• Journal of the Korean Society for Railway
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• v.10 no.2 s.39
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• pp.243-250
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• 2007

In general the Maglev vehicle is run over the elevated track called guideway. Since the guideway is elevated, the flexibility of the guideway has an effect on the dynamic responses of a vehicle such as its stability and ride quality. To improve the running performance of the Maglev vehicle and design a cost effective guideway using the dynamic analysis, the dynamic analysis of the system requires the coupling model of the Maglev vehicle and guideway. A coupling model based on multibody dynamics is proposed and programmed. With the program, the UTM01, a low speed Maglev vehicle, is analyzed and discussed.

• International Journal of Automotive Technology
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• v.6 no.4
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• pp.351-357
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• 2005

Development of a real-time simulation model for high-speed and multibody tracked vehicles is difficult because they involve hundreds of highly nonlinear equations. In the development of a reliable tracked vehicle model for real-time simulation, it is helpful to use an off-line tracked vehicle model developed by considering all the degrees of freedom of each element. This paper presents a step-by-step procedure for the development of a real-time simulation model based on the off-line tracked vehicle model. The road input data, Profile IV, is used for the real time simulation and simulation results are compared with vehicle test results obtained in the military test field. It is noted that the simulation results are quite close to the test results.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.1137-1146
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• 1993

In order to analyze lateral control in the forward manuever of a tractor- trailer combination , a human operator model and a kinematic vehicle model were utilized for the operator/vehicle system. By combining the vehicle and operator models, a mathematical model of the closed-loop operator/vehicle system was formulated. A computer program was developed so as to simulate the motion of the tractor-trailer combination . In order to verify the operator/vehicle system model, the results of the field trials were compared with the simulated results. There was found to be reasonably good agreement between the two.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.261-264
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• 1997

In case of high speed and high mobility multibody tracked vehicle, it is hard to develop the realtime simulation model for track tension control because of the hundreds of highly nonlinear equations. In order to design more trustworthy realtime simulator for track tension control, it is necessary to use off-line tracked vehicle model. In this study, a step by step procedure is presented to develop realtime simulation model based on off-line tracked vehicle model. Simulation results show that modified off-line multibody tracked vehicle model can be used for real time simulation to control the track tension.

• Journal of Mechanical Science and Technology
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• v.19 no.spc1
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• pp.395-402
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• 2005

This paper deals with modeling and computer simulation of a full multibody vehicle model for a driving simulator. The multibody vehicle model is based on the recursive formulation and a corresponding simulation code is generated automatically from AUTOCODE, which is a symbolic computation package developed by the authors using MAPLE. The paper describes a procedure for automatically generating a highly efficient simulation code for the full vehicle model, while incorporating realistically modeled components. The following issues have been accounted for in the procedure, including software design for representing a mechanical system in symbolic form as a set of computer data objects, a multibody formulation for systems with various types of connections between bodies, automatic manipulation of symbolic expressions in the multibody formulation, interface design for allowing users to describe unconventional force-and torque-producing components, and a method for accommodating external computer subroutines that may have already been developed. The effectiveness and efficiency of the proposed method have been demonstrated by the simulation code developed and implemented for driving simulation.

• Journal of Auto-vehicle Safety Association
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• v.14 no.4
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• pp.35-42
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• 2022

This paper presents a stochastic model predictive control (SMPC) for stop maneuver of autonomous vehicles considering perception uncertainty of stopped vehicle. The vehicle longitudinal motion should achieve both driving comfortability and safety. The comfortable stop maneuver can be performed by mimicking acceleration profile of human driving pattern. In order to implement human-like stop motion, we propose a reference safe inter-distance and velocity model for the longitudinal control system. The SMPC is used to track the reference model which contains the position uncertainty of preceding vehicle as a chance constraint. We conduct simulation studies of deceleration scenarios against stopped vehicle in urban environment. The test results show that proposed SMPC can execute comfortable stop maneuver and guarantee safety simultaneously.

• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.75-82
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• 2022

Automated vehicles (AVs) are coming to our roadways. In practice, there are still several challenges that can impede the AV sensors are polluted on various road conditions. In this paper, we propose a strategy for V2E performance assurance technology using Kano model. We are developing the vehicle sensor cleaning system about the three types of commonly used sensors: camera, radar, and LiDAR. Surveys were carried out in 30 AV's experts on quality characteristics about V2E performance assurance technology. As a result, the Kano model developed to verify a major requirement of autonomous vehicle's sensor cleaning system. It is expected that the Kano model will be actively used to verify the importance of V2E development strategy.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.9
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• pp.51-58
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• 2002

Vehicle dynamics control systems are. complex and non-linear, so they have difficulties in developing a controller for the anti-lock braking systems and the auto-traction systems. Currently the fuzzy-logic technique to estimate the absolute vehicle speed is good results in normal conditions. But the estimation error in severe braking is discontented. In this paper, we estimate the absolute vehicle speed by using the wheel speed data from standard 50-tooth anti-lock braking system wheel speed sensors. Radial symmetric basis function of the neural network model is proposed to implement and estimate the absolute vehicle speed, and principal component analysis on input data is used. Ten algorithms are verified experimentally to estimate the absolute vehicle speed and one of those is perfectly shown to estimate the vehicle speed with a 4% error during a braking maneuver.

• Journal of the Korean Society for Railway
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• v.10 no.4
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• pp.431-437
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• 2007

This paper describes the dynamic modeling of a railway vehicle when it is under braking force. It is important for the enhancement of braking performance to establish a proper dynamic model of a railway vehicle because the braking performance is affected by some dynamic forces generated by a railway vehicle when it undergoes braking. In this paper, a dynamic model for one vehicle is suggested to compute the dynamic behavior of a railway vehicle in the HILS(Hardware In-the-loop Simulation) system for the railway vehicle braking devices. To simplify the dynamic model, friction between a wheel and a rail is assumed that there exist only the static and the dynamic friction forces. Static friction coefficient is also assumed to be a function of the running speed. Some simulations are carried out with various braking forces, and the braking characteristics according to the change of the braking force are discussed. This study can provide some fundamental results to construct the HILS system for braking devices of a railway vehicle.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.5
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• pp.575-582
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• 2019

Advanced driving assist system can support safety of driver and passengers which may require vehicle dynamics states as well as road geometry. It is essential to have in real-time estimation of related variables and parameters. Among the road geometry parameters, road slope angle which can not be measured is essential parameter in pose estimation, adaptive cruise control and others on sag road. In this paper, Kalman filter based method for the estimation of the vehicle dynamics and road slope angle using a nonlinear vehicle model is proposed. It uses a combination of Kalman filter as Cascade Extended Kalman Filter. CEKF uses measured vehicle states such as yaw rate, longitudinal/lateral acceleration and velocity. Unknown vehicle parameters such as center of gravity and inertia are obtained by 2 D.O.F lateral model and experimentally. Simulation and Experimental tests conducted with commercialized vehicle dynamics model and real-car.