Journal: Vehicle System Dynamics

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Abbreviation

Veh. Syst. Dyn.

Publisher

Taylor & Francis

Journal Volumes

ISSN

0042-3114
1744-5159

Description

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Publications 1 - 8 of 8
  • Stefanelli, R.; Dual, Jürg; Cataldi-Spinola, E. (2006)
    Vehicle System Dynamics
  • Andreasson, J.; Bunte, T. (2006)
    Vehicle System Dynamics
  • De Almeida Costa, Mariana; Costa, João N.; Andrade, António R.; et al. (2023)
    Vehicle System Dynamics
    Guaranteeing operational safety is mandatory for railways worldwide. As track deteriorates, its geometry deviates from ideal conditions (e.g. perfectly aligned and levelled), which creates undesired vibration and oscillations to the vehicle, increasing dynamic loads and derailment risk. Although current standards establish nominal limits for the track geometry, such point-wise comparisons may overlook relevant track features that can lead to unsafe conditions. The proposed investigation is a contribution to the study of the response of the rail vehicle to the track quality, aimed at identifying track irregularities that produce high track forces and unsafe vehicle responses. To fulfil this aim, Wavelet Analysis is combined with Vehicle Dynamics Simulations to evaluate how the track irregularities, filtered in various wavelength ranges and reconstructed with different wavelets and coefficients' amplitudes, impact vehicle safety in terms of the Nadal safety criterion Y/Q. The simulations demonstrate that defects occurring in some scales/frequencies are more harmful than others, and the similarity between the geometric defects and the shape of the wavelets may be used to identify track locations that require maintenance. These findings suggest that it is possible to create ‘stamps’ of track irregularities that can be used by infrastructure managers to improve their maintenance strategies.
  • Micheli, Francesco; Bersani, Mattia; Arrigoni, Stefano; et al. (2023)
    Vehicle System Dynamics
    This paper presents a trajectory planner for autonomous driving based on a Nonlinear Model Predictive Control (NMPC) algorithm that accounts for Pacejka's nonlinear lateral tyre dynamics as well as for zero speed conditions through a novel slip angle calculation. In the NMPC framework, road boundaries and obstacles (both static and moving) are taken into account with soft and hard constraints implementation. The numerical solution of the NMPC problem is carried out using ACADO toolkit coupled with the quadratic programming solver qpOASES. The effectiveness of the proposed NMPC trajectory planner has been tested using CarMaker multibody models. The formulation of vehicle, road and obstacles' models has been specifically tailored to obtain a continuous and differentiable optimisation problem. This allows to achieve a computationally efficient implementation by exploiting automatic differentiation. Moreover, robustness is improved by means of a parallelised implementation of multiple instances of the planning algorithm with different spatial horizon lengths. Time analysis and performance results obtained in closed-loop simulations show that the proposed algorithm can be implemented within a real-time control framework of an autonomous vehicle.
  • Zimmer, Dirk; Otter, Martin (2010)
    Vehicle System Dynamics
  • Alberding, Matthäus B.; Tjønnås, Johannes; Johansen, Tor A. (2014)
    Vehicle System Dynamics
  • Novi, Tommaso; Liniger, Alexander; Capitani, Renzo; et al. (2020)
    Vehicle System Dynamics
  • Voser, Christoph; Hindiyeh, Rami Y.; Gerdes, Christian (2010)
    Vehicle System Dynamics
Publications 1 - 8 of 8