| The use of tilting train is an efficient way to raise train speed in existing railway lines, especially in the lines with many sharp curves. The tilting train can also be applied to further increase train speed in high speed lines. Tilting trains have successfully entered into commercial use in many countries. Even though a lot of researches have been conducted in China since 1990's, we still haven't fully mastered some core technologies of tilting trains. In this thesis, the dynamic problems of the tilting train electrical-mechanical coupled system are studied thoroughly. The work conducted can provide the theoretical basis for the future development of tilting trains in China. The main research work of the thesis are as below:(1) The nonlinear mathematical model of tilting train electrical-mechanical coupled system, which consists of several motor cars and trailer cars, is established. The model, that can simulate the actual running behaviour of tilting trains, includes the subsystems of vehicle, car end interface, pantograph-catenary, tilting control and mechtronic actuator, and brake anti-sliding control.(2) The curve detecting method, tilting control signal generating method and tilting control strategy are studied. The compensation methods of control signal delay of the first car such as the linear forecast and neural network forecast are disscussed. The P controller and H_∞robust controller of the tilting system are studied. It can be known from the simulation that the curve entry and exit of the tilting train can be better diagnosed by the use of track cant change rate. The use of signal forecast can efficiently compensate the tilting delay of the first car caused by signal filtering. The linear forecast is effictive when the time delay is short, while the neural network method can get better results when the time delay is long. The P control and H_∞robust control methods can accurately trace the tilting control signals, but the H_∞controller is more robust and possesses better control effect than the P controller. Then the curving detecting data obtained from the field test for a train are processed by using the curving detecting method and tilting signal generating method suggested in the thesis, and the test track curve condition is simulated by the tilting train model. Through the comparison between the numerical results and test results, the curve detecting method is validated. (3) The curving dynamics of the tilting train is carefully investigated. The curving behaviour of the steering bogies, the effect of carbody torsion on tilting behaviour and the performance of turnout negotiation are analysed.(4) The ride quality and hunting stability of tilting train are studied. The influence of the train consist, car end interface stiffness and damping on the vehicle ride quality and hunting speed is analysed. It can be known from the numerical results that the lateral ride quality of a single car model is worse than the results of train model, while the lateral ride quality of the front and rear cars are worse than the middle cars. The use of proper lateral damping between cars can improve the lateral ride performance. Because there is not much difference for the hunting critical speed between the single car model and trainset model, the single car model can be utilized for train stability study.(5) The pantograph-catenary coupled dynamics of the tilting train is studied by considering the FEM catenary model and nonlinear pantograph model. The passive and active controls for the pantograph lateral motions are analysed. The pantograph guideway on top of the carbody is designed, and control signal and control law are investigarted..(6) The braking anti-slide control model is set up and the tilting train braking dynamic problems are researched. The wheelset seized process, anti-slide control and stick-slip chatter problem during braking are thoroughly studied. The influence of chatter vibration on the braking anti-slide control is investigated.
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