Hierarchical Vehicle Stability Control Strategy Based on Unscented Kalman Filter Estimation 2022-01-0294

High-speed vehicle is prone to instability under bad road conditions, causing many safety accidents such as tail-flicking and overturning. Stability control could assist vehicle to drive safely and stably by adjusting the additional yaw moment. However, most of the existing stability control strategies directly invoke the information of the sideslip angle of the centroid that is difficult to obtain on the vehicle, and carry out complex controller design, which deviates from the actual application.

In order to achieve a complete set of stability control architecture oriented to practical applications, this paper designs a hierarchical vehicle stability control strategy based on differential braking and state estimation technology. Firstly, two different model oriented to state estimation and controller design are built according to the vehicle dynamics; Secondly, the sideslip angle of the centroid is accurately estimated through the unscented Kalman filter algorithm; Subsequently, the sliding mode controller solves the appropriate additional yaw moment for vehicle stability control according to the desired vehicle motion control state and the estimated sideslip angle; Finally, a rule-based differential braking yaw moment distribution strategy is formulated according to the steering wheel angle, steering wheel speed, and additional yaw moment. Based on MATLAB/Simulink and vehicle dynamics simulation software CarSim, a joint simulation platform is built to test and verify the algorithm. The simulation results show that the designed controller has a high estimation accuracy for the sideslip angle, and reliably ensures the steering stability of the vehicle under a variety of extreme conditions.