Research On Control Strategy Of Railway Vehicle Lateral Suspensions

As the train is running at high speed, the body of train has lateral.rolling and yawing vibration due to track irregularity input.And three kinds of vibration constitudes train lateral synthetic acceleration,the lateral stability of train is affected. So,the suspension system is used to reduce the lateral vibration and improve the vehicle running stability and comfort. Semi-active suspension not only is better than passive suspension in the damping effect but also achieves more energy conservation than active suspension, which can become the focus and difficulty in the futural research. Because the train lateral motion system is a dynamic one with complex, nonlinear, time-varying and multi-variable characters, many control algorithms of semi-active suspension have their limitations. Fuzzy control does not depend on the accurate mathematical model among those control algorithms, and has also characteristics of artificial intelligence, thus shows strong superiority in the semi-active suspension system. After train lateral system model with 17 degrees of freedom is built by Simulink software, the general,variable universe,optimized by evolutionary algorithm and hybrid fuzzy control are respectively designed, and then the validity of the algorithm is proved through simulation. The main work is as follows:(1) Vibration structure of train semi-active suspension is analyzed. In three kinds of vibration, lateral and yawing vibration is important factor of affecting the lateral synthetic acceleration of train. The cross correlation function and wavelet transform analysis show that the main frequency of lateral vibration mainly is concentrated in the low frequency band below 1Hz, horizontal irregularity is an important eause of train lateral and yawing vibration, and alignment irregularity is an important factor of train rolling vibration, horizontal irregularity is an important factor for the train lateral synthetic acceleration at the same time.(2) Fuzzy controller is designed for semi-active suspension of train. To improve the ride quality and reduce lateral vibration, the fuzzy controller is designed to adjust damping parameter by taking the the body’s acceleration and velocity as the controller’s input variables and the dampmer’s current as the controller’s output variables. Simulation result by the means of root mean square shows that lateral acceleration of the body significantly decreases by the ordinary fuzzy control, and it is proved that semi-active suspension is better than passive suspension at the same time.(3) The variable universe fuzzy control strategy is completed. The more widely convergence conditions of variable universe fuzzy control is given, and it is suitable for semi-active suspension system. After lateral motion model of 17 degree-of-freedom train is established, the variable universe fuzzy controller is designed. The simulation results show that the variable universe fuzzy control is better than the ordinary fuzzy control in the maximum amplitude, mean square root and power spectral density maximum value of the lateral, rolling and yawing, front, middle and rear acceleration.(4) Satisfactory optimization mothed is used to optimize the fuzzy controller by an improved biogeography-based optimization algorithm. To improve satisfactory optimization effect, the semi-active suspension fuzzy controller is optimized by the improved biogeography-based optimization algorithm based on complex method. The simulation results show that fuzzy control optimized by this method can effectively reduce the maximum amplitude, mean square root and power spectral density maximum value of lateral vibration.(5) A hybrid fuzzy controller is designed. The variable universe fuzzy controller and the fuzzy cotroller optimized by evolutionary algorithm is organically combined, and the hybrid fuzzy controller is designed. Research results show that control effect is the best while control factor is 0.5. So, modified biogeography-based optimization algorithm is also used to optimize the hybrid control when control factor is 0.5.Simulation results show that the control effect of hybrid fuzzy controller is better than that of the variable universe fuzzy controllor.