Research On Road Adaptive Control Of Solenoid Valve Semi-Active Suspension For UTV

UTV have excellent maneuverability and can walk freely on roads that are difficult for ordinary vehicles to drive.The complex and changeable road environment makes the traditional passive suspension unable to meet the dynamic performance of the vehicle.The actuator is a solenoid valve type shock absorber with adjustable damping.It is a semi-active suspension system with excellent damping performance.In its control research,most of the system control parameters are designed on a single road surface.The suspension control parameters on a mixed road surface cannot be adaptively adjusted according to the road surface,and the improvement of driving dynamics performance is limited.In view of the above problems,this paper takes the solenoid valve type semi-active suspension of UTV vehicle as the research object,and conducts a comprehensive research on the actuator,input,state and output of the system,and designs a road adaptive control system for the semi-active suspension of UTV vehicle.In order to improve the dynamic performance of the vehicle on mixed roads.The main research contents of this paper are as follows:Firstly,the structure and working principle of the CDC(Continuous Damping Control)shock absorber were analyzed,the shock absorber test plan was designed,and the test bench was built to test the external characteristics of the shock absorber.The working mechanism of the shock absorber in the semi-active suspension control system is clarified,and the BP neural network inverse model of the CDC shock absorber is established by using the test data,which provides the basis for the control research of the solenoid valve type semi-active suspension system.Secondly,the corresponding relationship between the road surface of the UTV vehicle and the random road surface is analyzed,and the random road input model is established based on the filtered white noise method.At the same time,a four-degreeof-freedom 1/2 vehicle solenoid valve type semi-active suspension system dynamics and state space model are established,and the vibration response amplitude-frequency characteristics of the vehicle under the change of damping coefficient are studied,which provides a model basis and basis for subsequent research.Theory reference.Subsequently,the realization method of road recognition is analyzed,the transfer function method and NARX neural network method of road time domain estimation are designed,and the shortcomings in the practical application of the transfer function estimation method are explored.The AR model is used to estimate the road power spectrum,and the trapezoid method is used to calculate the root-mean-square value of the spectral density,which realizes the estimation and recognition of the road level.At the same time,a Kalman observer is constructed based on the system’s measurable state variables.The road surface estimator and Kalman observer provide the basis of system input and system state for the research of semi-active suspension system control strategy.Finally,combining the shock absorber inverse model,the road input model,the road estimator and the Kalman observer,the semi-active suspension system adaptive optimal controller is designed,and the dynamic performance demand mapping relationship under different grades of roads is analyzed.The EGA(Elite Genetic Algorithm)algorithm determines the control parameters under various dynamic performance requirements,and simulates and verifies the control effect of the adaptive optimal controller under mixed roads.The simulation results show that the designed control system can realize the adaptive switching of different levels of road control parameters,and effectively meet the dynamic performance requirements of vehicles on different roads.