Research On Control Of Engine Magneto-rheological Mount System

With the rapid development of the national economy,people's quality of life has been greatly improved,and have higher and higher requirements for the performance of cars,from the durability of the beginning to the current comfort;Excellent NVH performance will give passengers a good ride comfort,and engine vibration is an important factor affecting NVH performance.Compared with passive mount,magneto-rheological mount has the advantages of continuous adjustable characteristics,which can improve the quality of NVH,and better control strategy can greatly improve the vibration isolation performance of magnetorheological mount system.At present,most of the control strategies designed for magnetorheological mount systems use a single control strategy,and the control effect is not good.For this reason,the neural network and fuzzy control are combined to design the neural fuzzy controller,and then the simulated annealing particles are used.The group algorithm(SAPSO)optimization algorithm optimizes the controller parameters and compares the simulation data.The main research work of the thesis is as follows.The main research work of the thesis is as follows:Introduced the rheological properties and working modes of magnetorheological fluids,and design a magnetorheological suspension on the existing hydraulic suspension structure using flow mode.Analyzed the damping force of the designed damping channel.At the same time,the finite element method is used to analyze the magnetic field of the damping channel corresponding to the effective magnetic pole to verify whether the magnetic field strength of the designed magnetic circuit meets the requirements.It is difficult to use the mathematical model to express the characteristics of magnetorheological mount,and the damping model is used to simulate its characteristics.Fabricated and processed the sample of magnetorheological mount,and tested the static and dynamic characteristics of the sample.Based on the different currents and damping results obtained at different frequencies,established the forward and inverse models of magnetorheological mount damping,This is to prepare for the design of the semi-active controller.In order to more comprehensively analyze the vibration isolation performance of the magnetorheological suspension system,constructed six-degree six-degree-of-freedom dynamic model considering road excitation,including the vertical and vertical pitch of the engine,the vertical and vertical pitch of the vehicle body,and the two wheels.There are a total of six degrees of freedom in the vertical direction.The main excitation of the four-cylinder engine is analyzed,and the engine excitation input model of the mount system and the random white noise model of the filtered white noise are established.Then,established the six-degree-of-freedom dynamic model is in the Simulink.Aiming at the problem that the control effect of magnetorheological suspension is not good,the magneto-rheological suspension is used as the control object,designed the fuzzy controller and the neuro-fuzzy controller,and the simulated annealing particle swarm optimization algorithm based on time-varying weight is applied to optimize the parameters of the neuro-fuzzy controller.It can be obtained by three kinds of controller simulation analysis.The neural network fuzzy device has better improvement effect on the vibration isolation performance of the engine suspension system than the fuzzy controller.The optimized neural fuzzy controller has better control effect than the neural fuzzy control.