As high-speed trains operate at a higher speed, the problem of rail wear is more serious. In this paper, a new Gaussian function correction (GFC) method is proposed to design the new rail profile, two parameters are introduced to control the removal area. Then a high-speed train vehicle dynamic model is established, the Kriging surrogate model (KSM) is used to reduce the number of simulations and the Non dominated sorting genetic algorithm-II (NSGA-II) algorithm is used to optimize the rail profile. Finally, the dynamic characteristics and wheel/rail wear evolution of the optimized profile are analyzed. The results show that the dynamic performance of the optimized rail profile has been improved. The maximum wear depth of the optimized rail profile is reduced by 15.63% when passing a total weight of 16 Mt. The wheel wear depth of S1002CN profile contact with CHN60OPT is reduced by 4.8%. The proposed GFC method can quickly generate a new rail profile and has good engineering significance for rail grinding. The GFC-KSM-NSGA- II method can be used to optimize the rail profiles for high-speed lines, and it can further guide the operation and maintenance.

The existing multi-objective wheel profile optimization methods mainly consist of three sub-modules: (1) wheel profile generation, (2) multi-body dynamics simulation, and (3) an optimization algorithm. For the first module, a comparably conservative rotary-scaling fine-tuning (RSFT) method, which introduces two design variables and an empirical formula, is proposed to fine-tune the traditional wheel profiles for improving their engineering applicability. For the second module, for the TRAXX locomotives serving on the Blankenburg–Rübeland line, an optimization function representing the relationship between the wheel profile and the wheel–rail wear number is established based on Kriging surrogate model (KSM). For the third module, a method combining the regression capability of KSM with the iterative computing power of particle swarm optimization (PSO) is proposed to quickly and reliably implement the task of optimizing wheel profiles. Finally, with the RSFT–KSM–PSO method, we propose two wear-resistant wheel profiles for the TRAXX locomotives serving on the Blankenburg–Rübeland line, namely S1002-S and S1002-M. The S1002-S profile minimizes the total wear number by 30%, while the S1002-M profile makes the wear distribution more uniform through a proper sacrifice of the tread wear number, and the total wear number is reduced by 21%. The quasi-static and hunting stability tests further demonstrate that the profile designed by the RSFT–KSM–PSO method is promising for practical engineering applications.

Wheel hollow wear is a serious problem of high-speed EMUs (HSE). The wheel wear characteristics of the CRH5 HSE is investigated by the test data and simulation results. Then an HSE dynamics model and wheel wear model are established. Two assessment indicators for wheel hollow wear are proposed, the wheel wear simplification index and the contact fatigue index. Finally, some suppression measures of wheel hollow wear are proposed. The results showed that The wheel wear simplification index is calculated simply and with strong engineering applicability. The fatigue index can effectively assess the fatigue level of different hollow wear. The vehicle with the larger wheel profile hardness, the larger equivalent damping and the smaller node stiffness of the anti-yaw damper, the rail profile grinding can effectively suppress the wheel hollow wear of HSE. The research provides ideas for the design of bogies for HST.