• International Journal of Railway
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• v.5 no.4
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• pp.156-162
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• 2012

When a vehicle passes through turnout, it is required to minimize the changes of lateral force for running safety of vehicle. Therefore, it is necessary to analyze interaction between the vehicle and the turnout in order to estimate the lateral force and the derailment coefficient on the turnout. In this paper, analysis model of the vehicle and turnout are established and analysis is carried out when the vehicle passes through turnout in order to improve running safety of the vehicle on turnout. To verify the vehicle and turnout analysis model, the contact points between wheel and rail and the influence of changing cradle and tongue rail are also discussed.

• Structural Engineering and Mechanics
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• v.46 no.1
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• pp.75-90
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• 2013

In order to identify damage of highway bridges rapidly, a method for damage identification using dynamic response of bridge induced by moving vehicle and static test data is proposed. To locate damage of the structure, displacement energy damage index defined from the energy of the displacement response time history is adopted as the indicator. The displacement response time histories of bridge structure are obtained from simulation of vehicle-bridge coupled vibration analysis. The vehicle model is considered as a four-degree-of-freedom system, and the vibration equations of the vehicle model are deduced based on the D'Alembert principle. Finite element method is used to discretize bridge and finite element model is set up. According to the condition of displacement and force compatibility between vehicle and bridge, the vibration equations of the vehicle and bridge models are coupled. A Newmark-${\beta}$ algorithm based professional procedure VBAP is developed in MATLAB, and used to analyze the vehicle-bridge system coupled vibration. After damage is located by employing the displacement energy damage index, the damage extent is estimated through the least-square-method based model updating using static test data. At last, taking one simply supported bridge as an illustrative example, some damage scenarios are identified using the proposed damage identification methodology. The results indicate that the proposed method is efficient for damage localization and damage extent estimation.

• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.1-20
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• 2022

As unmanned aerial vehicle (UAV) technology grew in popularity over the years, it was introduced for air quality monitoring. This can easily be used to estimate the sidewalk emission concentration by calculating road traffic emission factors of different vehicle types. These calculations require a simulation of the spread of pollutants from one or more sources given for estimation. For this purpose, a Gaussian plume dispersion model was developed based on the US EPA Motor Vehicle Emissions Simulator (MOVES), which provides an accurate estimate of fuel consumption and pollutant emissions from vehicles under a wide range of user-defined conditions. This paper describes a methodology for estimating emission concentration on the sidewalk emitted by different types of vehicles. This line source considers vehicle parameters, wind speed and direction, and pollutant concentration using a UAV equipped with a monocular camera. All were sampled over an hourly interval. In this article, the YOLOv5 deep learning model is developed, vehicle tracking is used through Deep SORT (Simple Online and Realtime Tracking), vehicle localization using a homography transformation matrix to locate each vehicle and calculate the parameters of speed and acceleration, and ultimately a Gaussian plume dispersion model was developed to estimate the CO, NOx concentrations at a sidewalk point. The results demonstrate that these estimated pollutants values are good to give a fast and reasonable indication for any near road receptor point using a cheap UAV without installing air monitoring stations along the road.

• Transactions of the Korean Society of Automotive Engineers
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• v.23 no.5
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• pp.486-493
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• 2015

In this paper, a battery model for electric vehicle virtual platform was developed. A battery model consisted of a battery cell model and battery thermal management system. A battery cell model was developed based on Randles equivalent circuit model. Circuit parameters in the form of 3D map data was obtained by charge-discharge experiment of Li-Polymer battery in various temperature condition. The developed battery cell model was experimentally verified by comparing voltages. Thermal management system model was also developed using heat generator, heat transfer and convection model, and cooling fan. For verification of the developed battery model in vehicle level, the integrated battery model was applied in to EV(electric vehicle) virtual platform, and virtual driving simulation using UDDS velocity profile was conducted. The accuracy of the developed battery model has been verified by comparing the simulation results from EV platform with the experimental data.

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.5
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• pp.581-587
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• 2016

Braking is a basic and an important safety feature for all vehicles, and the final braking performance of a vehicle is determined by the vehicle's ABS performance and tire performance. However, the combination of excellent ABS and tires will not always ensure good braking performance. This is due to the fact that tire performance has non-linearity and uncertainty in predicting the repeated increase and decrease of wheel slip when activating the ABS, thus increasing the uncertainty of tire performance prediction. Furthermore, existing studies predicted braking performance after using an ABS that used a wheel slip control as a controller, which was different from an actual vehicle's ABS that controlled angular acceleration, therefore causing a decrease in the prediction accuracy of the braking performance. This paper reverse-designed the ABS that controlled angular acceleration based on the information on brake pressure, etc., which were obtained from vehicle tests, and established a braking performance prediction analysis model by combining a multi-body dynamics(MBD) vehicle model and a magic formula(MF) tire model. The established analysis model was verified after comparing it with the results of the braking tests of an actual vehicle. Using this analysis model, this study analyzed the braking effect by vehicle factor, and finally designed a tire that had optimized braking performance. As a result of this study, it was possible to design the MF tire model whose braking performance improved by 9.2 %.

• Journal of Service Research and Studies
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• v.14 no.1
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• pp.27-43
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• 2024

The market share of online platform services in the used car market continues to expand. And The used car online platform service provides service users with specifications of vehicles, accident history, inspection details, detailed options, and prices of used cars. SUV vehicle type's share in the domestic automobile market will be more than 50% in 2023, Sales of Hybrid vehicle type are doubled compared to last year. And these vehicle types are also gaining popularity in the used car market. Prior research has proposed a used car price prediction model by executing a Machine Learning model for all vehicles or vehicles by brand. On the other hand, the popularity of SUV and Hybrid vehicles in the domestic market continues to rise, but It was difficult to find a study that proposed a used car price prediction model for these vehicle type. This study selects a used car price prediction model by vehicle type using vehicle specifications and options for Sedans, SUV, and Hybrid vehicles produced by domestic brands. Accordingly, after selecting feature through the Lasso regression model, which is a feature selection, the ensemble model was sequentially executed with the same sampling, and the best model by vehicle type was selected. As a result, the best model for all models was selected as the CBR model, and the contribution and direction of the features were confirmed by visualizing Tree SHAP Value for the best model for each model. The implications of this study are expected to propose a used car price prediction model by vehicle type to sales officials using online platform services, confirm the attribution and direction of features, and help solve problems caused by asymmetry fo information between them.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11b
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• pp.140-143
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• 2005

The hybrid CAE/CAT methods are widely applied to product development in various fields because this method can predict the response of the whole system when a part of the system is changed. Especially, the hybrid CAE/CAT method is very useful to predict tile vehicle NVH characteristics after changing some parts of the vehicle. Target parts can be established on the basis of test models and FE models of the prototype constructed in the planning stage of car development. In this study, the topic was focused on the proper test-based FBS application process to predict vehicle NVH characteristic. First, the test-based FBS method was apply to vehicle substructure and car-body. And then the test-based model was replaced with FE model to apply hybrid CAE/CAT method. The replaced FE model was modified through the optimization process. The interior noise in vehicle during the drive was predicted with Modified FE model, then the predicted results were verified by experimenting with actual modified model.

• 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.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.937-943
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• 2017

To design an automatic steering controller with high performance for autonomous vehicle, it is necessary to have a precise model of the lateral dynamics with respect to the steering command input. This paper presents an empirical modeling of the steering system for an autonomous vehicle. The steering system here is represented by three individual transfer function models: a steering wheel actuator model from the steering command input to the steering angle of the shaft, a dynamic model between the steering angle and the yaw rate of the vehicle, and a dynamic model between the steering command and the lateral deviation of vehicle. These models are identified using frequency response data. Experiments were performed using a real vehicle. It is shown that the resulting identified models have been well fitted to the experimental data.

• Journal of information and communication convergence engineering
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• v.21 no.4
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• pp.351-358
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• 2023

This study designed a model-based Vehicle Control Unit (VCU) software for electric vehicles. Electric vehicles have transitioned from conventional powertrains (e.g., engines and transmissions) to electric powertrains. The primary role of the VCU is to determine the optimal torque for driving control. This decision is based on the driver's power request and current road conditions. The determined torque is then transmitted to the electric drive system, which includes motors and controllers. The VCU employs an Artificial Neural Network (ANN) and calibrated reference torque to enhance the electric vehicle's performance. The designed VCU software further refines the final reference torque by comparing the control logic with the torque calculation functions and ANN-generated reference torque. Vehicle tests confirmed the effective optimization of vehicle performance using the model-based VCU software, which includes an ANN.