Title :
Quasi-steady state approximation of the dynamics of a planar motorcycle
Author :
Saccon, Alessandro ; Hauser, John
Author_Institution :
Dipartimento di Ingegneria dell´´Informazione, Padova Univ., Italy
Abstract :
Modelling the dynamics of a vehicle is the starting point for any control and optimization strategy. Generally speaking, as the complexity of a model grows, possible instability and nontrivial dynamic coupling make the exploration of vehicle trajectories a rather challenging task. The aim of this paper is to present a way to simplify a detailed model into a simpler one, the trajectories of which being close to those of the original system. For the sake of presentation, we describe a planar motorcycle model including front and rear suspensions and chain drive. The motorcycle model is composed of six rigid bodies and its equations of motion are derived using a Lagrangian approach. A suitable chain model is described. In particular, we provide a method that avoids explicit inclusion of the dynamics of the drive sprocket. This motorcycle model is then simplified allowing us to compute an estimate of the tire forces and the fast suspension dynamics. Dynamic simplification is achieved by imposing holonomic constraints at the wheels and quasi-steady state conditions on the suspensions. A simple example, a mass-wheel-suspension system, is discussed, comparing the dynamic simplification to that obtained using singular perturbation theory. A comparison between the complete dynamics and the simplified quasi-steady state model is reported by means of simulation.
Keywords :
approximation theory; motorcycles; optimisation; perturbation theory; suspensions (mechanical components); vehicle dynamics; Lagrangian approach; chain drive; drive sprocket; holonomic constraints; mass-wheel-suspension system; nontrivial dynamic coupling; planar motorcycle dynamics; quasi-steady state approximation; rear suspensions; singular perturbation theory; vehicle trajectories; Equations; Geometry; Lagrangian functions; Motorcycles; Predictive models; Solid modeling; Suspensions; Tires; Vehicle dynamics; Vehicles;
Conference_Titel :
Decision and Control, 2004. CDC. 43rd IEEE Conference on
Conference_Location :
Nassau
Print_ISBN :
0-7803-8682-5
DOI :
10.1109/CDC.2004.1428751