Vehicle sideslip angle estimation with stiffness adaptation

The main task in driving safety is the understanding and prevention of risky situations. While looking closer at the accidents data analysis, it appears that vehicle loss of control represents a huge part of car accidents. Preventing such kind of accidents, using assistance systems needs several type of information on vehicle dynamic state and vehicle-road interaction phenomenon. Longitudinal velocity, acceleration, steering angle and yaw rate can be easily measured using low cost sensors that are standard equipping a large part of recent vehicles with system as A.B.S. and E.S.P. However, other parameters that have a major impact on vehicle dynamics, are more difficult to measure using vehicle industry technology sensors. A particular case of such signals is the sideslip angle. Using an appropriate vehicle model and available measurements, the vehicle state vector as well as the road/tyre interaction forces can be reconstructed by implementing an Extended Kalman Filter (EKF). Thereafter, an estimation of the sideslip angle is obtained as a component of the state vector. Once the Filter was developed, the simulation and the estimation results are then compared to real measurements collected by an equipped test vehicle on the Satory test track. Finally, as a validation step, the Filter is implemented in the test vehicle and then run in real-time.