响应面法与多目标遗传算法在桥壳优化上应用  

Application of Response Surface Methodology and Multi-Objective Genetic Algorithm in Optimization of Axle Housing

作　　者：王强[1] 苏小平[1] 许金龙[1] WANG Qiang;SU Xiao-ping;XU Jin-long(College of Mechanical and Power Engineering,Nanjing Tech University,Jiangsu Nanjing 211800,China)

机构地区：[1]南京工业大学机械与动力工程学院

出　　处：《机械设计与制造》2019年第9期71-76,共6页Machinery Design & Manufacture

基　　金：江苏省自然科学基金项目(BK20130941)

摘　　要：桥壳作为后桥的核心,其设计强度和寿命直接关系到整车的使用寿命及可靠性。首先,根据车辆实际行驶条件抽象出三大模拟工况,基于限元模型求解出桥壳的应力分布。Bump工况下桥壳中段处应力最大,为50.97MPa。其次,在MSC.Fatigue软件得到桥壳的疲劳寿命云图。然后,构建以寿命为应变量的响应面模型并运用NSGA-Ⅱ多目标优化的遗传算法对桥壳进行优化设计,优化后的寿命增加了22%,静应力减少了约10%,在质量减少的基础上实现了桥壳的寿命延长。最后,对优化前和优化后的桥壳分别进行台架试验,垂直弯曲疲劳试验的结果是寿命延长了18%,与仿真结果接近,符合相关规定,证明了优化设计的正确性。As the core of the rear axle,the design strength and service life of the axle housing are related to the service life and reliability of the whole vehicle directly. First of all,three simulation cases are abstracted according to the actual vehicle running conditions. And the stress distribution of the axle housing is solved based on the finite element model. Under the Bump working condition,the stress in the middle of the axle shell is the biggest,which is 50.97 MPa. Secondly,the fatigue life of the axle housing is obtained by MSC. Fatigue. Thirdly,The response surface model with life as the dependent variable is constructed.And the genetic algorithm of multi-objective optimization of NSGA-II is used to optimize the design of the axle housing. The optimized life increased by 22%,and the static stress decreased by about 10%. The life span of the axle housing was prolonged on the basis of reduced mass. Finally,bench tests are carried out on the axle housings before and after optimization respectively. The result of the vertical bending fatigue test is that the service life is prolonged by 18%,which is close to the simulation result and conforms to the relevant regulations. The correctness of the optimization design is proved.

关 键 词：桥壳 响应面 多目标遗传算法 疲劳寿命 

分 类 号：TH16[机械工程—机械制造及自动化] U463.32[机械工程—车辆工程]