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The lateral vibration of the car body affects the lateral stability of high-speed trains (HSTs), and the aim of this study is to design a good control strategy to decrease the lateral vibration of the car body. First, the Maxwell model of the anti-yaw damper was transformed into a Voigt model by the equivalence method, and a modified 17-degree-of-freedom (DOF) lateral vibration model that includes the anti-yaw damper was established. After the design difficulty and control accuracy of the control strategy were weighed, the lateral and yaw motions of the wheelsets were regarded as disturbances, and a disturbance observer of wheelset motions was designed to simplify the 17-DOF model to a 9-DOF lateral vibration model. Second, a model predictive control (MPC) strategy for HST lateral vibration was designed, and the effects of the key parameters on the lateral vibration acceleration of the HST car body and on the iterative computation time of the MPC strategy were studied. In addition, a conditionally triggered model predictive control (CMPC) strategy was proposed. Last, the control effects of the CMPC strategy under the working conditions of speed change, turnout passage, and aerodynamic load were studied by simulation, which verified the validity of the proposed model and control strategy. [ABSTRACT FROM AUTHOR]

The setting curve and control method of internal temperature in trains are studied in this paper to achieve energy saving control for air conditioning systems. First, a model of interior temperature that considers the heat transmission from infiltration air is established according to the relationship between the equivalent leakage area for the train body and the pressure difference between the internal and external carriage. Second, the interior temperature setting curve, which changes adaptively with the ambient temperature, is established considering the energy consumption of air conditioning systems and passengers' thermal comfort. Finally, an adaptive iterative learning control (AILC) algorithm is proposed and applied to control the interior temperature according to the periodicity of train operation. In this paper, meteorological data from a typical meteorological year are used for simulation analysis. Simulation results show that the AILC algorithm can effectively track the interior temperature setting value and has a better control effect when the train runs on the same line repeatedly. Under the action of the AILC algorithm, the root-mean-square error is reduced to 0.069 °C in the third iteration. Furthermore, the energy saving for a single carriage in a single process reaches up to 1.534 kW·h, thus achieving energy saving control. [ABSTRACT FROM AUTHOR]

For the operational noise of a medium-low speed maglev train, this paper proposes a method to achieve sound source identification based on characteristic frequency extraction and coherence analysis through continuous cross wavelet transform. Field tests were conducted on a main line in China on the operational noise, vibration and traction current of linear induction motor in the medium-low speed maglev train. The proposed method was applied to the test data to analyze the operational noise properties. The characteristic frequencies were extracted from all the three test target signals for coherence analysis through continuous cross wavelet transform, which verifies the transmission characteristics of electromagnetic noise. The coherence spectrum of noise-vibration signal and current-vibration signal showed that the operational noise in the starting and braking stages mainly originates from the high-frequency vibration excited by the high-frequency harmonics in the traction current of the traction motor. [ABSTRACT FROM AUTHOR]

To explore the relationship between the dynamic model parameters of a stabilizing device coupled system and the quality status of a ballast bed, this study establishes a dynamic model of a frame-stabilizing device-rail sleeper system by combining track coupling dynamics with the operating mechanism of a stabilizing device and by using the lumped parameter method. Moreover, by combining the experimental results and nonlinear least squares identification method based on the trust-region reflective algorithm, the mapping relationship between the model parameters and the lateral resistance of the sleeper is discussed. In addition, the dynamic model is validated by numerical simulation using the fourth-order Runge-Kutta method. Results show that the model has good accuracy, and the acceleration peak error rates between the dynamic model response and the test data are all within 5 %; the lateral resistance of the sleeper is positively and negatively correlated with the transverse stiffness and transverse damping of the ballast bed in the system model, and the correlation coefficients are 0.96 and 0.89, respectively. [ABSTRACT FROM AUTHOR]