Various active safety systems proposed for articulated heavy goods vehicles (HGVs) require an accurate estimate of vehicle sideslip angle. However in contrast to passenger cars, there has been minimal published research on sideslip estimation for articulated HGVs. State-of-the-art observers, which rely on linear vehicle models, perform poorly when manoeuvring near the limits of tyre adhesion. This paper investigates three nonlinear Kalman filters (KFs) for estimating the tractor sideslip angle of a tractor–semitrailer. These are compared to the current state-of-the-art, through computer simulations and vehicle test data. An unscented KF using a 5 degrees-of-freedom single-track vehicle model with linear adaptive tyres is found to substantially outperform the state-of-the-art linear KF across a range of test manoeuvres on different surfaces, both at constant speed and during emergency braking. Robustness of the observer to parameter uncertainty is also demonstrated.