摘要
第3代汽车轮毂轴承铆合装配涉及内圈-内法兰过盈装配和内法兰轴端铆合装配过程,对轴向卡紧力和轴承游隙控制十分重要,直接决定着轮毂轴承的使用性能。为进一步探索轴向卡紧力的形成机理及精确控制方法,结合现有研究成果,以时间为线索简要介绍了轮毂轴承轴端铆合设备构成、工艺特点及主要性能参数,梳理了轴端铆合装配数值模拟过程及其关键模拟技术,重点综述了轴端铆合工艺参数对轴向卡紧力、内圈变形量、疲劳寿命等结构和性能关键指标的影响,以及有限元分析和智能算法在轮毂轴承设计及优化中的应用,最后对轮毂轴承轴端铆合装配的研究方向进行了展望。
The riveting assembly of the third generation wheel hub bearings involves the inner ring-inner flange interference assembly and the shaft-end riveting assembly of the inner flange,which is very important in the control of axial clamping force and bearing clearance,and directly determines the service performance of the wheel hub bearings.To further explore the formation mechanism and precise control method of the axial clamping force,combining with the existing research,the constitute,process characteristics and main performance parameters of the shaft end riveting apparatus of wheel hub bearings were briefly introduced at time sequence.The numerical simulation processes and key simulation technologies of the shaft-end riveting assembly were combed.The influences of the shaft end riveting process parameters on the key structural and performance indexes,such as the axial clamping force,deformation of the inner ring and fatigue life along with the application of finite element analysis and intelligent algorithm in the design and optimization of wheel hub bearing were summarized.Finally,the research directions of shaf-end riveting assembly were prospected.
作者
王友
熊伟
梅松
刘德政
李江全
WANG You;XIONG Wei;MEI Song;LIU De-zheng;LI Jiang-quan(Hubei Key Laboratory of Power System Design and Test for Electrical Vehicle,Hubei University of Arts and Science,Xiangyang 441053,China;School of Mechanical Engineering,Hubei University of Arts and Science,Xiangyang 441053,China;Hubei New Torch Science&Technology Co.,Ltd.,Xiangyang 441004,China)
出处
《塑性工程学报》
CAS
CSCD
北大核心
2020年第9期1-11,共11页
Journal of Plasticity Engineering
基金
湖北省教育厅科学技术研究计划青年人才项目(Q20202605)
“机电汽车”湖北省优势特色学科群(XKQ2020006)
教育部科技发展中心高校产学研创新基金资助项目(2018A04017)。
关键词
轮毂轴承
铆合装配
多目标优化
智能算法
有限元分析
wheel hub bearings
riveting assembly
multi-objective optimization
intelligent algorithm
finite element analysis