• Structural Engineering and Mechanics
• /
• v.29 no.4
• /
• pp.355-380
• /
• 2008

In this study, the new three-dimensional finite element analysis model of guideway structures considering ultra high-speed magnetic levitation train-bridge interaction, in which the various improved finite elements are used to model structural members, is proposed. The box-type bridge deck of guideway structures is modeled by Nonconforming Flat Shell finite elements with six DOF (degrees of freedom). The sidewalls on a bridge deck are idealized by using beam finite elements and spring connecting elements. The vehicle model devised for an ultra high-speed Maglev train is employed, which is composed of rigid bodies with concentrated mass. The characteristics of levitation and guidance force, which exist between the super-conducting magnet and guideway, are modeled with the equivalent spring model. By Lagrange's equations of motion, the equations of motion of Maglev train are formulated. Finally, by deriving the equations of the force acting on the guideway considering Maglev train-bridge interaction, the complete system matrices of Maglev train-guideway structure system are composed.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.24 no.2
• /
• pp.167-175
• /
• 2011

The purpose of this study is to examine the impact that change in speed and modeling methods has on maglevs' runnability. The study constructed equations of motion on 4-DOF, 6DOF, and 10-DOF vehicles respectively and carried out numerical analysis, applying 4th Runge Kutta method, in order to run six different model maglev as changing the vehicles speed on the same bridge that had 2000 to 1 deflection. The analysis revealed that maglev's runnability improved as speed was lower and the specific model had higher number of bogey and EMS.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.21 no.2
• /
• pp.137-145
• /
• 2011

This study is proposed to develop a numerical interaction model of the magnetically levitated(maglev) train and guideway. For this purpose, equation of motion for 6-DOF vehicle model, EMS, guideway and guideway irregularity are derived as the state-space equation. In order to solve the state space equations, the present work was performed via matlab simulation using Runge-Kutta method. Through the simulation, the effect of dynamic response of maglev system to different vehicle speeds, guideway rigidity(EI) and masses is investigated.

• Journal of the Earthquake Engineering Society of Korea
• /
• v.15 no.3
• /
• pp.1-9
• /
• 2011

The purpose of this study is to examine the dynamic characteristics of low, medium and high speed Maglev trains and guideways through dynamic interaction analysis. The coupled dynamic equations of motion for a vehicle of 10-dof and the associated guideway girders are developed by superposing vibration modes of the girder itself. The controller used in the UTM-01 Maglev vehicle is adopted to control the air gap between the bogie and guideway in this study. The effect of roughness, the guideway deflection-ratio and vehicle speed on the dynamic response of the maglev vehicle and guideway are then investigated using the 4th Runge-Kutta method. From the numerical simulation, it is found that the air gap increases with an increase of vehicle speed and the roughness condition. In particular, the dynamic magnification factor of the guideway girder is small at low and medium speeds, but the factor is noticeable at super-high speeds.

• Journal of the Korean Society for Precision Engineering
• /
• v.34 no.1
• /
• pp.41-46
• /
• 2017

Magnetically levitated (Maglev) vehicles maintain a constant air gap between guideway and car bogie, and thereby achieves non-contact riding. Since the straightness and the flatness of the guideway directly affect the stability of levitation as well as the ride comfort, it is necessary to monitor the status of the guideway and to alert the train operators to any abnormal conditions. In order to develop a signal processing algorithm that extracts guideway irregularities from sensor data, virtual testing using a simulation model would be convenient for analyzing the exact effects of any input as long as the model describes the actual system accurately. Simulation model can also be used as an estimation model. In this paper, we develop a state-space dynamic model of a maglev vehicle system, running on the guideway that contains jumps. This model contains not only the dynamics of the vehicle, but also the descriptions of the power amplifier, the anti-aliasing filter and the sampling delay. A test rig is built for the validation of the model. The test rig consists of a small-scale maglev vehicle, tracks with artificial jumps, and various sensors measuring displacements, accelerations, and coil currents. The experimental data matches well with those from the simulation model, indicating the validity of the model.