• Journal of computational fluids engineering
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• v.19 no.1
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• pp.41-46
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• 2014

The aerodynamic drag of high-speed train has been calculated and the effect of bogie side fairing on the aerodynamic drag has been investigated. Computational Fluid Dynamics (CFD) simulation based on steady-state 3 dimensional Navier-Stokes equation has been conducted employing FLUENT 12 and the aerodynamic model of HEMU-430x, the Korean next generation high-speed train under development has been built using GAMBIT 2.4.6. Three types of bogie side fairing configuration, the proto-type without fairing, half-covered fairing to avoid the interference with the bogie frame and full-covered fairing have been adopted to the train model to compare the drag reduction effects of the bogie side fairing configurations and the numerical results yields that the bogie side fairing can reduce the aerodynamic drag of the 6-car trainset up to 7.8%. The aerodynamic drag coefficient of each vehicle as well as the flow structures around the bogie system have also been examined to analyze the reason and mechanism of the drag reduction by bogie side fairing.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.8 s.227
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• pp.1125-1134
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• 2004

This paper presents a mathematical model which is about the dynamics of not only a two wheel steering vehicle but a four wheel steering vehicle. A sliding mode ABS control strategy and PID rear wheel control logic are developed to improve the brake and cornering performances, and enhance the stability during emergency maneuvers. The performances of the controllers are evaluated under the various driving road conditions and driving situations. The numerical study shows that the proposed full car model is sufficient to accurately predict the vehicle response. The proposed ABS controller reduces the stopping distance and increases the vehicle stability. The results also prove that the ABS controller can be employed to a four wheel steering vehicle and improves its performance. The four wheel steering vehicle with PID rear wheel controller shows increase of stability when a vehicle speed is high and sharp cornering maneuver when a vehicle speed is low compared to that of a two wheel steer vehicle.

• International Journal of Automotive Technology
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• v.6 no.2
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• pp.149-159
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• 2005

A full nonlinear finite element P185/70Rl4 passenger car radial-ply tire model was developed and run on a 1.7-meter-diameter spinning test drum/cleat model at a constant speed of 50 km/h in order to investigate the tire transient response characteristics, i.e. the tire in-plane free vibration modes transmissibility. The virtual tire/drum finite element model was constructed and tested using the nonlinear finite element analysis software, PAM-SHOCK, a nonlinear finite element analysis code. The tire model was constructed in extreme detail with three-dimensional solid, layered membrane, and beam finite elements, incorporating over 18,000 nodes and 24 different types of materials. The reaction forces of the tire axle in vertical (Z axis) and longitudinal (X axis) directions were recorded when the tire rolled over a cleat on the drum, and then the FFT algorithm was applied to examine the transient response information in the frequency domain. The result showed that this PI 85/70Rl4 tire has clear peaks of 84 and 45 Hz transmissibility in the vertical and longitudinal directions. This result was validated against more than 10 previous studies by either theoretical or experimental approaches and showed excellent agreement. The tire's post-impact response was also investigated to verify the numerical convergence and computational stability of this FEA tire model and simulation strategy, the extraordinarily stable scenario was confirmed. The tire in-plane free vibration modes transmissibility was successfully detected. This approach was never before attempted in investigations of tire in-plane free vibration modes transmission phenomena; this work is believed to be the first of its kind.

• Journal of Korea Technology Innovation Society
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• v.21 no.2
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• pp.715-737
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• 2018

The introduction of autonomous vehicles will bring about not only changes in existing automotive ecosystem but also widespread changes in our lives, society, economy, and culture. Social acceptance is one of important influencing factors for the commercialization of autonomous vehicles. The purpose of this study analyzes influencing factors in the acceptance of autonomous vehicles in terms of consumers. Autonomous vehicles in this study were defined as PAV (Partial Autonomous Vehicles) and FAV (Full Autonomous Vehicles) by drivers' intervention or not. The survey was conducted over 20 years old including not only drivers but also non-drivers. The results showed that the factors affecting acceptance of PAV and FAV were different. Factors directly related to drivers influenced PAV acceptance while external environmental factors influenced FAV acceptance. This study is proved that is should need different strategies between PAV and FAV for increasing those acceptance

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.1
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• pp.20-28
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• 2014

This paper presents static output feedback LQ and $H_{\infty}$ controllers for rollover prevention. Linear quadratic static output feedback controllers have been proposed for rollover prevention in such a way to minimize the lateral acceleration and the roll angle. Rollover prevention capability can be enhanced if $H_{\infty}$ controller is designed. To avoid full-state measurement for feedback requirement or sensitiveness of an observer to nonlinear model error, static output feedback is adopted. To design static output feedback controllers, Kosut's method is adopted because it is simple to calculate. Differential braking and active anti-roll bar are adopted as actuators that generate yaw and roll moments, respectively. The proposed method is shown to be effective in preventing rollover through the simulations on nonlinear multi-body dynamic simulation software, CarSim.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.10 s.253
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• pp.1284-1292
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• 2006

Heat treatment is a controlled heating and cooling process to improve the physical and/or mechanical properties of metal products without changing their shapes. Today finite element method is widely used to simulate lots of manufacturing processes including heat treatment and surface hardening processes, which aims to reduce the number of time- and cost-consuming experimental tryouts. In this study we tried, using this method, to simulate the full carburizing process that consists of carburizing, diffusing and quenching, and to predict the distribution of carbon contents, phase fraction and hardness, thermal deformation and other mechanical characteristics as the results. In the finite element analysis deformation, heat transfer, phase transformation and diffusion effects are taken into consideration. The carburizing process of a lock gear, a part of the car seat recliner, that is manufactured by the fine blanking process is adopted as the analysis model. The numerical results are discussed and partly compared with experimental data. And a combination of process parameters that is expected to give the highest surface hardness is proposed on the basis of this discussion.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2949-2952
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• 2000

A new neural networks and learning algorithm are proposed in order to measure nonlinear heights of complexed road environments in realtime without pre-information. This new neural networks is Error Self Recurrent Neural Networks(ESRN), The structure of it is similar to recurrent neural networks: a delayed output as the input and a delayed error between the output of plant and neural networks as a bias input. In addition, we compute the desired value of hidden layer by an optimal method instead of transfering desired values by back-propagation and each weights are updated by RLS(Recursive Least Square). Consequently. this neural networks are not sensitive to initial weights and a learning rate, and have a faster convergence rate than conventional neural networks. We can estimate nonlinear models in realtime by ESRN and learning algorithm and control nonlinear models. To show the performance of this one. we control 7 degree of freedom full car model with several control method. From this simulation. this estimation and controller were proved to be effective to the measurements of nonlinear road environment systems.

• International Journal of Automotive Technology
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• v.6 no.2
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• pp.141-148
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• 2005

In order to reduce the time and costs of improving the performance of vehicle suspensions, the techniques for optimizing damping and air spring characteristic were proposed. A full vehicle model for a bus is constructed with a car body, front and rear suspension linkages, air springs, dampers, tires, and a steering system. An air spring and a damper are modeled with nonlinear characteristics using experimental data and a curve fitting technique. The objective function for ride quality is WRMS (Weighted RMS) of the power spectral density of the vertical acceleration at the driver's seat, middle seat and rear seat. The objective function for handling performance is the RMS (Root Mean Squares) of the roll angle, roll rate, yaw rate, and lateral acceleration at the center of gravity of a body during a lane change. The design variables are determined by damping coefficients, damping exponents and curve fitting parameters of air spring characteristic curves. The Taguchi method is used in order to investigate sensitivity of design variables. Since ride and handling performances are mutually conflicting characteristics, the validity of the developed optimum design procedure is demonstrated by comparing the trends of ride and handling performance indices with respect to the ratio of weighting factors. The global criterion method is proposed to obtain the solution of multi-objective optimization problem.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.9
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• pp.1643-1653
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• 1992

A method, which uses analytical or numerical modal analysis results, e.g. from finite element analysis, to select desirable response measurement and excitation points for an efficient modal testing is introduced. First, points of master degree of freedom(DOP) are determined so as to statistically minimize errors between responses of a full order model and those estimated from the reduced order model. Such master DOF's are selected as the response measurement points. Then a criterion named 'driving point model constant(DPMC)' related to the magnitudes of resonance peaks of the driving point freqency response functions used to select the point of excitation out of the master DOF's. In this work, the method is demonstrated through applications to modal testing on a one dimensional cantilever beam and an aluminum plate and the results are compared with those by another technique. also, the method is applied to a two dimensional structural component of a passenger car.

• Transactions of the Korean Society of Automotive Engineers
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• v.3 no.1
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• pp.33-44
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• 1995

As the occupant safety receives more attention from automobile industries. protection systems have been developed quite well. Developed protection systems must be evaluated through real tests in crash environment Since the real tests are extremely expensive. computer simulations are replaced for some prediction of the real test In the computer simulation. it is very crucial to express the real environment precisely in the modeling precess. The energy absorbing(EA) steering system has a very important rote in vehicle crashes because the occupant can hit the system directly. In this study. the EA steering system is modeled precisely. analyzed for the safely and designed by an optimization technology. First. the EA steering system is disassembled by parts and modeled by segments and joints. The segments are modeled by rigid bodies in motion and they have resistances in contact. Spring-damper elements and force-deflection curves are utilized to represent the joints. The body block test is cal lied out to validate. the modeling. When the test results are not enough for the detailed modeling. the differences between tests and simulations are minimized to calculate unknown parameters using optimization. The established model is applied to a crash simulation of a full-car model and tuned again. After the modeling is finished. components of the steering system are designed by an optimization algorithm. In the optimization process. the compound injury of a driver is defined and minimized to determine the chracteristics of the components. The second. order approximation algorithm has been adopted for the optimization.