Railway wheel profile fine-tuning system for profile recommendation
Yunguang Ye, Jonas Vuitton, Yu Sun, Markus Hecht
Abstract
Abstract This paper develops a wheel profile fine-tuning system (WPFTS) that comprehensively considers the influence of wheel profile on wheel damage, vehicle stability, vehicle safety, and passenger comfort. WPFTS can recommend one or more optimized wheel profiles according to train operators’ needs, e.g., reducing wheel wear, mitigating the development of wheel out-of-roundness (OOR), improving the shape stability of the wheel profile. Specifically, WPFTS includes four modules: (I) a wheel profile generation module based on the rotary-scaling fine-tuning (RSFT) method; (II) a multi-objective generation module consisting of a rigid multi-body dynamics simulation (MBS) model, an analytical model, and a rigid–flexible MBS model, for generating 11 objectives related to wheel damage, vehicle stability, vehicle safety, and passenger comfort; (III) a weight assignment module consisting of an adaptive weight assignment strategy and a manual weight assignment strategy; and (IV) an optimization module based on radial basis function (RBF) and particle swarm optimization (PSO). Finally, three cases are introduced to show how WPTFS recommends a wheel profile according to train operators’ needs. Among them, a wheel profile with high shape stability, a wheel profile for mitigating the development of wheel OOR, and a wheel profile considering hunting stability and derailment safety are developed, respectively.