Study Of The Researching On Simulation Modeling And Control Of Electrostatic Active Suspension

With the development of the automotive industry,people have put forward higher requirements for the performance of automobiles.Therefore,improving the safety,smoothness and handling stability of automobiles has always been the concern of the technology workers in the industry.Compared with passive suspension,active suspension can adapt to the undulating road surface by outputting main power and bring good riding experience to the occupants,which makes the research of active suspension a hot topic at home and abroad.This paper combines the relevant research results of scholars at home and abroad,and further researches on the control strategy of electro-hydraulic and hydrostatic active suspension system as follows:(1)Considering the actual vehicle driving road conditions,random road surface,sinusoidal road surface and impact road surface input models are established respectively.By analyzing the structure and working principle of electro-hydraulic and hydrostatic active suspension,the electro-hydraulic and hydrostatic active suspension system model is established,and the passive suspension simulation model is built and simulated in Matlab/Simulink.(2)Three control strategies,fuzzy PID,GA-LQG control and Fuzzy-SMC control,are selected as the control strategies of electro-hydraulic and hydrostatic active suspension.Since the PID controller parameters are fixed values,the control effect becomes weaker when the system is disturbed.To solve this problem,this paper uses fuzzy control to adjust the parameters of the PID controller in real time and designs a fuzzy PID controller based on this;optimal control can optimize multiple control objectives simultaneously,but it is inefficient to determine the optimal control weighting coefficients through a patchwork approach and the optimal results cannot be obtained.In order to solve this problem,this paper determines the weighting coefficients required for optimal control with the help of genetic algorithm(GA),and designs the GA-LQG controller based on it;the sliding mode control has good robustness and strong anti-interference ability,but jitter occurs when the controlled system switches the system structure at high frequency,which will affect the accuracy of the control algorithm and the stability of the system.In order to solve this problem,this paper suppresses the jitter by formulating fuzzy rules to ensure the accuracy of the algorithm and the stability of the system,and designs the Fuzzy-SMC controller based on this.The simulation model of electro-hydraulic and hydrostatic active suspension under the above three control strategies is built and simulated in Matlab/Simulik.The control effect of several control algorithms is compared,and the best control effect is achieved when Fuzzy-SMC control is selected for electro-hydrostatic-hydraulic active suspension,taking into account the body acceleration,suspension dynamic travel and tire dynamic load.(3)In order to make the electro-hydraulic and hydrostatic active suspension simulation closer to the actual situation,the control of the actuator(actuator)part is increased,and the cascade control is selected as the control strategy of the active suspension,and the cascade control is divided into the control outer loop and the control inner loop.In this paper,FuzzySMC control strategy is selected as the cascade control outer loop control strategy to calculate the ideal main power;the control of the inner loop brushless DC motor adopts double closedloop control,in which the motor drives the hydraulic motor and the hydraulic motor drives the hydraulic cylinder to output the actual main power in the simulation.The cascade control model is established and simulated in Matlab/simulink by combining the outer loop for calculating the ideal main power and the inner loop for outputting the actual main power.The simulation curves of the active suspension performance indexes and the simulation curves of the main motive force under the two control strategies are compared,and the overlap between them is very high,which indicates that the actual main motive force output from the inner loop of the cascade control well tracks the ideal main motive force calculated by the Fuzzy-SMC control and accomplishes the design goal.