侯文彬+单春来+于野+张红哲

摘 要：针对在模块化平台中筛选共享变量的问题，受协同优化算法使用一致性约束函数对各子优化问题进行一致性统筹的启发，提出一种基于一致性约束的优化算法.在系统级优化中使用非支配排序的遗传算法NSGA-Ⅱ对该多目标优化问题进行求解后得到Pareto解集，利用模糊聚类算法对解集中的每组解进行综合性能的评价并选优，根据最终筛选出的最优解即可实现共享变量的筛选.相比以往常用的基于经验或灵敏度的方法，该方法更严格地在子学科优化中以车身性能为目标函数，在系统级优化中进行共享度的优化，并且可根据系统级优化结果筛选出局部共享变量.以SUV、两厢掀背车和三厢轿车为算例，使用该方法有效地筛选出3款车型的全局共享变量、局部共享变量和非共享变量，对该方法的可行性和有效性进行了验证.

关键词：一致性约束；协同优化；模糊聚类；模块化；产品族

中图分类号：U462.1 文献标志码：A

Selection Method of Sharing Modules for Modular Product Family

HOU Wenbin1，SHAN Chunlai1，YU Ye1，ZHANG Hongzhe2

（1. School of Automotive Engineering， Dalian University of Technology， Dalian 116024，China；

2. School of Mechanical Engineering， Dalian University of Technology， Dalian 116024，China）

Abstract：For sharing modules selection in the modular platform design， an algorithm based on constraints was proposed， which was inspired by Collaborative Optimization using the constraints to coordinate the System Level Optimization and Sub-system Level Optimization. In this algorithm， NSGA-Ⅱ was used in the System level to solve the Multidisciplinary Design Optimization problem， and a Pareto set was gotten. By using the fuzzy set theory to evaluate each equation in the Pareto set， the optimum solution was easily picked out， and the sharing modules selection was realized in this way. At last， this method was verified by using an application example constituted by involving a SUV， a hatchback， and a sedan.

Key words：consistency constraints； collaborative optimization； fuzzy set theory； modular； product family

随着汽车生产的全球化，制造水平的日益提高，以零部件超前发展为重心的模块化技术已经成为时下各大汽车制造厂商的核心技术，模块化产品族的设计制造方式也无疑是企业获得持续竞争力的最关键的内容[1-2].模块化设计作为新型产品平台构建的主要策略，以零部件标准化和多样化的方式提高了产品族内不同产品之间的零部件共享度并保证了产品的多变性[3].

Torstenfelt等[4]基于模块化平……