A comparison of longitudinal adhesion models and identification of the dominant adhesion parameter. Issue 4 (2nd April 2020)

• Record Type: Journal Article
• Authors: Lee, HyunWook
• Is Part Of: Vehicle system dynamics. Volume 58:Issue 4(2020)
• Page Start: 590
• Page End: 603
• Publication Date: 2020-04-02
• Subjects: Estimation accuracy -- adhesion model -- dynamic variance -- parameter contribution -- coefficient of adhesion -- multiple regression analysis; Motor vehicles -- Dynamics -- Periodicals; Electronic journals; 629.231
• DOI: 10.1080/00423114.2019.1592204
• Languages: English
• ISSNs: 0042-3114

Abstract

ABSTRACT: Accurately estimating the coefficient of adhesion (CoA) is important to the safety, maintenance, operation and wheel–rail dynamics of railway systems. Studies have reported the influence of various parameters on the CoA and developed subsequent models, but parameter contribution or model estimation accuracy has not been systematically examined. Therefore, this study aims to quantitatively compare the accuracy of Heuristic, Polach and Dynamic estimation models with statistical measures and to investigate the contribution of various parameters on the CoA. Experimental CoA data was collected using a twin-disc rig at 57 and 85 km/h. The percentage root-mean-square error (PRMSE) of each model was then calculated for the rolling, sliding and overall contact regimes at each speed and multiple regression analysis (MRA) was applied to examine the contribution of each parameter. The Dynamic model was found to most accurately estimate the CoA in the sliding contact regime at both speeds due to its ability to capture dynamic variance. The Polach model also provided accurate estimations, but could not capture dynamic variance at the sliding contact regime. Using MRA, the CoA was found to be most dependent on sliding velocity. Overall, this work contributes to increase the prediction accuracy of wheel–rail contact dynamics.