Characterization of handling performance through identification of vehicle/tire models from instrumented vehicle tests


CALL: 2015

DOMAIN: MS - Materials, Physics and Engineering


LAST NAME: Montrouge


INDUSTRY / PPP PARTNER: Universite de Haute-Alsace


KEYWORDS: Vehicle dynamics, Tire, Modelling, Identification, Control theory

START: 2015-10-01

END: 2019-09-30


Submitted Abstract

The tyre transmits all forces enabling the control of a motor vehicle, thereby playing a critical role in the cornering, braking and traction response of the vehicle. Tyre characteristics are strongly influenced by prevalent operating conditions and the state of the tyre itself. Factors such as tyre pressure, state of wear, external temperature, road surface texture and weather conditions produce variations of more than 50% in tyre characteristics compared to controlled conditions in laboratory tests. This creates a serious challenge, not only to tyre development activities, but also to the development of vehicle control strategies used in applications such as ABS braking, traction controllers, ESP systems, driver assistance systems and autonomous driving vehicles. Goodyear studies show that with knowledge of the actual tyre characteristics, ABS systems could reduce braking distance from 100kph on wet roads by up to 6m. This projects aim is to develop robust mathematical routines for the identification of pneumatic tyre characteristics from measurements performed on a running vehicle. In an initial phase, classical multi-body vehicle modelling and empirical tyre modelling techniques will be employed together with extensive vehicle instrumentation to identify tyre characteristics from controlled tests. These models will serve to define the sensitivity of identified characteristics to measurement and model error, as well as instrumentation and test requirements for tyre characteristic identification. There will be direct applications of this work to tyre development. A further aim of the project is to develop and evaluate functional modelling strategies capable of system identification from reduced data sets and lower levels of system excitation. Such strategies have as their ultimate goal the identification of system performance on standard vehicles on public roads. This work lays an important foundation and support to ongoing projects in the areas of Intelligent Tyre Sensors and their integration into vehicle control strategies.

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