Optimization of Third Rail End Elbow Based on NURBS

[Objective] In order to improve the collision performance of the end elbow of the shoe-rail system and enhance the current collection quality, it is necessary to carry out the optimization research on the third-rail end elbow based on NURBS (Non-Uniform Rational B-Spline). [Method] Taking the end elbow of a certain metro line in Wuhan as example, an optimization design for the end elbow is carried out based on the concepts of parametric design and multi-objective optimization. According to the collision simulation of the end elbow of the shoe-rail system under the working condition of 120 km/h train running speed, the evaluation indicators of the current collection quality of the shoe-rail system under high speed working conditions are determined. The cross-section stretching curve of the end elbow is established through NURBS. A finite-element model of the curved end elbow is established by using the ANSYS Parametric Design Language. Taking the control point coordinates of the cross-section stretching curve as design variables, the optimization objectives are selected through main effect analysis, and the value range of the design variables is clarified. Based on NSGA-II (Non-dominated Sorting Genetic Algorithm II), a multi-objective optimization model of the curved end elbow is established, and the optimal solution is selected through the non-dominated sorting method and the min-max regret value method. [Result & Conclusion] According to the results of the main effect analysis, the bending-in collision force, bending-out collision force, total offline time, and the maximum impact acceleration are selected as the optimization objectives, and the maximum single offline time and the number of collisions are taken as the constraint conditions. After optimization, the current collection quality of the end elbow of the shoe-rail system is improved. When the train running speed is 120 km/h, the total offline time and the maximum single offline time are significantly optimized, with a reduction of 80.77% and 89.96% respectively. The corner entry impact force and the corner exit impact force are reduced by 32.26% and 44.03% respectively. When the train running speeds are 40 km/h and 80 km/h, all indicators are reduced by more than 20%.