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강연식(Yeonsik Kang),이홍우(Hongwoo Lee),김재현(Jaehyun Kim),정경환(Kyunghwan Chung),이현영(Hyunyoung Lee),남재복(Jaebok Nam) 한국자동차공학회 2012 한국자동차공학회 학술대회 및 전시회 Vol.2012 No.11
POSCO developed a new body concept for electric vehicle (PBC-EV, POSCO Body Concept ? Electric Vehicle) with the aim to identify requirements of new steel grades for electric vehicle and to provide cost efficient steel solutions to customer. The objectives are achieved by advanced steel technologies and engineering design optimization with the best attributes of steel ? its design flexibility, strength, formability and low manufacturing cost. PBC-EV features steel body structure designs that reduce weight to 218kg by 26 percent over a benchmark body of 296kg. The weight reduction has been realized through the use of advanced high strength steel grades by 65% of total body weight. The steel grades include TWIP, 2Gipa grade HPF steels as well as DP, CP and TRIP steels. A number of steel application technologies were also adopted to take the benefit of advanced steels. New forming technologies such as tailored hot press forming and multi-directional roll forming were applied as well as conventional manufacturing methods. Even though there is a cost premium associated with the use of higher grade steels, the consequently achieved weight savings and the optimal use of forming process minimize the overall cost increase of manufacturing and assembly. The total life cycle emission of PBC-EV is reduced by nearly 50 percent comparing to the benchmark internal combustion engine vehicle. These are accomplished while meeting a broad list of global safety requirements such as US FMVSS, IIHS and EuroNCAP. No damage of battery cell in the crash simulations is observed. In the last stage hardware demonstration was done by building BIWs (Body-in-White) excluding opening parts and fenders. It is very important for automakers to avoid unintended consequences by using eco-friendly steel technologies for advanced powertrain vehicle. With this project advanced steel solutions which are not only lighter and safer but greener can be provided to automakers.
NO<sub>X</sub> 및 NH<sub>3</sub> Slip 저감을 위한 Urea-SCR 제어기반 모델 개발 및 검증
이승근,이성욱,강연식,Lee, Seung Geun,Lee, Seang Wock,Kang, Yeonsik 대한기계학회 2015 大韓機械學會論文集B Vol.39 No.1
디젤 자동차의 점점 강화되는 $NO_X$ 배기가스 규제를 만족하기 위해서는 화학공학 기반의 SCR 반응모델을 사용한 모델기반 제어 알고리즘 개발이 필요하다. 본 연구에서는 소형 경유차량을 대상으로 $NO_X$ 를 저감하기 위한 배기 후처리 시스템 모델을 설계하기 위하여 SCR 시스템 모델링과 Rig 실험 및 Matlab 을 이용하여 시뮬레이션 및 검증을 하였다. SCR Rig 실험은 디젤엔진에서 배출되는 배기가스와 같은 성분의 모사가스를 생성하여 공간속도와 온도의 변화에 의한 SCR 의 $NO_X$ 저감효율에 대한 실험 조건 및 데이터를 획득하였다. 또한, 제안된 모델은 Rig 실험에서 사용한 실험조건과 결과데이터를 이용하여 Matlab 을 통해 검증하였으며 시뮬레이션 시 필요한 모델의 파라미터 값들은 실험데이터를 기반으로 최적화하였다. To satisfy stricter $NO_X$ emission regulations for light- and heavy-duty diesel vehicles, a control algorithm needs to be developed based on a selective catalytic reaction (SCR) dynamics model for chemical reactions. This paper presents the development and validation of a SCR dynamics model through test rig experiments and MATLAB simulations. A nonlinear state space model is proposed based on the mass conservation law of chemical reactions in the SCR dynamics model. Experiments were performed on a test rig to evaluate the effects of the $NO_X$ and $NH_3$ concentrations, gas temperature, and space velocity on the $NO_X$ conversion efficiency for the urea-SCR system. The parameter values of the proposed SCR model were identified using the experimental datasets. Finally, a control-oriented model for an SCR system was developed and validated from the experimental data in a MATLAB simulation. The results of this study should contribute toward developing a closed-loop control strategy for $NO_X$ and $NH_3$ slip reduction in the urea-SCR system for an actual engine test bench.
날씨인식 결과를 이용한 GPS와 비전센서기반 하이브리드 방식의 태양추적 시스템 개발
유정재(Jeongjae Yoo),강연식(Yeonsik Kang) 제어로봇시스템학회 2014 제어·로봇·시스템학회 논문지 Vol.20 No.5
It is well known that solar tracking systems can increase the efficiency of exiting solar panels significantly. In this paper, a hybrid solar tracking system has been developed by using both astronomical estimates from a GPS and the image processing results of a camera vision system. A decision making process is also proposed to distinguish current weather conditions using camera images. Based on the decision making results, the proposed hybrid tracking system switches two tracking control methods. The one control method is based on astronomical estimates of the current solar position. And the other control method is based on the solar image processing result. The developed hybrid solar tracking system is implemented on an experimental platform and the performance of the developed control methods are verified.
서승범(SeungBeum Suh),강연식(Yeonsik Kang),노치원(Chi-Won Roh),강성철(Sung-Chul Kang) 제어로봇시스템학회 2009 제어·로봇·시스템학회 논문지 Vol.15 No.5
Autonomous Lane detection with vision is a difficult problem because of various road conditions, such as shadowy road surface, various light conditions, and the signs on the road. In this paper we propose a robust lane detection algorithm to overcome shadowy road problem using a statistical method. The algorithm is applied to the vision-based mobile robot system and the robot followed the lane with the lane following controller. In parallel with the lane following controller, the global position of the robot is estimated by the developed localization method to specify the locations where the lane is discontinued. The results of experiments, done in the region where the GPS measurement is unreliable, show good performance to detect and to follow the lane in complex conditions with shades, water marks, and so on.
비선형 모델예측제어 데이터에 기반한 실시간 심층 인공신경망 자율주행 제어기법 개발
이택규(Taekgyu Lee),강연식(Yeonsik Kang) 제어로봇시스템학회 2020 제어·로봇·시스템학회 논문지 Vol.26 No.5
In this paper, a vehicle control method was developed based on a deep artificial neural network using the closed-loop simulation results of a nonlinear model predictive controller for its training set. The nonlinear model predictive controller had the potential for real-time application due to its unpredictable computation time. Therefore, we developed an artificial neural network controller that showed a performance similar to the nonlinear model predictive control method, but had better real-time capability. The performance of the developed control method was verified through simulations with complex reference trajectories, including obstacles. Although thetrajectory tracking performance of the developed method was similar with nonlinear model predictive control, the computation time was improved significantly, which showed the feasibility of this method in real-time applications.
승용디젤엔진 배기가스 규제 대응을 위한 슬라이딩모드 관측기 기반 Urea-SCR 제어기 개발
이승근(Seunggeun Lee),강연식(Yeonsik Kang) 한국자동차공학회 2013 한국자동차공학회 부문종합 학술대회 Vol.2013 No.5
This paper presents the development and validation of a model of SCR(Selective Catalytic Reduction) dynamics, sliding mode observer and adaptive control algorithm through simulations. In order to achieve high NOX conversion and low NH₃ slip, this work presents an adaptive control strategy that uses SCR system and sliding mode observer. Proposed observer can replace such a NH₃ sensor and be used for SCR catalyst NH₃ coverage ratio control. The stability of the observer was validated by simulations. Then, adaptive control strategy that control NH₃ coverage ratio and NH₃ slip was applied to SCR dynamic system and validated by simulation. The results of this study should contribute toward developing a closed-loop control strategy for urea-SCR systems for light-duty vehicles.
지능형 차량을 위한 최적화기반 긴급 충돌 회피 제어 알고리즘 개발
최철호(Chulho Choi),강연식(Yeonsik Kang) 한국자동차공학회 2011 한국자동차공학회 학술대회 및 전시회 Vol.2011 No.11
This paper presents collision avoidance maneuver based on a model predictive control method which can control vehicles velocity and steering angle simultaneously. Collision avoidance maneuver that didn"t consider vehicle dynamics may not avoid obstacle or can be damaged by other causes. In this paper, collision avoidance maneuver is designed to consider limitation of maximum steering and maximum acceleration with vehicle dynamics. With vehicle kinematic model, NMPC predicts vehicle position next N time steps later trom present and calculates error that composes cost function fram desired line. NMPC calculJates control input which minimizes this cost function. The performance of proposed collision avoidance maneuver is tested on the simulation with stationary vehicle collision avoidance scenario.