Online Tire Cornering Stiffness Estimation for Articulated Road Vehicles: Real-Time Estimation of Tire Cornering Stiffness in Articulated Vehicles using Unscented Kalman Filtering

Abstract

This thesis investigates the real-time estimation of tire cornering stiffness for articulated heavy-duty vehicles using an Unscented Kalman Filter (UKF). Utilizing a simulation-based approach via IPG TruckMaker and Simulink, the study evaluates single-track, two-track, and articulated vehicle models under varying sensor availability and lateral excitation conditions. Results indicate a single-track, axle-level representation yields robust and convergent stiffness estimates for the tractor, whereas individual tire estimation seems to suffer from severe unobservability. The estimator demonstrates robustness to velocity sensor degradation by falling back on inertial and wheel speed data. Trailer cornering stiffness estimation exhibits steady-state errors attributed to unmodeled hitch dynamics. An observability-driven update strategy utilizing the local observability Gramian successfully restricts parameter updates to periods of sufficient lateral excitation.