Experimental validation of non-linear multi-body railroad vehicle system algorithms

Pigorini, F; Gugliotta, Antônio; Sinokrot, Tariq; Shabana, Ahmed A.

doi:10.1243/14644193jmbd107

Cited by 2 publications

(2 citation statements)

References 7 publications

(9 reference statements)

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“…In general, the rigs can be used to perform experimental tests for stability, comfort, and braking conditions. The use of reduced-scale vehicles with the roller rigs is achieved in this study by following Jaschinski's scaling method [4,10]. Using this method, a length scale factor of 1/4 or 1/5 can be used in building bogie prototypes.…”

Section: Experimental Roller Rigmentioning

confidence: 99%

Experimental and numerical investigation of railroad vehicle braking dynamics

Mellace

Lai

Gugliotta

et al. 2009

Proceedings of the Institution of Mechanical Engineers, Part K:

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One of the important issues associated with the use of trajectory coordinates in railroad vehicle dynamic algorithms is the ability of such coordinates to deal with braking and traction scenarios. In these algorithms, track coordinate systems that travel with constant speeds are introduced. As a result of using a prescribed motion for these track coordinate systems, the simulation of braking and/or traction scenarios becomes difficult or even impossible. The assumption of the prescribed motion of the track coordinate systems can be relaxed, thereby allowing the trajectory coordinates to be effectively used in modelling braking and traction dynamics. One of the objectives of this investigation is to demonstrate that by using track coordinate systems that can have an arbitrary motion, the trajectory coordinates can be used as the basis for developing computer algorithms for modelling braking and traction conditions. To this end, a set of six generalized trajectory coordinates is used to define the configuration of each rigid body in the railroad vehicle system. This set of coordinates consists of an arc length that represents the distance travelled by the body, and five relative coordinates that define the configuration of the body with respect to its track coordinate system. The independent non-linear state equations of motion associated with the trajectory coordinates are identified and integrated forward in time in order to determine the trajectory coordinates and velocities. The results obtained in this study show that when the track coordinate systems are allowed to have an arbitrary motion, the resulting set of trajectory coordinates can be used effectively in the study of braking and traction conditions. The results obtained using the trajectory coordinates are compared with the results obtained using the absolute Cartesian-coordinate-based formulations, which allow modelling braking and traction dynamics. In addition to this numerical validation of the trajectory coordinate formulation in braking scenarios, an experimental validation is also conducted using a roller test rig. The comparison presented in this study shows a good agreement between the obtained experimental and numerical results. distance travelled by the body along the track. This arc length parameter can be used with the prescribed track geometry to define the location and orientation of a track coordinate system that follows the body motion. The other five parameters used in the trajectory coordinate formulations are two relative translations and three relative rotations. The two translational coordinates define the location of the origin of the body coordinate system with respect to the track coordinate system in directions lateral and normal to the track. The three relative rotations define the orientation of the body coordinate system with respect to the track coordinate system. These trajectory coordinates, JMBD129

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Section: Experimental Roller Rigmentioning

confidence: 99%

Experimental and numerical investigation of railroad vehicle braking dynamics

Mellace

Lai

Gugliotta

et al. 2009

Proceedings of the Institution of Mechanical Engineers, Part K:

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“…Aiming at the 7-axis laser welding and measuring machine tool, a hybrid dynamic modelling method [10][11][12] is presented. Several desirable trajectories in different feed rate are applied to examine the spatial error of tool path motion and test the performance.…”

Section: Introductionmentioning

confidence: 99%

Electro-mechanical simulation and analysis on spatial error of multi-axis laser welding motion

Peng

Zhang

Yan

et al. 2011

Proceedings of the Institution of Mechanical Engineers, Part K:

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This article proposes a co-simulation platform concerning both mechanical and control subsystems, in order to test the dynamic performance of the welding machine. Two welding trajectories, before and after smoothing, are conducted in the simulation platform and welding practice to study the influence among smoothness, space precision and welding quality. Meanwhile, a series of welding trajectories are used to examine the spatial error of tool path motion by simulation in the platform. Results indicate that, the feed rate increases so high, beyond the dynamic characteristic of machine tool that induced undesirable oscillation of welding velocity and acceleration, as well as increased spatial error.

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Experimental validation of non-linear multi-body railroad vehicle system algorithms

Cited by 2 publications

References 7 publications

Experimental and numerical investigation of railroad vehicle braking dynamics

Experimental and numerical investigation of railroad vehicle braking dynamics

Electro-mechanical simulation and analysis on spatial error of multi-axis laser welding motion

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