Research On Body Attitude Optimal Control Of Intelligent Vehicle Based On Magnetorheological Suspension

Under the trend of the development of automobiles in the direction of full intelligence,it is essential for intelligent vehicle to ensure the stability of the body attitude while driving and thus provide good ride comfort for passengers in the car.Therefore,in this thesis,the intelligent suspension is applied to the attitude control in the path tracking process of the intelligent vehicle in combination with the magnetorheological intelligent suspension and the intelligent vehicle.According to the different driving conditions of the intelligent vehicle,a sub-mode optimal attitude control method is proposed to optimize the attitude change of the intelligent vehicle during the path tracking process.The specific research contents are as follows:Firstly,the magnetorheological damper model was established.The basic theories of magnetorheological fluid were analyzed,including its composition,magnetorheological effect,rheological mechanism and mechanical property.Based on this,the working mode of magnetorheological damper was analyzed in detail,and the dynamic models of magnetorheological damper were summarized.Based on the modified Bouc-Wen model,the magnetorheological damper simulation model was established in Simulink,and the simulation results showed that the model can describe the nonlinear hysteresis characteristics of the magnetorheological damper more accurately.Secondly,the magnetorheological suspension system and its control strategy were studied.The quarter vehicle simulation models of passive suspension and magnetorheological suspension were established in Simulink.A single wheel random road model was established using the filtered white noise production method.A variety of control strategies including on-off skyhook damping control,LQR optimal control and fuzzy control were applied to control the magnetorheological suspension,and a control simulation platform for the 1/4 magnetorheological suspension system was established.The simulation results showed that LQR optimal control and fuzzy control had better control effects.Finally,according to the difference of driving conditions in the path tracking process of intelligent vehicle,a sub-mode optimal attitude control method was proposed,and a co-simulation platform was established to verify the method.The optimal attitude control was divided into a stable-attitude optimal control mode under a uniform straight-line driving state and a mutated-attitude optimal control mode under an acceleration/deceleration or steering driving state.Combined the preview follower theory with the improved pure-pursuit control strategy,a reliable path tracking controller of the intelligent vehicle was designed.For the stable-attitude optimal control mode,a specific effective control strategy was designed based on the LQR optimal control and the improved IAHP method.For the mutated-attitude optimal control mode,based on the status information of the intelligent vehicle and the steering information provided by the path tracking controller,the fuzzy control strategies of pitch and roll attitude optimization were respectively designed.A co-simulation platform was established based on CarSim/Simulink,and the co-simulation simulation experiments showed that under different operating conditions,the sub-mode optimal attitude control method had certain optimization effects on the body attitude of intelligent vehicle during the path tracking process,and it provided a certain reference for the body attitude optimization control of intelligent vehicle based on semi-active suspension.