<div class="section abstract"><div class="htmlview paragraph">As an important vibration damping element in automobile industries, the vibration transmitted from the engine to the frame can be reduced effectively because of rubber mount. The influence of preload on the static characteristics of rubber mount and the constitutive parameters identification of Mooney-Rivlin model under preload were studied. Firstly, a test rig for stiffness measurement of rubber mount under preload was designed and the influence of preload on the force versus displacement of mount was studied. Then, the model for estimating force versus displacement of rubber mount was established. The response surface model for parameters identification was established. And the identification method for estimating parameters of Mooney-Rivlin model of rubber mount was proposed with the crow search algorithm. Taking the rubber mount as the research object and taking the parameters of Mooney-Rivlin model as the variables. Then, using response polynomials corresponding to different force-displacement curves as the objective functions, a least squares method is used to ontain constitute parameters of Mooney-Rivlin model. The force versus displacement for the mount is estimated using the obtained parameters of Mooney-Rivlin model along with the developed model. The results show that the relative errors calculated with parameters identified under preload are keeping in 10% in all working conditions. The real force performance of the rubber mount is better reflected by the parameters identified under preload. The parameters identification method proposed in this paper can provide reference for the accurate identification of constitutive parameters.</div></div>
<div class="section abstract"><div class="htmlview paragraph">As an important vibration damping element in automobile, the rubber mount can effectively reduce the vibration transmitted from the engine to the frame. In this study, a method of parameters identification of Mooney-Rivlin model by using surrogate model was proposed to more accurately describe the mechanical behavior of mount. Firstly, taking the rubber mount as the research object, the stiffness measurement was carried out. And then the calculation model of the rubber mount was established with Mooney-Rivlin model. Latin hypercube sampling was used to obtain the force and displacement calculation data in different directions. Then, the parameters of the Mooney-Rivlin model were taken as the design variables. And the error of the measured force-displacement curve and the calculated force-displacement curve was taken as the system response. Two surrogate models, the response surface model and the back-propagation neural network, were established. In addition, their prediction accuracy was compared and analyzed. For the prediction accuracy, the response surface model is more accurate than the back-propagation neural network. Finally, the surrogate model was combined with crow search algorithm to obtain the minimum error between the measured force-displacement curve and the calculated force-displacement curve. And the parameters of the Mooney-Rivlin model were identified with the presented method. The results show that the relative errors between the calculated stiffness and the measured stiffness in the three directions are less than 3%, which proving the identified parameters are accurate.</div></div>
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