Current research papers use simulated load spectrums to assess bogie frames’ fatigue life but seldom consider traction and braking loads. Traction and braking loads play important roles in predicting fatigue life in high-speed and heavy haul operational scenarios. Hence, there is a research gap in terms of the consideration of longitudinal load spectrums while assessing bogie frames’ fatigue life. This paper presents research about this topic. A virtual prototype technique available in literature has been extended for this purpose; it uses multibody dynamics and finite element techniques to simulate the behaviour of bogie frames under real operational service loads. As a result, the special simulation methodology has been developed in this work and it includes the unique integration of simulation approaches that includes train dynamics, locomotive dynamics with the consideration of a traction control algorithm and the adopted fatigue life calculation method. This paper gives numerical examples of a rigid-flexible coupled dynamic railway vehicle model subjected to longitudinal forces. Road Environment Percent Occurrence Spectrum (REPOS) load spectrums of the bogie frame were developed from a whole-trip train simulation on a real route. The spectrums are then used to predict locomotive the bogie frame’s fatigue life. The results of the bogie frame fatigue life evaluation performed in this paper show that fatigue lives at the roots of traction rod seats under longitudinal load spectrums are shorter than their fatigue life under vertical load spectrums.
To obtain improved comprehensive crashworthiness criteria for a B-type subway train, the influence laws of the vehicle design collision weight M and empty stroke D on the train’s collision responses were investigated, and multi-objective optimization and decision-making were performed to minimize TS (total compression displacement along the moving train) and TAMA (the overall mean acceleration along the moving train). Firstly, a one-dimensional train collision dynamics model was established and verified by comparing with the results of the finite element model. Secondly, based on the dynamics model, the influence laws of M and D on the collision responses, such as the energy-absorbing devices’ displacements and absorbed energy, vehicles’ velocity and acceleration, TS, TAMA and the coupling correlation effect were investigated. Then, surrogate models for TS and TAMA were developed using the optimal Latin hypercube method (OLHD) and response surface method (RSM), and multi-objective optimization was conducted using the particle swarm optimization algorithm method (MPOSO). Finally, the entropy method was used to obtain the weight coefficients for TS and TAMA, and multi-objective decision-making was performed. The results indicate that D and M significantly affect the compression displacements and energy absorption of the first three collision interfaces, but have limited impact on the last three collision interfaces. The velocity versus time curves of vehicle M1 and M2 are shifted and parallel with different D. However, the velocity versus time curves of all the vehicles are shifted but gradually divergent with different M. The maximum collision instantaneous accelerations of the vehicles are directly determined by M, but are only slightly affected by D. Under the coupling effect, all concerned collision responses are strongly correlated with M; however, the responses are weakly correlated with D except for the compression displacement at the M2-M3 collision interface and the maximum collision instantaneous acceleration of vehicle M2. The comprehensive crashworthiness criteria of the B-type subway train were significantly improved after multi-objective optimization and decision-making. The research provides more theoretical and engineering application references for the subway train crashworthiness design.
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