Intelligent Vehicle Sideslip Angle Observation Strategy Based on Steady‐State Model and SCKF With Nonlinear Compensation

Vehicle sideslip angle is one of the irreplaceable variable indicators for evaluating vehicle stability. However, it is difficult to directly measure vehicle sideslip angle with onboard sensors. In order to obtain precise vehicle sideslip angle using onboard sensors, a novel observation strategy based on fusion of steady‐state model method and square‐root cuvature Kalman filter (SCKF) with nonlinear compensation is proposed. To predict the vehicle dynamics states, a four‐wheel vehicle dynamics model is established, and a tires force estimator is designed based on Magic tire formula considering tire vertical load transfer caused by dynamics coupling characteristics. Firstly, an improved SCKF observation strategy is investigated and the nonlinear compensation strategy using exponential function is proposed to compensate vehicle dynamics system modeling error. Then, an observer based on steady‐state model method is designed and tire cornering–stiffness identification strategy is used to adaptively update observer parameters. Finally, a fusion strategy using exponential function is proposed to calculate sideslip angle from steady‐state model observer and SCKF observer. The large curvature steering and lane change maneuver results show that the proposed fusion observer performs well under different driving conditions.