| The magnetorheological semi-active suspension has the advantages of simple structure,low energy consumption and continuous and controllable damping force,which has become a research hotspot of domestic and foreign scholars.Researchers mainly design a reliable control algorithm based on the mechanical characteristics of the magnetorheological damper(MRD),so as to realize the driving comfort and operating stability of the vehicle at the same time.However,in the actual work of the system,due to the response of Mr Fluid,the calculation of the control system and the drive of MRD,there will be a time lag between the control damping force and the actual motion state of the suspension system,which will affect the control performance.Therefore,this paper takes Mr Semi-active suspension as the research object,based on the optimal control theory,and under the premise of considering the time lag.The following studies were carried out:In this paper,the working principles of magnetorheological fluid and MRD are described respectively,and the mechanical property test platform of MRD is built to conduct the performance test of MRD,and the force-displacement relationship curves and force-velocity relationship curves reflecting the performance characteristics of MRD are obtained respectively.On this basis,the parameters of the improved hyperbolic tangent model are identified by using genetic algorithm.By comparing the fit degree of the curve predicted by the model and the test curve,the results show that the identification accuracy is high.Then,the reverse dynamic model of MRD is obtained according to the improved hyperbolic tangent model identified,which can be used to design the control strategy of semi-active suspension.The three performance indexes of evaluating suspension performance are described,which are body acceleration(ride comfort),suspension dynamic travel(safety)and tire dynamic load(operating stability).The two-degree-of-freedom 1/4 vehicle suspension model and its state space equation are established.According to the actual driving conditions of vehicles,the random pavement model and the impact pavement model were established respectively and simulated respectively in Simulink environment,and their axial displacement curves were obtained.In order to solve the problem that the weighting coefficient matrix of LQR control strategy is difficult to determine in the application process,NSGA-Ⅱ algorithm which can carry out multi-objective optimization is introduced.The body acceleration and tire dynamic load are selected as the optimization objectives,and the weighting coefficient matrix is optimized under the premise that the suspension dynamic travel does not exceed the limit block.Aiming at the problem of time delay in response of semi-active suspension system,based on NSGA(Ⅱ)-LQR control strategy,the first order Taylor series expansion method was introduced to establish the extended state space equation,and to realize the prediction of the ideal control force at future time,and the NSGA(Ⅱ)-TLQR control strategy was proposed.Simulink simulates passive suspension,semi-active suspension under simple LQR control,semi-active suspension under NSGA(Ⅱ)-LQR control strategy,semi-active suspension under NSGA(Ⅱ)-TLQR control strategy.The simulation results show that the three control strategies have been optimized in different degrees on the basis of passive suspension.And NSGA(Ⅱ)-TLQR control strategy achieves the best control effect,followed by NSGA(Ⅱ)-LQR control strategy.A semi-active suspension test scheme is designed based on STM32.In order to solve the interference problem of sensors in the A/D adoption process,the first-order digital low-pass filtering algorithm is used to process the sampled signal,filtering the high-frequency disturbance in the signal to make the signal more stable.In order to realize the real-time controllable damping force output of MRDS,BUCK circuit is designed as the driver circuit of MRDS.In order to realize the accurate tracking of signals,PID control algorithm is introduced to realize the negative feedback modulation of BUCK circuit.The effectiveness of this strategy is verified by step signal tracking and sinusoidal half-wave signal tracking experiments.The suspension performance test platform was built and sinusoidal excitation experiment and impact load experiment were carried out respectively under no control(passive),NSGA(Ⅱ)-LQR control and NSGA(Ⅱ)-TLQR control.The results showed that the suspension system under the two control strategies achieved different degrees of optimization on the basis of passive suspension.The experimental results of NSGA(Ⅱ)-TLQR control are the best,which verifies the effectiveness of the proposed control strategy. |
