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Keywords: parameter identification, railway vehicle model, uncertainty, stationary tests, singular value decomposition, virtual acceptance process.

Summary

The work carried out in this paper is focused on improving the validation process of mathematical models of railway vehicles. Moreover, the reliability of multi-body simulation results used for predicting the vehicle behaviour is determined by the model building process and the accuracy of the model parameters. Therefore, the objective of this paper is to develop a parameter identification methodology in order to obtain accurate estimations of the vehicle model parameters by means of the results of the stationary tests during the acceptance process. For this purpose a new criterion is developed (SVD criterion), based on the singular value decomposition analysis, which provides useful information about which parameters could be identified in each test and which measurements must be taken for ensuring that the parameters are correctly estimated. Furthermore, this methodology allows for the probabilistic calculation of the model parameters, by estimating confidence uncertainty margins for those parameters. These parameter uncertainties are caused by the measurement uncertainties of the sensors used in the acceptance tests. Regarding the validation of the methodology, virtual verifications were performed. The virtual validation was carried out by applying the methodology to virtual results of the wheel unloading test, analysing the parameters that could be identified. Four significant model parameters can be accurately calculated for the analysed vehicle: vertical primary and secondary suspension stiffness, stiffness of the anti-roll bar, and height of the null moment point (the lateral/roll coupling effect of the air spring). These parameters can be estimated by only adding two additional measurements (the vertical displacements of the primary and secondary suspensions) to the mandatory ones according to EN14363.

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Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Proceedings ISSN 1759-3433 CCP: 104 PROCEEDINGS OF THE SECOND INTERNATIONAL CONFERENCE ON RAILWAY TECHNOLOGY: RESEARCH, DEVELOPMENT AND MAINTENANCE Edited by: J. Pombo Paper 253 A New Parameter Identification Method for Railway Vehicle Models Using Stationary Tests M. Aizpun¹, A. Alonso² and J. Vinolas³ ¹School of Mechanical Engineering, Pontificia Universidad Católica de Valparaíso, Chile ²CEIT and Tecnun, University of Navarra, Spain ³Bantec Group, Spain doi:10.4203/ccp.104.253 purchase the full-text of this paper Full Bibliographic Reference for this paper M. Aizpun, A. Alonso, J. Vinolas, "A New Parameter Identification Method for Railway Vehicle Models Using Stationary Tests", in J. Pombo, (Editor), "Proceedings of the Second International Conference on Railway Technology: Research, Development and Maintenance", Civil-Comp Press, Stirlingshire, UK, Paper 253, 2014. doi:10.4203/ccp.104.253 Keywords: parameter identification, railway vehicle model, uncertainty, stationary tests, singular value decomposition, virtual acceptance process. Summary The work carried out in this paper is focused on improving the validation process of mathematical models of railway vehicles. Moreover, the reliability of multi-body simulation results used for predicting the vehicle behaviour is determined by the model building process and the accuracy of the model parameters. Therefore, the objective of this paper is to develop a parameter identification methodology in order to obtain accurate estimations of the vehicle model parameters by means of the results of the stationary tests during the acceptance process. For this purpose a new criterion is developed (SVD criterion), based on the singular value decomposition analysis, which provides useful information about which parameters could be identified in each test and which measurements must be taken for ensuring that the parameters are correctly estimated. Furthermore, this methodology allows for the probabilistic calculation of the model parameters, by estimating confidence uncertainty margins for those parameters. These parameter uncertainties are caused by the measurement uncertainties of the sensors used in the acceptance tests. Regarding the validation of the methodology, virtual verifications were performed. The virtual validation was carried out by applying the methodology to virtual results of the wheel unloading test, analysing the parameters that could be identified. Four significant model parameters can be accurately calculated for the analysed vehicle: vertical primary and secondary suspension stiffness, stiffness of the anti-roll bar, and height of the null moment point (the lateral/roll coupling effect of the air spring). These parameters can be estimated by only adding two additional measurements (the vertical displacements of the primary and secondary suspensions) to the mandatory ones according to EN14363. purchase the full-text of this paper (price £20) go to the previous paper go to the next paper return to the table of contents return to the book description purchase this book (price £65 +P&P)
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