Online and Offline Identification of Tyre Model Parameters
Doctoral thesis, 2018
The accelerating development of active safety system and autonomous vehicles put higher requirements on both environmental sensing and vehicle state estimation as well as virtual verification of these systems. The tyres are relevant in this context due to the considerable influence of the tyres on the vehicle motion and the performance boundaries set by the tyres. All forces that the driver use to control the vehicle are generated in the contact patch between the tyre and the road on a normal passenger car. Hence, the performance limits imposed by the tyres should ideally be considered in the active safety systems and in self-driving vehicles. Due to tyres influence on the vehicle motions, they are some of the key components that must be accurately modelled to correlate complete vehicle simulations models with physical testing.
This thesis investigates the possibility to estimate the tyre-road friction coefficient during normal driving using active tyre force excitation, i.e. online identification of tyre model parameters. The thesis also investigates the possibility to scale tyre Force and Moment (F&M) models for complete vehicle simulations from indoor tests to real road surfaces using vehicle-based tyre testing, i.e. offline identification of tyre model parameters.
For online identification of tyre model parameters, the focus has been on how to perform tyre force excitation to maximize the information about the tyre-road friction coefficient. Furthermore, the required excitation level, as a ratio of the maximum tyre-road friction coefficient, for different road surfaces and tyre models have been evaluated for a larger number of passenger car tyres. The thesis shows the feasibility and benefits of using active tyre force excitations and illustrates its benefits when estimating the tyre-road friction coefficient by identifying nonlinear tyre model parameters. The method shows promising results by offering tyre-road friction estimates when demanded by the driver or an on-board system. This system can also be combined with other tyre-road friction estimates to offer a continuous tyre-road friction estimate, e.g. through car-to-car communication.
For offline identification of tyre model parameters, the focus was put on rescaling tyre models from indoor testing to a real-world road surface using vehicle-based tyre testing. Sensors were fitted to the vehicle to measure all inputs and outputs of the Pacejka 2002 tyre model. Furthermore, testing was performed on both different road surfaces and using different manoeuvres for tyre model identification. The effect on the complete vehicle behaviour in simulation when using tyre models based on different manoeuvres and road surfaces was investigated. The results show the importance of using a road surface and manoeuvre that are representative for the road surface and manoeuvre in which the vehicle will be evaluated. The sensitivity to different manoeuvres are mainly related to the changes in tyre properties with tyre surface temperature and the lack of temperature effects in the tyre model. The method shows promising results as an efficient way to rescale tyre models to a new road surface.
computer aided engineering
tyre-road friction estimation