Automobile Active Anti-Roll Bar Control Based On Kalman Filter State Estimation

The traditional passive stabilizer bar can produce anti-rolling moment with its own torsional deformation to reduce the roll of the body,but its impact on the roll stiffness of the suspension is fixed and cannot meet the requirements of different driving conditions.The active lateral stabilizer can output real-time adjustable anti-rolling moment,which makes up for the shortcomings of passive stabilizer.However,when controlling the active stabilizer bar,it is necessary to obtain real-time data including the roll angle of the body as the input of the controller.Accurate measurement of the body roll state parameters is not easy to achieve.The paper adopts Kalman filtering method to estimate the body roll state parameters,and uses fuzzy PID control principle to design the active stabilizer bar controller,and realizes the combined control mode of roll angle state estimation and roll state control.The tire cornering characteristics were piecewise linearized,and the threedegree-of-freedom vehicle lateral dynamics model was used as the Kalman filter state prediction model.The lateral acceleration and yaw rate were used as the measured values to establish the linear Kalman filter state.Estimating the model to estimate the state of the body roll state parameters such as the body roll angle,roll angular velocity,center of mass roll angle,etc.In order to improve the anti-disturbance ability of the state estimation model to the measurement noise changes,a new adaptive method is introduced to adjust the theoretical measurement noise and process noise covariance of the Kalman filter model in real time.Comparing the state estimation results under the "Double lane-change " and "Steering wheel angle step" simulations with the simulation output values of the multibody dynamics model,it is verified that the Kalman filter model can accurately estimate the body roll state.It provides a solution to the problem that the existing on-board sensors of the target vehicle are not easy to accurately measure the body roll angle.Taking the estimated value of the body roll angle and the measured value of the body lateral acceleration as the control input,and the driving torque output by the active stabilizer bar actuator as the control object,the fuzzy PID controller is designed to achieve the ideal body roll angle and ensure the vehicle Roll stability and ride comfort,and use the speed and wheel angle signals to judge the opening and closing of the fuzzy PID controller.In the Adams/Car and MATLAB/Simulink co-simulation environment,three high-speed steering comparison simulations of " Double lane-change ","Steering wheel angle step",and " Single lane-change " are carried out.Compared with the control effect of passive stabilizer,the active anti-roll bar can reduce the peak value of the body roll angle by more than 40%,and can reduce the peak value of the left and right wheel load transfer rate by about 10%,which plays a good role in roll control.In the comparison simulation of "Single wheel over speed bump",the control strategy closed the active stabilizer bar,thus reducing the acceleration response value of the seat measurement point and avoiding the influence of the lateral stabilizer bar on the ride comfort to some extent.