结合Kriging与改进NSGA-Ⅱ的RV减速器优化

将体积、扭转刚度和传动效率作为优化目标,构建了RV减速器的多目标优化模型.为提高设计效率并节省计算开销,结合NXOpen C++与Abaqus Python二次开发技术,建立了部分扭转刚度的Kriging代理模型.为解决多目标混合整数非线性规划问题,提出了MP-NSGA-Ⅱ(mixed population-NSGA-Ⅱ)算法,改进了离散变量的编码方案.利用PySide2开发了一体化结构RV减速器设计软件,并分析了优化目标间的耦合关系.将熵权法选优后的结构参数与BAJ-25E比较,验证了该方法的有效性.

Optimization of an RV reducer by integrating Kriging with improved NSGA-II

With the volume, torsional stiffness and transmission efficiency taken as the optimization objectives, a multi-objective optimization model of the RV reducer was constructed. To improve the design efficiency and save the computational cost, a Kriging surrogate model with a partial torsional stiffness was established based on the NXOpen C++ and the Abaqus Python secondary development technology. To solve the multi-objective mixed-integer nonlinear-programming problem, an MP-NSGA-II (mixed population-NSGA-II) algorithm was proposed, and the coding scheme for discrete variables was improved. An integrated RV reducer design software was developed by using PySide2, and the coupling relationship between optimization objectives was analyzed. The structural parameters selected by the entropy method were compared with BAJ-25E, and the effectiveness of this method was verified.