The Finite Element Analysis Of The Vehicle Suspension Control Arm And Fatigue Life Prediction

Control arm is an important transmission and guide element of the vehicle suspension system, its main role is to deliver a variety of forces and torques. Therefore, it is required that the control arm has a certain mechanical properties such as stiffness, collapse force under tension and compression,natural frequency and so on. As an safety parts of the vehicle, control arm offen comes into being fatigue fracture when the car is running, which directly affect the driving safety and handling stability of the car, and it will endanger people’s lives and safety. Therefore, the finite element analysis and fatigue life prediction of the control arm is necessary.Taking the upper control arm of one vehicle as an objective, the finite element model has been established in this paper, and the stiffness, collapse force under tension and compression, natural frequency has been calculated. And the corresponding test in Y direction has been finished to verify the result of finite element analysis. It is shown that the test and finite element analysis of the collapse to the control arm are basically identical. The modal analysis results and the reference natural frequency comparison shows that, natural frequencies of the control arm meeting the performance requirements, and the system will not resonance.The stress and strain has been extracted at the critical point of the control arm, and two different fatigue life prediction models are established based on the critical plane approach. Four kinds of theoretical estimation method have been conducted so that the fatigue characteristics of the control arm material parameter have been calculated. The fatigue damage parameters have been calculated for different fatigue life prediction models when the critical plane have been confirmed. Finally, the fatigue life test of the control arm is carried out. The result shows that the prediction life and average life of the test of the two models are in 2 times of the error bands. And the two models are suitable for the fatigue life prediction of the control arm. The choice of prediction model is related to the estimation method of fatigue characteristic parameters.