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Research on the Optimal Design of Engine Mounts by Minimizing Transfer Power based on Identifying Excitation and Admittance Matrix
ISSN: 1946-3995, e-ISSN: 1946-4002
Published June 15, 2015 by SAE International in United States
Citation: Dai, H., Jiang, W., and Huang, Y., "Research on the Optimal Design of Engine Mounts by Minimizing Transfer Power based on Identifying Excitation and Admittance Matrix," SAE Int. J. Passeng. Cars - Mech. Syst. 8(3):904-909, 2015, https://doi.org/10.4271/2015-01-2252.
Engine mounts play important roles in interior noise of automobiles. Decoupling optimal design of mounts has been researched for long, but reducing vibration power into body transmitted from engine can be a more intuitive way to improve NVH performance. Some approaches for minimizing transfer power through engine mounts based on finite element model were reported, whose disadvantages are lack of data and inaccuracy at high frequency in some cases. To get an analytic formula of transmitted power, a model considering coupled vibration between the body and the engine is presented here. An admittance function matrix is used to describe the dynamic relationship between the mounting points on the body side. Based on this admittance matrix measured on the full vehicle, and excitation forces identified with acceleration data measured on all mounts, the vibration equation of the coupled model can be established by using Lagrange's methodology. Vibrational response of mounting points, as well as the vibration power transmitted to the body in each direction of mounts, can be obtained by solving the equations in complex-frequency within band of 20Hz∼200Hz. The overall transfer power can be expressed by summation of each direction of all mounts. The particle swarm optimization algorithm is used to minimize the transmitted power and find out an optimum solution for stiffness of the rubber mounts. It is confirmed by examples that power transmitted to the body was reduced observably after optimized with this method, which is better than optimization with TRA decoupling method.