Abstract
The auxiliary converter cabinet (ACC) of electric multiple unit vehicles guarantees the regular operation of electrical equipment. This article develops and optimizes a parametric model of the ACC based on lightweight composite pyramidal lattice materials to improve its performance. To make the sequential optimization procedure automatically closed-loop, an ACC model with parameter interfaces is built. A representative volume element model is adopted to obtain the physical properties of the pyramidal lattice structure. After global sensitivity analysis, three popular multi-objective optimization algorithms- multiobjective particle swarm optimization (MOPSO), non-dominated sorting genetic algorithm-III (NSGA-III) and multi-objective evolutionary algorithm based on decomposition (MOEAD)—are used to optimize the lattice ACC. MOPSO obtained the best results, and the lattice structure greatly improved the performance of the ACC in terms of random vibration and shock conditions.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call