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In order to systematically grasp the changes and matching characteristics of wheel and rail profiles of high speed railway (HSR) in China, 172 rail profile measurement points and 384 wheels of 6 high-speed electric motive unites (EMUs) were selected on 6 typical HSR lines, including Beijing–Shanghai, Wuhan–Guangzhou, Harbin–Dalian, Lanzhou–Xinjiang, Guiyang–Guangzhou and Dandong–Dalian for a two-year field test.

Based on the measured data, the characteristics of rail and wheel wear were analyzed by mathematical statistics method. The equivalent conicity of wheel and rail matching in a wheel reprofiling cycle was analyzed by using the measured rail profile.

Results showed that when the curve radius of HSR was larger than 2,495 m, the wear rate of straight line and curve rail was almost the same. For the line with annual traffic gross weight less than 11 Mt, the vertical wear of rail was less than 0.01 mm. The wear rate of the rail with the curve radius less than 800 m increased obviously. The wheel tread wear of EMUs on Harbin–Dalian line, Lanzhou–Xinjiang line and Dandong–Dalian line was relatively large, and the average wear rate of tread was about 0.05–0.06 mm·(10,000 km)⁻¹, while that of Beijing–Shanghai line, Wuhan–Guangzhou line and Guiyang–Guangzhou line was about 0.03–0.035 mm·(10,000 km)⁻¹. When the wear range was small, the equivalent conicity increased with the increase of wheel tread wear. When the wear range of wheel was wide, the wheel–rail contact points were evenly distributed, and the equivalent conicity did not increase obviously.

This research proposes the distribution range of the equivalent conicity in one reprofiling cycle of various EMU trains, which provides guidance for the condition-based wheel reprofiling.

Mountain metro vehicles have unique wheel wear characteristics due to the complex flat and longitudinal lines. With a combination of flat and longitudinal curved tracks, the traction and braking conditions are more frequent in mountain metro vehicles. This paper aims to analyze the wheel wear characteristics of mountain metro vehicles in complex flat and longitudinal lines.

A dynamic model of the mountain metro vehicle and a wear model are established to analyze the dynamic and wheel wear characteristics of mountain metro vehicles. The wheel wear law of mountain metro vehicles under complex track conditions is analyzed, and the suppression measure based on variable stiffness rotary arm nodes of mountain metro vehicles is proposed.

The results showed that the maximum wheel wear depth without considering the ramp track and considering the ramp track are 3.283 mm and 3.717 mm, respectively; the maximum wheel wear depth increases by 13.2%. Wheel wear can be effectively suppressed by the variable stiffness rotary arm model, and the maximum wear depth of the wheel profile is 3.316 mm, which is reduced by 10.79% compared with the constant stiffness model.

A dynamic model of a mountain metro vehicle is established, and the metro vehicle wheel wear under the large ramps under the traction and braking conditions is analyzed, and the metro vehicle wheel wear suppression measure based on variable stiffness rotary arm nodes is proposed.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2024-0247

This study aims to reduce the redundant weight of the anti-roll torsion bar brought by the traditional empirical design and improving its strength and stiffness.

Based on the finite element approach coupled with the improved beluga whale optimization (IBWO) algorithm, a collaborative optimization method is suggested to optimize the design of the anti-roll torsion bar structure and weight. The dimensions and material properties of the torsion bar were defined as random variables, and the torsion bar's mass and strength were investigated using finite elements. Then, chaotic mapping and differential evolution (DE) operators are introduced to improve the beluga whale optimization (BWO) algorithm and run case studies.

The findings demonstrate that the IBWO has superior solution set distribution uniformity, convergence speed, solution correctness and stability than the BWO. The IBWO algorithm is used to optimize the anti-roll torsion bar design. The error between the optimization and finite element simulation results was less than 1%. The weight of the optimized anti-roll torsion bar was lessened by 4%, the maximum stress was reduced by 35% and the stiffness was increased by 1.9%.

The study provides a methodological reference for the simulation optimization process of the lateral anti-roll torsion bar.