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Purpose: The inherent conflict between hunting stability and curve negotiation performance is a well-known challenge in railway vehicle dynamics. Stiff axle guidance of bogies can achieve high stability while good curving performance requires longitudinally soft guidance. To overcome the conflict, the application of hydraulic arm bushings with frequency-dependent stiffness to a passenger coach with small-radius wheels is discussed as a case study in this work. Methods: This type of bushing could provide low longitudinal stiffness when the wheelset yaw frequency is below 1 Hz, and the bushing stiffness becomes much larger when the wheelset yaw frequency exceeds 2 Hz. This frequency-dependent stiffness characteristic enables to achieve high stability on straight tracks and good curving performance in curves, and it can be represented by the Zener model. Four schemes including the nominal guiding design and three hydraulic arm-bushing designs are introduced, and the corresponding performances in various simulation scenarios, such as hunting stability, curving negotiation and long-term wheel wear behaviours, are compared by using the multibody simulations. Results: The critical hunting speeds for the four schemes SX31, SX3.9, SX1.6 and SX2.0 are 211, 209, 198 and 207 km/h respectively, and they are affected by the largest stiffness in the Zener model. Since the scheme SX1.6 has the smallest static stiffness in the Zener model, it generally has the best curve negotiation performance such as the lowest wheel-rail lateral force and the minimum wear number, and its long-term wheel wear volume is also the lowest among all schemes. Conclusion: Applying hydraulic arm bushings could significantly reduce the wheelset attack angle and the wear number in curves, especially in tight curves, which can be one of the countermeasures to reduce wear for small-radius wheels. Besides, low static stiffness and high dynamic stiffness are necessary for the arm bushing design to balance stability and curving performance.

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.