Identification of Tire Transient Parameters from Vehicle Onboard Sensors Data

Abstract

Measuring and modeling vehicle response delays is a fundamental prerequisite for dynamic simulations, both in real-time driving platforms and in offline systems. With a human driver the delays have a heavy influence on the driving feeling and for the achievement of the optimal lap times. If artificial intelligence is driving, lap times can be improved by using algorithms able to calculate vehicle states, whose reliable reproduction is deeply linked to the delay’s evaluation. In this paper, a methodology to estimate pneumatic relaxation lengths and the parameters that determine them is proposed. To do this, a double track model is used, in which the unknown parameters are varied until the congruence between the model output and the experimental data is reached.