Vehicle dynamics Estimation and Road Security Diagnosis: Developments at the HEUDIASYC CNRS Lab

摘要

Knowledge of vehicle dynamic parameters is important for vehicle control systems that aim to enhance vehicle handling and passenger safety. Unfortunately, some fundamental parameters like tire-road forces and sideslip angle are difficult to measure in a car, for both technical and economic reasons. This problem has been considered at the HEUDIASYC Lab, were we have proposed simple and non expensive solutions to precisely estimate the forces and the side-slip angle that are necessary to precisely describe the vehicle dynamics. This estimation methodology, based on Bayesian predictor-updater estimation techniques (unscented Kalman filtering), is presented in this paper. Experimental results show the potential of the estimation method. Once the forces and side-slip angle are easily observed, in real-time during the displacement of the vehicle, using the HEUDYASIC observers, we have developed a driving behaviour diagnosis methodology that enables us to detect and evaluate a potential dangerous situation in a anticipated way. This method is based on the prediction of the lateral dynamics of the vehicle and the anticipated evaluation of the rollover and lateral skyd risk indicators. Experimental results prove the pertinence of the method.