AFS Control Based on Estimation of Vehicle State and Road Coefficient Using UKF Method
This paper mainly focuses on the application and feasibility of the Active Front Steering （AFS） control system. Considering that tire behaves nonlinearly during emergency steering and that the vehicle states involved in the AFS control system and the road adhesion coefficient having important effect on the stability are difficult to measure, a controller using nonlinear sliding mode algorithm was designed to synthetically take into account the influence of load transfer, tire nonlinearity, and road on the vehicle stability. Meanwhile, with the use of signals measured from the existing Inertial Measurement Unit (IMU) sensor of ESP system and the application of Unscented Kalman Filter （UKF） algorithm, a state estimator was established to dynamically estimate the vehicle state information and road adhesion coefficient for sliding mode controller. On the above basis, the desired superposition angle is precisely reversely calculated by the nonlinear tire model after the desired tire force is obtained, which verifies the effectiveness of the control system over the "tire-road" attachment capability range. Finally, simulations of fishhook test with high road adhesion and step input with low road adhesion indicate that the state estimation combined with IMU and UKF ensures the feasibility of AFS control system and effectively improves the vehicle stability.
Keywords: Active Front Steering（AFS), Unscented Kalman Filter（UFK), state estimation road adhesion coefficient, Inertial Measurement Unit（IMU）
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