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.

电动车的辅助变流柜（ACC）保证了电气设备的正常运行。本文开发并优化了基于轻质复合金字塔晶格材料的 ACC 参数模型，以提高其性能。为了使序列优化过程自动闭环，建立了带有参数接口的ACC模型。采用具有代表性的体积元模型来获得锥体晶格结构的物理性质。经过全局敏感性分析，使用了三种流行的多目标优化算法——多目标粒子群优化（MOPSO）、非支配排序遗传算法-III（NSGA-III）和基于分解的多目标进化算法（MOEAD）。优化晶格ACC。