State and Parameter Estimation in a Semitrailer for Different Loading Conditions Only Based on Trailer Signals

For further development of assistance systems and autonomous systems for tractor-semitrailers, knowledge of relevant trailer states and parameters is necessary. However, the trailer is sparsely equipped with sensors and the standardized communication between truck and trailer is reduced to braking signals. This paper presents an approach for estimating the lateral and vertical tire forces, roll behavior and articulation angle of the trailer for different loading conditions solely based on trailer signals using an Unscented Kalman Filter (UKF). Due to missing information from the truck, the varying mass and center of gravity (COG) based on different loading conditions must be estimated only on trailer signals. The investigation on structural observability shows that an estimation of all unknown parameters with the UKF is not possible. Thus, the usage of a substitute mass and COG is necessary and calculated based on the trailer's axle load and domain knowledge of the usual practical loading distribution. The method is validated for different substitute masses and COGs with experimental data from a fully and partially loaded trailer.