Grey-box modeling of a motorcycle shock absorber for virtual prototyping applications
- 作者：Aless ; ro Beghi ; Marco Liberati ; Sergio Mezzalira ; Stivi Peron
- 关键词：Automotive ; Mechanical systems ; Grey-box models ; Identification ; Neural networks
- 刊名：Simulation Modelling Practice & Theory
- 出版年：2007
- 期刊代码：80_1569190x
- 类别：mt
- 出版时间：September 2007
- 卷：15
- 期：8
- 页码：894-907
- 文件大小：446 K
摘要
There is an increasing use of virtual prototyping tools in the motorcycle industry, aimed at reducing the development time of new models and speeding up performance optimization, by providing the designer with an in-laboratory virtual test track. Virtual prototyping software are multibody simulation software, which require the availability of models of all the vehicle components. The choice of the model is then of paramount importance, since it heavily affects the accuracy and reliability of the simulation results. Conventional models (like linear models) are often inadequate to describe the behavior of complex nonlinear components, so that it is necessary to appeal to different modeling approaches. This is actually the case when dealing with motorcycle suspension systems, given that their most critical part, the shock absorber, exhibits nonlinear and time-variant behavior.
In this paper, a grey-box model of a racing motorcycle mono-tube shock absorber is proposed, which consists of a nonlinear parametric model and a black-box, neural-network-based model. The absorber model has been implemented in a numerical simulation environment, and validated against experimental test data. The results of the validation show that the model is able to reproduce the real behavior of the shock absorber with an accuracy that matches or even beats that of other models previously presented in the literature. The interfacing of the proposed model to the ADAMS virtual prototyping environment is also discussed.