Methodology to optimize wedge suspensions of three-piece bogies of railway vehicles

Abstract

Wedge suspensions are critical systems for three-piece bogies. This paper proposes a methodology to optimize wedge suspensions using white-box suspension models, dynamic simulations of railway vehicle systems, parallel multi-objective Particle Swarm Optimization (pMOPSO), and parallel multi-objective Genetic Algorithm (pMOGA). Two types of original wedge suspensions with three different toe angle configurations were modeled and compared. Four case studies were carried out to prove the feasibility of the optimization methodology. A series of optimized designs were identified using the Pareto Front technique. Demonstrative optimized designs were compared with the original designs. Results show that wedge suspensions with the toe-in configuration provide better dynamic performance for freight wagons. Significant reductions to the maximum wheel/rail contact forces can be achieved by the optimized designs. Linear speed-up was achieved by using the parallel computing technique.

Car and train platoon simulations

“…The platoon simulation method that can be used for both car and train platoon simulations is shown in Figure 4. It uses parallel computing enabled by the Message Passing Interface (MPI) technique (Wu et al, 2018(Wu et al, , 2020. From an overall perspective, processes above the purple dashed line are initialisation for time integration cycles, that is, simulation cycles.…”

Train braking simulation with wheel-rail adhesion model

“…The model used in this paper has the structure shown in Figure 4 and can be expressed as where F N1 is the normal force between side frame and wedge; F N2 is the normal force between wedge and bolster; z b is the vertical displacement of bolster; γ is the toe angle or the vertical inclination angle of the wedge-side frame contact surface; μ 1 is the coefficient of friction on wedge-side frame contact surface; α is the wedge angle; μ 2 is the coefficient of friction on wedge-bolster contact surface; m w is the wedge mass; m b is the bolster mass; G w is the weight of the wedge; G b is the weight of the bolster; F kb is the bolster spring force; F cp is the centre plate force; and F kw is the wedge spring force. This model is based on [41] and was developed in [42]. It has considered the dynamics characteristics and relevant geometries of all components of the wedge suspension system.…”

Parallel computing in railway research

“…More information regarding MPI can be accessed via the online book of Barney [34]. In railway research, the MPI has found many applications [7,[11][12][13][21][22][23]31,[35][36][37][38][39][40][41][42][43]; it is one of the most widely used parallel computing enabling techniques. In the authors' opinion, MPI is very suitable for parallel co-simulations and parallel optimisations, as presented in References [31] and [42] respectively, since they have very independent parallelised computing tasks.…”

“…In addition to these applications, parallel GA has been used to optimise railway vehicle aerodynamics [77], truss structures [58], shock absorber distribution for railway tunnels [36], draft gear designs [37][38][39] and wedge suspension designs [42]. Parallel PSO has been used for optimisations of passenger traffic prediction [69], draft gear designs [37][38][39] and wedge suspension designs [42]. Evolutionary Algorithm optimisation has been used for optimisations of railway vehicle structures [33], and railway vehicle dynamics design [12].…”