Research On Fault Diagnosis And Compensation Method For Automotive Sensor Of Semi-active Suspension

The suspension system plays a leading role in determining the ride comfort and operation stability of the vehicle,aiming at improving the ride comfort and operation stability of the vehicle,the semi-active suspension can change the magnitude of the damping control force through the real-time data measured by the sensor The vehicle vibrates,but at the same time,it becomes particularly important to ensure the reliability of the system control effect.Based on the National Natural Science Foundation Project "Research on Adaptive Switching of Automobile Active Suspension Damping Control under Road Intelligent Sensing"(51605213),this paper studies the semi-active suspension control strategy based on adaptive gradual elimination,taking the semi-active suspension with adjustable damping as the research object On the basis of Kalman filter algorithm for vehicle vibration state estimation,fault diagnosis and compensation methods are studied for the main sensors of semi-active suspension vehicles.The details of the study are as follows:(1)The model of seven degrees of freedom semi-active suspension is established,the model of four-wheel random road input based on filtered white noise is established,and the common fault types of main sensors of semi-active suspension vehicles,including jamming,gain variation and constant deviation failure,are established The fault model to be used.(2)Based on the linear optimal control theory,the weighting coefficients of the LQG controller are obtained by using the analytic hierarchy process(AHP)and the improved AHP(IAHP)respectively,so as to complete the design of the whole controller The performance parameters of the dynamic suspension are compared with those of the passive suspension,and the simulation results are analyzed to verify the effectiveness of the above method.(3)Based on the model of semi-active suspension system,a method of vehicle vibration state estimation based on adaptive evanescent Kalman filter is presented,which is based on the information of vertical displacement and velocity,pitch angle and velocity,and roll angle and velocity The validity and applicability of the state estimator are verified by using Matlab / Simulink software.(4)Based on the residual theory,the fault object is determined by using the threshold value and the fault feature vector,and the fault compensation is realized by replacing the sensor measurement value with the estimated value of the estimator by the fault diagnosis information.The vehicle model is built by Carsim software,and the Carsim / Simulink joint simulation platform is built,based on this joint simulation platform,the correctness of the proposed fault diagnosis and compensation method for the main sensors of semi-active suspension is verified.The simulation results show that the vehicle state variables can be accurately estimated by the state estimator based on the adaptive fading Kalman filter algorithm,and the fault diagnosis and compensation of the semi-active suspension vehicle sensors can be carried out by further using the residual theory,thus ensuring the suspension.Control effect of rack system.