Research On Fatigue Life Of Car Wheel Bearing Based On Grey Prediction Model

Wheel bearing is one of the important parts for the smooth running of the car.Its excellent performance is directly related to the comfort and safety of the car.Therefore,the research and analysis of the mechanical properties and fatigue life of automobile wheel bearings are very important for the development of bearings.In this paper,firstly,a vehicle model of a car is built using dynamics simulation software.At the same time,in order to better simulate the real road conditions,a three-dimensional random road model is established as an input stimulus for vehicle simulation by using simulation means.The effect of the vehicle model on the load of the hub bearing under different vehicle speeds,different road levels and the combination of the two is analyzed,and the loadtime history at the hub bearing under the corresponding working conditions is obtained.This is the subsequent finite element analysis of the hub bearing and The estimation of fatigue life provides the basis for loading.Secondly,according to the structural characteristics of the third-generation hub bearing,its structure was simplified,a three-dimensional finite element model of the hub bearing was established,and a static analysis was performed.The stress distribution cloud map of the bearing was obtained and the dangerous parts of the bearing were determined..Based on the results of the static analysis and the load-time series obtained in the previous chapter,the fatigue life of the bearing was estimated.At the same time,simulation methods were used to design the orthogonal test of bearing structure parameters and load on bearing fatigue life under the four factors and three levels.Taking into account the constraints of test period and cost,bench tests were performed in only one of the cases to verify The correctness of the finite element simulation results is shown.Finally,combined with the simulation life data obtained from the orthogonal design experiment in the previous chapter,the application of the gray system theory in the processing and prediction of bearing life data is studied and analyzed.Based on the established original GM(1,1)model,the prediction accuracy is poor.Problems,on the basis of data preprocessing,a GM(1,N)model that relies on factor variables to correct the main behavior variables is proposed.The model comparison and verification further improves the prediction accuracy,but the required prediction results cannot be achieved.Finally,a gray GM(1,N)model based on residual correction is established by introducing a residual correction method to achieve a good prediction effect.It shows that the GM(1,N)model with residual error correction can provide a reference for the change trend prediction of bearing life data in the absence of experimental verification,and can achieve the purpose of shortening the test time and saving costs in the actual process.