• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.3
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• pp.190-197
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• 2000

A graphic vehicle modeling pre-processing program and a visualization post-processing program have been developed for AutoDyn7, which is a special program for vehicle dynamics. The Rapid-App for GUI(Graphic User Interface) builder and the Open Inventor for 3D graphic library have been employed to develop these programs in Silicon Graphics workstation. A Graphic User Interface program integrates vehicle modeling pre-processor, AutoDyn7 analysis processor, and visualization post-processor. In vehicle modeling pre-processor, vehicle hard point data for a suspension model are automatically converted into multibody vehicle system data. An interactive graphics capabilities provides suspension modeling aides to verify user input data interactively. In visualization post-processor, vehicle virtual test simulation results are animated with virtual testing environments.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.10
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• pp.958-966
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• 2007

This study presents full vehicle dynamics model for the dynamic characteristic analysis of chassis parts which are suspension and brake system. This vehicle dynamics model is appled to kinematics and quasi-static analysis for each chassis part. In order to develop the vehicle dynamics model, the parameters of each chassis element part which are bush, spring and damper are measured by experiment. Also the wheel forces and moments of 6 DOF are measured at each wheel center. These data are applied to input parameter for vehicle dynamics model. And the verification of the developed model is achieved to comparison with the experimental force data of spring, trailing arm and assist arm by using the load response by strain gauge. These experimental force data are acquired by road test at event surfaces of P/G which are belgian and chuck holes roads.

• Transactions of the Korean Society of Automotive Engineers
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• v.4 no.5
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• pp.109-118
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• 1996

An analysis of handling characteristics of a vehicle is performed for step and pulse steering input, which may be very useful in suspension design stage. Many developed computer programs for vehicle dynamics require test data of compliance effects for proto type car. Therefore, these programs are not suitable for automobile development stage. Using the raw design data of suspension and steering system, we analyze the vehicle behavior for step and pulse steering input with commercial multibody dynamics program, ADAMS. Simulated results are in good agreement with vehicle test results. Vehicle handling characteristics parameters which are very useful in automobile suspension design are evaluated from the analysis.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.33 no.4
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• pp.290-297
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• 1997

Underwater robotic vehicles(URVs) are used for various work assignments such as pipe-lining, inspection, data collection, drill support, hydrography mapping, construction, maintenance and repairing of undersea equipment, etc. As the use of such vehicles increases the development of vehicles having greater autonomy becomes highly desirable. The vehicle control system is one of the most critic vehicle subsystems to increase autonomy of the vehicle. The vehicle dynamics is nonlinear and time-varying. Hydrodynamic coefficients are often difficult to accurately estimate. It was also observed by experiments that the effect of electrically powered thruster dynamics on the vehicle become significant at low speed or stationkeeping. The conventional linear controller with fixed gains based on the simplified vehicle dynamics, such as PID, may not be able to handle these properties and result in poor performance. Therefore, it is desirable to have a control system with the capability of learning and adapting to the changes in the vehicle dynamics and operating parameters and providing desired performance. This paper presents an adaptive and learning control system which estimates a new set of parameters defined as combinations of unknown bounded constants of system parameter matrices, rather than system parameters. The control system is described with the proof of stability and the effect of unmodeled thruster dynamics on a single thruster vehicle system is also investigated.

• 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.

• Transactions of the Korean Society of Automotive Engineers
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• v.17 no.1
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• pp.169-175
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• 2009

Real-time multibody vehicle dynamics software has been developed for virtual handling tests. The software can be utilized for HILS(Hardware In the Loop Simulations) and consists of three modules such as a graphical vehicle modeling preprocessor, a real time dynamics solver, and a virtual reality graphic postprocessor for virtual handling tests. In the graphical vehicle modeling preprocessor, vehicle hard point data for a suspension model are automatically converted into multibody vehicle model. In the real time dynamics solver, the efficient subsystem synthesis method is used to create multibody equations of motion for a subsystem by a subsystem. In the virtual reality graphic postprocessor, an animator has been also developed by using Matlab Virtual Reality Toolbox for virtual handling tests.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.858-861
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• 2014

This paper presents a simplified finite element tire model for vehicle dynamics analysis. The classical finite element tire model was too big to simulate dynamic properties of the tire. In the simplified model, number of nodes of the tire model was dramatically reduced, and thus its simulation time was several times less than the classical model. Bead, carcass, belt which have an important role to the dynamic characteristics of tire were replaced by simple axis symmetric membrane elements. Also the rebar element was deleted. The tire model has been verified by comparing vertical stiffness data of the simulation model to the test data.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.208-214
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• 2014

Vehicle dynamic states used in various advanced driving safety systems are influenced by road geometry. Among the road geometry information, the vehicle pitch angle influenced by road slope and acceleration-deceleration is essential parameter used in pose estimation including the navigation system, advanced adaptive cruise control and others on sag road. Although the road slope data is essential parameter, the method measuring the parameter is not commercialized. The digital map including the road geometry data and high-precision DGPS system such as DGPS(Differential Global Positioning System) based RTK(Real-Time Kinematics) are used unusually. In this paper, low-cost cascade extended Kalman filter(CEKF) based road slope estimation method is proposed. It use cascade two EKFs. The EKFs use several measured vehicle states such as yaw rate, longitudinal acceleration, lateral acceleration and wheel speed of the rear tires and 3 D.O.F(Degree Of Freedom) vehicle dynamics model. The performance of proposed estimation algorithm is evaluated by simulation based on Carsim dynamics tool and T-car based experiment.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.2
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• pp.132-140
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• 2002

A momentum backpropagation neural network is prepared to carry out real-time dynamics simulations of a passenger car. A full-car model of fifteen degrees of freedom was constructed for vehicle dynamics analysis. Human body dynamics analysis was performed for a male driver(50 percentile Korean adult) restrained by a three point seatbelt system. The trained data using the neural network were obtained using a dynamic solver, ADAMS . The neural network were formed based on the dynamics of the simulator. The optimized hidden layer was obtained by selecting the optimal number of hidden layers. The driving scenario including bump passing and lane changing has been used for the estimation of the proposed neural network. A comparison between the trained data and neural network outputs is found to be satisfactory to show the applicability of the suggested approach.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.690-699
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• 2008

In this paper a conventional approach for design and analysis of subsonic air vehicle is used. First of all subsonic aerodynamic coefficients are calculated using Computational Fluid Dynamics(CFD) tools and then wind-tunnel model was developed that integrates vehicle components including control surfaces and initial data is validated as well as refined to enhance aerodynamic efficiency of control surfaces. Experimental data and limited computational fluid dynamics solutions were obtained over a Mach number range of 0.5 to 0.8. The experimental data show the component build-up effects and the aerodynamic characteristics of the fully integrated configurations, including control surface effectiveness. The aerodynamic performance of the fully integrated configurations is comparable to previously tested subsonic vehicle models. Mathematical model of the dynamic equations in 6-Degree of Freedom(DOF) is then simulated using MATLAB/SIMULINK to simulate trajectory of vehicle. Effect of altitude on range, Mach no and stability is also shown. The approach presented here is suitable enough for preliminary conceptual design. The trajectory evaluation method devised accurately predicted the performance for the air vehicle studied. Formulas for the aerodynamic coefficients for this model are constructed to include the effects of several different aspects contributing to the aerodynamic performance of the vehicle. Characteristic parameter values of the model are compared with those found in a different set of similar air vehicle simulations. We execute a set of example problems which solve the dynamic equations to find the aircraft trajectory given specified control inputs.