Algorithm development for modelling dynamic stiffness of driveshaft center bearing bushing

Abstract

Most of the noise and vibration problems caused by the driveshaft system on commercial vehicles occur due to the angular velocity variation of the cardan joint and are transmitted to the driver through the center bearing group, which is the connection point of the driveshaft to the chassis. Therefore, modeling the rubber element in the center bearing group is crucial. In this study, a Python algorithm has been developed that examines the experimental data as seen in Figure A, according to the defined boundary conditions and determines the most ideal model.Purpose: The primary objective of this study is to develop an algorithm in Python that improves the accuracy of modeling while reducing the time required for optimization. The algorithm aims to find the optimum number of elements, element types, and configurations based on parallel and series sequences of elements in the mathematical model for simulating the dynamic response characteristics of a rubber compound.Theory and Methods: Developing a mathematical model for rubber compounds and selecting spring and damping coefficients is tough due to dynamic stiffness changes. But an accurate model can simulate the center bearing's dynamic traits and give noise and vibration data for all operational conditions. The algorithm evaluates configurations by changing element number, coefficients, and connection in parallel/series sequences, with modeling time spent on the best configuration. Accuracy is tested against shaker table data with error rate and root mean square error control.Results: A Python algorithm was developed to simulate dynamic characteristics of rubber compound using different coefficients. The optimal configuration was found to be two serial layers, with 1 damping element and 5 spring elements, with an error rate below 1%. The root mean square error (RMSE) was reduced to 0.51 after investigating the correlation coefficient. The final test with increased sample rate recorded an acceptable RMSE of 0.54 for the best-fit model configuration.Conclusion: An algorithm was created to speed up correlation in modeling rubber's dynamic stiffness. It successfully modeled the center bearing of a commercial vehicle's driveshaft and can improve modeling accuracy and reduce simulation time.