Lateral tracking control of all-wheel steering vehicles with intelligent tires

TL;DR

This paper introduces a novel model-based lateral control method for all-wheel steering vehicles that integrates smart tire data and distributed tire dynamics to improve handling, especially at low speeds.

Contribution

It presents the first control strategy combining distributed tire models with smart tire technology for enhanced vehicle lateral tracking.

Findings

Suppression of micro-shimmy phenomena at low speeds.

Effective path-following via force control using tire slip estimation.

Robust control leveraging PDE-based tire dynamics.

Abstract

The accurate characterization of tire dynamics is critical for advancing control strategies in autonomous road vehicles, as tire behavior significantly influences handling and stability through the generation of forces and moments at the tire-road interface. Smart tire technologies have emerged as a promising tool for sensing key variables such as road friction, tire pressure, and wear states, and for estimating kinematic and dynamic states like vehicle speed and tire forces. However, most existing estimation and control algorithms rely on empirical correlations or machine learning approaches, which require extensive calibration and can be sensitive to variations in operating conditions. In contrast, model-based techniques, which leverage infinite-dimensional representations of tire dynamics using partial differential equations (PDEs), offer a more robust approach. This paper proposes a novel model-based, output-feedback lateral tracking control strategy for all-wheel steering vehicles that integrates distributed tire dynamics with smart tire technologies. The primary contributions include the suppression of micro-shimmy phenomena at low speeds and path-following via force control, achieved through the estimation of tire slip angles, vehicle kinematics, and lateral tire forces. The proposed controller and observer are based on formulations using ODE-PDE systems, representing rigid body dynamics and distributed tire behavior. This work marks the first rigorous control strategy for vehicular systems equipped with distributed tire representations in conjunction with smart tire technologies.