A method to evaluate stiffness and damping parameters of cabin suspension system for heavy truck

Abstract

Both stiffness and damping parameters of cabin suspension have important influences on the dynamic performance of cabin system for heavy truck. To theoretically study ride comfort of cabin system, the stiffness and damping parameter values of cabin suspension are often required. At present, there is no convenient method unless by bench test to accurately obtain all the stiffness and damping parameters; however, the cost of bench test is relatively high and inconvenient. In this article, according to the real cabin system of a heavy truck, a 3 degree-of-freedom cabin system linear model was presented and its vibration equations were built. By the tested cabin suspension excitations and seat acceleration response, based on curve fitting method, a stiffness and damping parameter identification mathematical model was established. With a practical example of cabin system, the stiffness and damping parameters were identified and validated by bench test. The results show that the built model and the proposed method are workable and lay a good foundation for the theoretical analysis and/or optimal design of cabin suspension to improve ride comfort.

Determination of Measurement Parameters for Vibration Analysis by Bus

“…Literatures [10] and [11] describe a Maximum Likelihood-based approximation to identify the parameters of a bus according to ARMA and ARMAX models. Another publication [12] represents a mathematical model to determine the stiffness and damping of a suspension of a heavy transport vehicle based on the curve fitting method. A curve fitting method was used to obtain the least square error function between the vertical acceleration power spectral density of the simulated seat and the measured power spectral density.…”

Ride Comfort Analysis and Multivariable Co-Optimization of the Commercial Vehicle Based on an Improved Nonlinear Model

“…On the one hand, the conventional analysis methods for ride comfort are still widely applied. Zhao et al [10] developed a linear cabin system model to identify the suspension parameters and validated the model by a bench test for the optimal design of a cabin suspension to improve ride comfort. Gong et al [11] proposed an optimization method based on a virtual and real prototype of an experimental integrated Kriging model for hydropneumatic suspension, showing a significant improvement in ride comfort.…”

“…It is not conducive to the optimization if we use all parameters as the design variables. In addition, the stiffness and damping have the greatest influence on the suspension characteristics and are coupled with one another to affect ride comfort [10], [13]. Therefore, the stiffness and damping coefficients of the suspensions, as well as the installation angle, are considered as design variables, such that (12), as shown at the bottom of this page.…”

Parameter identification of a fire truck suspension for vibration analysis

“…In [13]- [14] a maximum likelihood estimation method is presented to identify the parameters of a bus based on Auto-Regressive-Moving-Average (ARMA) and Auto-Regressive-Moving-Average model with eXogenous inputs (ARMAX) models. In [15] a mathematical model to identify the stiffness and damping of a heavy-duty truck suspension system is presented based on curve fitting method. Using curve fitting method the minimum of quadratic error function between the simulated seat vertical acceleration power spectral density and the measured power spectral density was taken.…”