Multi-objective optimisation of a metro wheel profile to reduce wheel flange wear and RCF considering the distribution density of wheel−rail contact points

In this study, the problem of severe wheel flange wear and tread rolling contact fatigue (RCF) of metro wheels with two wheel profiles, i.e. the LM-30 profile and the DIN5573-30 profile, is investigated. The contact characteristics of the two profiles are compared to analyse the causes of wheel flange wear and RCF. Indices combining the density distribution of contact points are proposed to evaluate the wheel flange wear and RCF. The optimisation region of the wheel profile is defined by eight arc parameters, which is derived from the tangency of the arcs. A back-propagation neural network is constructed as a surrogate model for the design variables and the objective function. Four intelligent optimisation algorithms are compared and used to solve the optimisation problem. The vehicle—track dynamic model and the wheel wear and RCF prediction model are used to verify the performance of the optimised profile. The results show that the critical speed of the optimised profile is between that of the LM profile and that of the DIN5573 profile, and the curving performance of the optimised profile is significantly improved. At the same time, the optimised wheel profile can reduce wheel flange wear and tread RCF.