 인식률 조건을 만족하는 최대 압축비를 도출한다. 제안 방법의 정당성을 확인하기 위해 FVC2004의 DB1 지문 영상 데이터베이스로 실험하였으며, 인식률의 큰 저하 없이 기존의 FBI WSQ 권장 압축비 대비 약 3배의 압축 성능 향상을 확인하였다. Compression techniques can be applied to large-scale fingerprint systems to store or transmit fingerprint data efficiently. In this paper, we investigate the effects of FBI WSQ fingerprint image compression on the performance of a fingerprint verification system using multiple linear regressions. We propose a maximum compression using fingerprint image quality score. Based on the experiments, we can confirm that the proposed approach can compress the fingerprint images up to 3 times more than the fixed compression ratio without significant degradation of the verification accuracy.

한글 어절 맞춤법 오류 검출을 위한 형태소 분석기

홍승우(SeungWoo Hong),이종연(JongYun Lee),오상헌(SangHun Oh) 한국정보과학회 1993 한국정보과학회 학술발표논문집 Vol.20 No.2

본 논문은 한글어절에 대해 언어 정보를 이용하여 맞춤법 오류가 일어난 어절을 검출하기 위한 형태소 분석기의 설계 및 구현에 관해 기술한다. 본 논문에서 제안하는 형태소 분석기는 문자 인식 시스템으로부터 입력 어절에 대하여 단어의 기본형만을 수록한 사전 정보를 이용하여 입력어절을 형태소 단위로 분리한다. 불규칙 변이가 일어난 입력어절은 사전에는 형태소의 기본형만을 수록하고 원형복구 알고리즘을 적용하여 형태로소를 추출하고 각 형태소의 결합관계를 검사하여 어절의 맞춤법 오류를 검출한다. 형태소 분석기에서 분석된 결과는 어절에 오류의 존재 여부를 결정하여 이를 언어의 구조적 정보를 이용하여 오인식을 교정하는 오인식 교정단계에 제공된다.

러프집합이론을 중심으로 한 감성 지식 추출 및 통계분석과의 비교 연구

홍승우(Seungwoo Hong),박재규(Jaekyu Park),박성준(Sungjoon Park),정의승(Eui S. Jung) 대한인간공학회 2010 大韓人間工學會誌 Vol.29 No.4

The aim of affective engineering is to develop a new product by translating customer affections into design factors. Affective data have so far been analyzed using a multivariate statistical analysis, but the affective data do not always have linear features assumed under normal distribution. Rough sets model is an effective method for knowledge discovery under uncertainty, imprecision and fuzziness. Rough sets model is to deal with any type of data regardless of their linearity characteristics. Therefore, this study utilizes rough sets model to extract affective knowledge from affective data. Four types of scent alternatives and four types of sounds were designed and the experiment was performed to look into affective differences in subject's preference on air conditioner. Finally, the purpose of this study also is to extract knowledge from affective data using rough sets model and to figure out the relationships between rough sets based affective engineering method and statistical one. The result of a case study shows that the proposed approach can effectively extract affective knowledge from affective data and is able to discover the relationships between customer affections and design factors. This study also shows similar results between rough sets model and statistical method, but it can be made more valuable by comparing fuzzy theory, neural network and multivariate statistical methods.

서비스 품질 보장을 위한 통합 전달 시스템

윤지욱,홍승우,이종현,염경환,Youn JiWook,Hong SeungWoo,Lee JongHyun,Yeom KyungWhan 대한전자공학회 2005 電子工學會論文誌-TC (Telecommunications) Vol.42 No.12

본 논문에서는 이더넷 패킷에 대한 서비스 품질을 보장할 수 있는 통합전달 시스템을 설계 및 구현하였다. 구현된 통합전달 시스템은 하나의 장치에서 MPLS 기반의 L2 VPN 서비스, 프리미엄 멀티미디어 서비스 및 TDM 전용회선 서비스를 동시에 제공할 수 있다. 제안된 통합전달 시스템은 VCG로 구성된 채널별로 QoS 정책을 설정하고 그 용량을 제어할 수 있기 때문에 기존의 이더넷 시스템에서는 가질 수 없었던 높은 신뢰성을 제공할 수 있어 고 품질 실시간 서비스 제공이 가능하다. 구현된 시스템의 성능 실험은 3노드로 구성된 링 네트워크에서 성공적으로 수행되었다. We propose and design a fully conversed Ethernet and TDM transport system to guarantee qualify of service for Ethernet packet. Developed convergence system can support not only L2 VPN service and premium multimedia service based on MPLS protocol but also TDM leased line service, simultaneously. Developed convergence system has the advantage of providing high reliability that realizes high-quality and real time communications due to assign QoS profile and guarantee bandwidth per channel consist of VCGs without affect adjacent channels. Evaluation for proposed system was successfully performed within the ling network.

치과적 중재가 장병 금연 성공률에 미치는 영향 연구

홍진선 ( Jinson Hong ),최정인 ( Jungin Choi ),전한가람 ( Hangaram Jeon ),강인순 ( Insoon Kang ),홍승우 ( Seungwoo Hong ),박아름 ( Areum Park ) 국군의무사령부 2018 대한군진의학학술지 Vol.49 No.1

Objectives; The objective of this study was to evaluate the effect of the dental intervention effects on success of smoking-cessation for military soldiers. Methods; A dental intervention including periodontal management and oral health care program has combined with conventional smoking-cessation program in the Armed Forces Busan Hospital. An advanced smoking-cessation program was provided at every visit. Hydrogen sulfide(H2S) and methyl mercaptan(CH3SH) concentration for halitosis evaluation were measured at the each consecutive visit using Twin Breasor II. Results; Dental intervention effect on success of regular smoking-cessation was verified for this study. Quantitative approach for halitosis evaluation was introduced. Hydrogen sulfide(H2S) and methyl mercaptan(CH3SH) concentration level has decreased after stop smoking. Conclusions; It is recommended that broader and long-term study is necessary to evaluate the dental intervention effects on success of smoking-cessation

동기 발전기 등가회로를 이용한 얼터네이터 토크 모델 설계

손정원(Jeongwon Sohn),홍승우(Seungwoo Hong),이현준(Hyunjun Lee),이주원(Joowon Lee),이민광(Minkwang Lee),선우명호(Myoungho Sunwoo) 한국자동차공학회 2012 한국자동차공학회 부문종합 학술대회 Vol.2012 No.5

This paper presents the alternator torque model derived from an equivalent circuit of synchronous generator. The model is designed to simulate the automotive alternator operated on various conditions. It reflects the torque variation mainly caused by dynamic characteristics such as engine speed, load current, and target voltage. The alternator torque works as the engine load directly, thus the model can be used for the establishment of energy management strategies. In this paper, a research case of the alternator generation control is introduced to validate a model application. The simulation result shows the model is applicable for the variety of energy management researches.

날씨를 고려한 딥러닝 기반의 개별 가구 에너지 사용 요금 예측

박지수(Jisoo Park),홍승우(Seungwoo Hong),서일홍(Il-hong Suh) 대한전자공학회 2020 전자공학회논문지 Vol.57 No.4

에너지 사용 요금은 가계의 고정적인 지출 항목 중 하나로써, 특히 날씨로 인해 에너지 사용이 급증하는 시기에는 높은 누진율이 적용되어 가계 부담을 키우고 있다. 이에 소비자는 합리적인 에너지 사용을 필요로 하는데, 이를 위해서는 소비자가 고지될 에너지 사용 요금을 사전에 예측하고, 그에 따라 에너지 사용을 조절할 수 있어야 한다. 따라서 본 논문은 딥러닝 기반의 모델을 이용하여 에너지 요금 예측에 큰 영향을 미치는 날씨를 고려한 개별 가구의 월 에너지 사용 요금 예측 방법을 제안하였다. 날씨 정보로는 실험적으로 유의미한 성능 향상을 보인 최저기온, 최고기온, 강수확률, 강수량, 습도, 풍속, 적설량, 전운량이 사용되었으며, 대표적인 딥러닝 기반의 세 가지 모델들(Multilayer Perceptron, Convolution Neural Network, Long-Short Term Memory)을 주어진 문제에 맞게 설계 및 구현하여 Long-Short Term Memory 기반의 모델이 가장 적은 오차를 보이는 것을 확인하였다. 또한, 이러한 결과를 바탕으로 본 논문에서 제안한 방법을 실제 2,234가구의 에너지 사용량 데이터와 기상청의 날씨 데이터에 적용하였을 때 평균 5,110원이라는 작은 오차로 개별 가구의 에너지 사용 요금 예측이 가능함을 실험적으로 입증하였다. Energy bills are one of the household"s fixed expenses. In particular, when energy consumption is soaring due to weather conditions, a progressive rate is applied, which raises household burden. Therefore, consumers need to be rational in their energy use, and for this, they must be able to predict energy expenditure and adjust the energy use accordingly. To this end, in this paper, we propose a prediction method of the monthly energy bill for individual households using a deep-learning-based model, considering the weather, which has an important effect on energy bill prediction. As weather information, minimum temperature, maximum temperature, precipitation probability, precipitation, humidity, wind speed, snow level, and cloud cover are used, which shows an experimentally significant performance improvement. Also, three representative deep learning models (Multilayer Perceptron, Convolution Neural Network, Long-Short Term Memory) are designed and implemented for the given problem, and the model based on Long-short term memory exhibits the lowest error. The proposed method based on these results is applied to the actual energy usage data of 2,234 households and weather data of the Korea Meteorological Administration. The experiment shows that the energy bills of individual households can be predicted with a small average error of 5,110 won (4.28 dollars when the Korean won to the U.S. dollar exchange rate is 1,194 won per dollar) using the proposed approach.