Identification of Damping Parameters of Hydraulic Engine Mount by Volterra Series Theory 2021-01-0666
Hydraulic engine mounts are a typical non-linear system. Compared with rubber mount, it has good dynamic characteristics under different excitation, so it has been widely used in automobiles. The vibration isolation performance of hydraulic engine mounts is related to its dynamic characteristics, and its dynamic characteristics are closely related to mount model parameters. Therefore, parameter identification of hydraulic engine mounts has become a prerequisite for studying its dynamic characteristics and even vibration isolation performance. Aiming at the damping parameters of mount model parameters, based on Volterra series theory, this paper takes the inertial track-floating decoupler hydraulic engine mount as the research object, and proposes the identification method of the damping phase angle of the hydraulic engine mount and the damping parameters of the fluid damping mechanism. With the known output and some structural parameters, the relationship between the output of the nonlinear system and the damping parameters under a certain sinusoidal input excitation is studied. The damping parameters of the fluid damping mechanism can be obtained simply, and the error between the identification value of the damping parameters obtained under a certain range of excitation frequency and the experimental parameters value can be kept within 3%. Besides, the damping phase angle of the hydraulic engine mount identified by Volterra series theory has been compared and verified by the averaging method, which also shows good consistency. It can be proved that the Volterra series method mentioned in this paper can be used to indirectly obtain the main unknown damping parameters from the component to the whole of the hydraulic engine mount.
Citation: Gao, Z., Zhen, D., and Liu, X., "Identification of Damping Parameters of Hydraulic Engine Mount by Volterra Series Theory," SAE Technical Paper 2021-01-0666, 2021. Download Citation
ZhongZheng Gao, Dong Zhen, Xiao-Ang Liu