Abstract:
Tyre modelling has been a focal point of vehicle dynamics modelling since the beginning of vehicle dynamics research. Many tyre models are based on single point contact models which utilize some form of the Pacejka Magic Formula curve fit. The Pacejka Magic Formula approach was formulated in the 1980s and has certain advantages such as high computational efficiency and easily obtainable parameterization data. However, the Pacejka Magic Formula is limited to function on smooth roads and a finite number of well defined, long wavelength discrete obstacles.
A high fidelity approach in the form of Cosin s FTire tyre model was developed, in which the tyre is modelled as a three dimensional object populated with bending, tangential, lateral and radial stiffnesses as well as damping. The tyre is numerically approximated with a predetermined number of elements. The disadvantages of using FTire include its low computational efficiency and the large number of parameters prescribed to parameterize the tyre model. However, FTire is claimed to be capable of accurately predicting the forces and moments generated by the tyre on smooth as well as uneven road surfaces for on-road tyres.
The focus of this study lies on parameterizing and validating an FTire model of an all-terrain SUV tyre. The aim is to verify whether a parameterized FTire model is able to predict the tyre behaviour of an all-terrain SUV tyre for lateral and longitudinal forces on smooth road surfaces and vertical forces on uneven but hard terrain.
Static laboratory and dynamic field tests are conducted to acquire parameterization and validation test data to parameterize the FTire model. An Adams model of the tyre testing equipment is implemented to simulate the FTire model and validate it against dynamic validation test results.
It is found that the FTire model is able to predict the lateral tyre behaviour well on a smooth road surface. The longitudinal tyre behaviour on a smooth road surface and vertical tyre behaviour on an uneven road surface are predicted very well by the parameterized FTire model.
