汽车轮毂轴承疲劳寿命分析及结构优化设计

发布时间：2018-06-13 10:54

本文选题：轮毂轴承 + 载荷分布　；参考：《南京航空航天大学》2016年硕士论文

【摘要】：随着国内汽车产量的增加,汽车零部件行业迅猛发展。轮毂轴承作为汽车关键的零部件之一,一直是人们关注的重点。国内的轮毂轴承和国外的相比,还有很大的差距。因此,对其开展疲劳寿命分析以及结构优化设计有着重要的意义。本文首先对轮毂轴承疲劳寿命进行了理论分析。采用静力学法,建立轮毂轴承力学分析模型,研究了在径向、轴向以及力矩载荷联合作用下的轮毂轴承的内部载荷分布。此外,综合考虑滚动体和滚道的影响,基于修正的Lundberg-Palmgren理论,分析了不同的载荷参数以及结构参数对轮毂轴承疲劳寿命的影响规律。然后,基于有限元分析结果,对轮毂轴承进行了疲劳寿命仿真分析。在Catia中建立了轮毂轴承三维模型,采用Hypermesh和ANSYS对轮毂轴承进行有限元建模,并展开了力学性能分析。同时,根据力矩刚性试验,将仿真结果和试验结果进行对比,验证了有限元模型的正确性。在此基础上,利用应力分析结果,采用nCode DesignLife对轮毂轴承进行了疲劳寿命仿真分析,确定了容易发生疲劳失效的部位,为进一步的设计与优化提供了参考。最后,对轮毂轴承进行多目标优化设计。选取额定动载荷与额定静载荷作为目标函数,以轮毂轴承主要内部结构参数为设计变量,采用多目标粒子群算法(MOPSO)对轮毂轴承进行了结构优化设计。优化结果表明,各目标性能指标都得到了不同程度的提升。此外,通过有限元仿真对轮毂轴承优化前后的疲劳寿命以及应力分布进行对比,验证了优化结果的有效性。
[Abstract]:With the increase of domestic automobile output, auto parts industry develops rapidly. As one of the key parts of automobile, hub bearing has always been the focus of attention. Domestic hub bearings and foreign comparison, there is a big gap. Therefore, it is of great significance to carry out fatigue life analysis and structural optimization design. In this paper, the fatigue life of hub bearing is analyzed theoretically. The mechanical analysis model of hub bearing is established by statics method. The internal load distribution of hub bearing under the combined action of radial axial and torque loads is studied. In addition, based on the modified Lundberg-Palmgren theory, the effects of different load parameters and structural parameters on the fatigue life of hub bearings are analyzed. Then, based on the results of finite element analysis, the fatigue life of hub bearing is simulated. The three-dimensional model of hub bearing is established in Catia. The finite element model of hub bearing is modeled by HyperMesh and ANSYS, and the mechanical properties are analyzed. At the same time, the correctness of the finite element model is verified by comparing the simulation results with the experimental results according to the moment rigidity test. Based on the results of stress analysis, the fatigue life of hub bearing is simulated by nCode Design Life, and the position of fatigue failure is determined, which provides a reference for further design and optimization. Finally, the multi-objective optimization design of hub bearing is carried out. Selecting rated dynamic load and rated static load as objective function and taking the main internal structure parameters of hub bearing as design variables, multi-objective particle swarm optimization algorithm (MOPSO) is used to optimize the structure of hub bearing. The optimization results show that each target performance index has been improved to varying degrees. In addition, the fatigue life and stress distribution of hub bearing before and after optimization are compared by finite element simulation, which verifies the effectiveness of the optimization results.
【学位授予单位】：南京航空航天大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：U463.343

【参考文献】