A CEN standard (EN 14067-4, 2005) describes the methodologies for the assessment of the running resistance of railway vehicles starting from full-scale test measurements. According to this standard, the speed dependent terms of the equation of Davis [1] have to be determined by means of coasting tests. In this paper, a new method to estimate the running resistance coefficients from a full-scale coasting test is proposed and compared with the two methods proposed in the CEN standard (the regression method and the speed history identification method). The main advantage of this new method is that it does not require the railway line characteristics to be known and it will be shown that the new method is able to evaluate the coefficients with an accuracy equivalent to that of the other methods considered.

Simplified estimation of the train resistance parameters: full scale experimental tests and analysis

SOMASCHINI, CLAUDIO;ROCCHI, DANIELE;TOMASINI, GISELLA MARITA;SCHITO, PAOLO
2016-01-01

Abstract

A CEN standard (EN 14067-4, 2005) describes the methodologies for the assessment of the running resistance of railway vehicles starting from full-scale test measurements. According to this standard, the speed dependent terms of the equation of Davis [1] have to be determined by means of coasting tests. In this paper, a new method to estimate the running resistance coefficients from a full-scale coasting test is proposed and compared with the two methods proposed in the CEN standard (the regression method and the speed history identification method). The main advantage of this new method is that it does not require the railway line characteristics to be known and it will be shown that the new method is able to evaluate the coefficients with an accuracy equivalent to that of the other methods considered.
2016
CIVIL-COMP PROCEEDINGS - vol. 110
Coasting tests; Full scale tests; Regression method; Speed history method; Train running resistance; Computational Theory and Mathematics; Civil and Structural Engineering; Artificial Intelligence; Environmental Engineering
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/989871
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