Sideslip estimation for articulated heavy vehicles in low friction conditions

Active safety systems for Heavy Goods Vehicles (HGVs), like passenger cars, often require an accurate estimate of sideslip angle. However, very little research has been published on HGV sideslip estimation in low friction conditions. This paper proposes three nonlinear Kalman Filters to estimate the tractor sideslip angle of a tractor-semitrailer combination. Performance is compared in simulation to a linear Kalman Filter in both high and low friction conditions. An Unscented Kalman Filter using a yaw-roll vehicle model and nonlinear tire model is found to accurately estimate sideslip in all maneuvers simulated, significantly outperforming the linear Kalman Filter.