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전자식 차동 제한장치를 이용한 후륜구동 차량의 횡방향 안정성 제어
차현수,이경수,Cha, Hyunsoo,Yi, Kyongsu 한국자동차안전학회 2021 자동차안전학회지 Vol.13 No.3
This paper presents a lateral stability control for rear wheel drive (RWD) vehicles using electronic limited slip differentials (eLSD). The proposed eLSD controller is designed to increase the understeer characteristic by transferring torque from the outside to inside wheel. The proposed algorithm is devised to improve the lateral responses at the steady state and transient cornering. In the steady state response, the proposed algorithm can extend the region of linear cornering response and can increase the maximum limit of available lateral acceleration. In the transient response, the proposed controller can reduce the yaw rate overshoot by increasing the understeer characteristic. The proposed algorithm has been investigated via computer simulations. In the simulation results, the performance of the proposed controller is compared with uncontrolled cases. The simulation results show that the proposed algorithm can improve the vehicle lateral stability and handling performance.
타이어 힘 추정을 위한 파라미터 최적화 파제카 모델과 인공 신경망 모델 간의 비교 연구
차현수,김자유,이경수,박재용,Cha, Hyunsoo,Kim, Jayu,Yi, Kyongsu,Park, Jaeyong 한국자동차안전학회 2021 자동차안전학회지 Vol.13 No.4
This paper presents a comparative study between the parameter-optimized Pacejka model and artificial neural network model for the tire force estimation. The two different approaches are investigated and compared in this study. First, offline optimization is conducted based on Pacejka Magic Formula model to determine the proper parameter set for the minimization of tire force error between the model and test data set. Second, deep neural network model is used to fit the model to the tire test data set. The actual tire forces are measured using MTS Flat-Track test platform and the measurements are used as the reference tire data set. The focus of this study is on the applicability of machine learning technique to tire force estimation. It is shown via the regression results that the deep neural network model is more effective in describing the tire force than the parameter-optimized Pacejka model.
차현수(HyunSoo Cha),유승화(SeungWha Yoo),김기형(Kihyung Kim),김영한(Younghan Kim),이상산(Sangsan Lee) 대한기계학회 2012 대한기계학회 춘추학술대회 Vol.2012 No.11
The past few years have witnessed increased interest in large-scale Industrial Wireless Sensor Network(WSN). General Industrial WSN consists of a large number of low-cost, low power, and short RF range sensor nodes because of the cost saving. In industrial applications, sensor nodes are statically deployed and left unattended to continuously report sensing data(e.g. temperature, pressure, and humidity) to the Base Station(BS). Therefore, energy efficiency is a key challenge in the design and operation Industrial WSN. One of the major reason for worse energy efficiency is the traffic concentration on a small number of sensor nodes. Furthermore, several applications in industrial area require the bounded delay, so the proposed scheme have to support it. In these respect, node clustering can be a efficient solution to solve energy problem and satisfy delay bound in industrial WSN. In this paper we propose a novel clustering algorithm based on information entropy.
위상 궤적을 이용한 정상상태 드리프트을 위한 제어기의 시각적 검증
차현수(Hyunsoo Cha),좌은혁(Eunhyek Joa),이경수(Kyongsu Yi) 대한기계학회 2018 대한기계학회 춘추학술대회 Vol.2018 No.12
This paper presents visual validation of drift controllers for steady-state cornering using phase portrait to show the stability of steady-state drifting of a rear wheel drive vehicle. Phase portraits are drawn to display the change in vehicle states based on the time derivative of states at each phase coordinate. Phase portraits of bicycle model without a controller show the existence and vehicle state of an unstable drift equilibrium point where the vehicle states are not sustained with the lapse of the time. With the activation of steering angle or front tire lateral force controller, phase portrait reveals the existence of a stable drift equilibrium point. Successful implementation of the controllers can be confirmed through the convergence of trajectories to the stable drift equilibria.