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오광석,손권,최경현,Oh, Kwangseok,Son, Kwon,Choi, Kyunghyun 대한기계학회 2002 大韓機械學會論文集A Vol.26 No.5
Visual effects are important cues for providing occupants with virtual reality in a vehicle simulator which imitates real driving. The viewpoint of an occupant is sensitively dependent upon the occupant's posture, therefore, the total human body motion must be considered in a graphic simulator. A real-time simulation is required for the dynamic analysis of complex human body motion. This study attempts to apply a neural network to the motion analysis in various driving situations. A full car of medium-sized vehicles was selected and modeled, and then analyzed using ADAMS in such driving conditions as bump-pass and lane-change for acquiring the accelerations of chassis of the vehicle model. A hybrid III 50%ile adult male dummy model was selected and modeled in an ellipsoid model. Multibody system analysis software, MADYMO, was used in the motion analysis of an occupant model in the seated position under the acceleration field of the vehicle model. Acceleration data of the head were collected as inputs to the viewpoint movement. Based on these data, a back-propagation neural network was composed to perform the real-time analysis of occupant motions under specified driving conditions and validated output of the composed neural network with MADYMO result in arbitrary driving scenario.
제어 입력 기반 예측된 종방향 속도를 이용하는 자율주행 자동차의 차선 변경을 위한 모델 예측 조향 제어 알고리즘
오광석(Kwangseok Oh),오세찬(Sechan Oh) 한국자동차공학회 2021 한국 자동차공학회논문집 Vol.29 No.7
Steering control when changing lanes involving autonomous vehicles is the most important task of autonomous driving for driving strategy and safety. This paper presents a model predictive steering control algorithm for changing lanes among autonomous vehicles by using a control input that is based on predicted velocity. Two model predictive control algorithms have been designed for longitudinal and lateral autonomous driving with physical constraints. The model predictive longitudinal controller computes optimal longitudinal accelerations that use relative information between subject and preceding vehicles. Based on the optimal accelerations from the longitudinal controller, longitudinal velocities have been predicted, and the predicted velocities have been used to compute the optimal steering angle for changing lanes through a model predictive controller. The proposed model predictive control algorithms for lane change behavior have been constructed in a Matlab/Simulink environment. A performance evaluation has been conducted by using a commercial software(CarMaker) to ensure reasonable evaluation under variable lane change conditions of the subject vehicle.
주행 및 작업성능 통합 시뮬레이션을 위한 휠로더 동역학 모델의 개발
오광석(Kwangseok Oh),김학구(Hakgoo Kim),윤승재(Seungjae Yun),고경은(Kyungeun Ko),김판영(Panyoung Kim),이경수(Kyongsu Yi) 한국자동차공학회 2012 한국자동차공학회 학술대회 및 전시회 Vol.2012 No.11
This paper presents a 3D dynamic simulation model of a wheel loader. The objective of development of the wheel loader dynamic simulation model is to test the performance of the Wheel loader under both working and driving conditions by simulation. The wheel loader dynamic simulation model consists of 3 parts: Vehicle powertrain module, Hydraulic module for working and steering, and Vehicle dynamic module. Vehicle powertrain module consists of engine, torque converter and transmission, and Hydraulic module consists of pump, valve, cylinder and attachments. 3D dynamic simulation module is based on vehicle dynamics and multi-body (front and rear bodies) dynamic analysis method. Front and rear bodies are connected by pin in the center of steering system. Action/reaction forces and moments applied to the pin are calculated by solving front/rear dynamic simultaneous equations. Forces and moments at the pin are considered to analyze how they have an effect on the dynamics of wheel loader. The wheel loader dynamic simulation model is verified through real measurement, and it is shown that proposed dynamic simulation model can represent actual dynamics of wheel loader.
주행 안정성 향상을 위한 모델 예측 제어 기반 4WD 차량의 후륜 토크벡터링 알고리즘
오광석(Kwangseok Oh),박관우(Kwanwoo Park),이지수(Jisoo Lee),윤재민(Jaemin Yun) 한국자동차공학회 2018 한국 자동차공학회논문집 Vol.26 No.6
This paper describes a model predictive control based rear wheel torque vectoring algorithm of a 4WD vehicle for improving the driving stability. The model predictive control algorithm has been used to compute the optimal longitudinal tire forces of rear-left and rear-right wheels based on the linearized error dynamics. The used error dynamic model has been derived from the planar vehicle dynamic model that was represented by longitudinal, lateral, and yaw dynamics. In order to compute the reasonable optimal tire forces, dynamic physical constraints(e.g., tire force limit and change rate limit of tire force) have been applied to the model predictive control algorithm. Based on the computed optimal tire forces of the rear wheels, the torque distribution ratio between the rear-left wheel and rear-right wheel of the vehicle has been computed based on the wheel dynamics. The yaw rate in a steady state has been used as a reference value for improving the driving stability. The use of the proposed model predictive torque vectoring algorithm can bring about not only good torque distribution, but also sound driving stability. For the performance evaluation, simulation studies with the proposed torque vectoring algorithm have been conducted on Matlab/CarSim environment under various driving conditions, such as step steer, double lane change, and high speed avoidance. The simulation results showed that the proposed model predictive torque vectoring algorithm produced both reasonable torque distribution and good driving stability.
오광석(Kwangseok Oh),김학구(Hakgu Kim),고경은(Kyungeun Ko),김판영(Panyoung Kim),이경수(Kyongsu Yi) 대한기계학회 2014 大韓機械學會論文集A Vol.38 No.11
본 논문에서는 가상의 V상차 작업을 위한 이벤트 기반의 휠로더 운전자 모델을 개발하였다. 운전자 모델 개발의 목적은 휠로더의 일반적인 작업인 V상차 작업 시 동역학적 해석과 작업성능을 가상의 시뮬레이션 모델과 운전자 입력을 이용해 예측 및 평가하는 것이다. V상차 작업은 4단계로 이루어져 있으며, 총 8 개의 이벤트로 인해 순차적으로 작업이 진행된다. 개발된 3D 휠로더 시뮬레이션 모델은 Matlab/Simulink 환경에서 구성 되었으며, 시뮬레이션 결과는 V상차 작업의 실차 데이터와 비교 되었다. 본 연구에서 개발된 운전자 모델로 향후 가상의 V상차 작업에 대한 작업성능 및 동역학적 해석이 가능할 것으로 본다. This paper presents the development of an event-based operator model of a wheel loader for virtual V-pattern working. The objective of this study is to analyze the performance and dynamic behavior of the wheel loader for a typical V-pattern. The proposed typical V-pattern working is divided into four stages. The developed operator model is based on eight events, and the operator"s inputs are occurred sequentially by event. A 3D dynamic simulation model of the wheel loader is developed and used to analyze the dynamic behavior during working, and the simulation results are compared with the experimental data of V-pattern working. The proposed 3D dynamic simulation model and operator model are constructed using MATLAB/Simulink. The proposed operator model for V-pattern working is expected to enable evaluation of the working performance and dynamic behavior of the wheel loader.
슬라이딩 모드 관측기를 이용한 자율주행 자동차의 모델 기반 고장 검출 및 강건 조향 제어 알고리즘
오광석(Kwangseok Oh),이경수(Kyongsu Yi) 한국자동차공학회 2017 한국 자동차공학회논문집 Vol.25 No.6
This paper describes a model-based fault detection and robust steering control algorithm for autonomous vehicles using sliding mode observers. The proposed fault detection and robust steering control algorithm is based on a bicycle model and design of sliding mode observers. The steering input that includes a fault signal has been reconstructed based on the sliding mode observer in order to detect the fault signal component with the fault signal having been reconstructed for robust control. Use of the sliding mode observer can bring not only good fault reconstruction performance but also sound robust control performance. Moreover, it is shown that the reconstructed fault and actual fault are nearly the same shape. To evaluate the performance of the proposed algorithm, path tracking simulation studies with the model predictive control algorithm have been conducted under various driving conditions. The simulation results show that the proposed model-based fault detection and robust control algorithm indeed results in both good fault detection and sound robust control performance.