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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]

Aiming at reducing the effect of time delay on the control performance of magnetorheological (MR) damper semi-active suspension, a control strategy with strong robustness to time delay is investigated in this study, including the force controller of MR damper, the robust controller and the predictive compensator. The force controller of MR damper is built based on the hyperbolic tangent function; the robust controller is built based on the simplified model of car body lateral vibration and is designed by μ-synthesis method considering the effect of time delay; then the Smith predictive model and the lateral velocity predictor are designed, which form the predictive compensator of semi-active controller to reduce the effect of time delay. To validate the effectiveness of the proposed control strategy, several conventional semi-active controllers are designed as comparative objects. The simulation results show that the proposed semi-active control strategy can maintain good performance when time delay is in the range of 0–100 ms and has better robustness to time delay compared with the conventional 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]

Traction motor's rolling element bearings are one of the most critical components for the structural health monitoring of high-speed train vehicles. Most structural health monitoring techniques for railway rolling element bearings are using vibration signal. However, the vibration characteristic of cage defect is difficult to be transmitted to external monitoring point owing to the location of cage in bearing. Hence, the cage defect of Railway Traction Motor Bearing (RTMB) is usually difficult to be recognized with motor housing vibration acceleration signal. Considering Induction Motor (IM) itself a sensor, the mechanical imbalance of bearing cage defect can reflect in stator current through the motor gap magnetic field rather than a solid transmission path. A novel strategy with stator current for monitoring the traction motor bearing cage health status in High-Speed Train (HST) is proposed in this paper. This method requires no additional sensor in the practical application. To prove the strategy is feasible and more effective than vibration-based method for the cage fault diagnosis of RTMB, a comprehensive experiment investigation with a real railway traction motor of a HST is completed. Artificial cage defects are processed on bearings at both ends of the induction motor, respectively. Three high-speed (≥250 km/h) conditions are observed. The data analysis results show that vibration-based method is almost invalid at high-speed condition and the proposed current-based method is feasible and effective for the fault diagnosis of high-speed railway traction motor bearing cage. [ABSTRACT FROM AUTHOR]

Because of the complexity of high-speed train operation, the measured wall pressure of high-speed train will be affected by many factors, such as train vibration and environmental changes, which make the test signal inaccurate. The main interferences are the electromagnetic interference caused by the complicated electromagnetic environment and the sensor output interference caused by the train body vibration. In this paper, ensemble empirical mode decomposition (EEMD) combined with singular value decomposition (SVD) and the local projection de-noise algorithm with better effect on non-linear time series noise reduction are used to eliminate electromagnetic interference in test signal. Because of the frequency band aliasing of test signal and interference cause by vibration, it is difficult to eliminate vibration interference by the signal processing method. In this paper, a vibration interference model is established by model-train experiment and computational fluid dynamics (CFD) software to eliminate the vibration interference in the test signal. Moreover, the theoretical guidance for accurately extracting the wall pressure of high-speed train has been put forward. [ABSTRACT FROM AUTHOR]

Hunting monitoring is very important for high-speed trains to achieve safe operation. But all the monitoring systems are designed to detect hunting only after hunting has developed sufficiently. Under these circumstances, some damage may be caused to the railway track and train wheels. The work reported in this paper aims to solve the detection problem of small amplitude hunting before the lateral instability of high-speed trains occurs. But the information from a single sensor can only reflect the local operation state of a train. So, to improve the accuracy and robustness of the monitoring system, a multi-sensor fusion framework for detecting small amplitude hunting of high-speed trains based on an improved Dempster–Shafer (DS) theory is proposed. The framework consists of a series of steps. Firstly, the method of combining empirical mode decomposition and sample entropy is used to extract features of each operation condition. Secondly, the posterior probability support vector machine is used to get the basic probability assignment. Finally, the DS theory improved by the authors is proposed to get a more accurate detection result. This framework developed by the authors is used on high-speed trains with success and experimental findings are provided. This multi-sensor fusion framework can also be used in other condition monitoring systems on high-speed trains, such as the gearbox monitoring system, from which nonstationary signals are acquired too. [ABSTRACT FROM AUTHOR]

Detached Eddy Simulation (DES) has been used to investigate the effect of the Reynolds number on the wake of a high-speed train in the range from 5.2 ​× ​105 to 2.2 ​× ​107. Then, the characteristics of vortex structure, streamlines distribution, velocity characteristics, and pressure characteristics in the wake region of the high-speed train at five Reynolds numbers are studied. The results show that with the increase of the Reynolds number, some small-scale vortices emerge in the wake region of the high-speed train, which increases the complexity of the wake vortex structure, but the large-scale vortex structure has not changed significantly. The separation lines and vortices distributed on the train surface, and the characteristics of the pressure distribution in the wake region do not change considerably at different Reynolds numbers. The frequency of the vortex shedding from the train based on Strouhal number is approximately a constant at five Reynolds numbers, and the phenomenon and mechanism of the flow in the wake region are almost the same within the range of Reynolds number selected in this study. With the increase of the Reynolds number, the fluctuation degree of the velocity and pressure, and the vorticity in the wake region increase substantially. • DES has been used to investigate the wake characteristics of a high-speed train at five Reynolds numbers. • With the increase of Re , small-scale vortices emerge, but the large-scale vortex structure has not changed significantly. • The separation lines and vortices distributed on the train surface do not change considerably at different Re. • The phenomenon and mechanism of the flow in wake region is almost same within the range of Re from 5.2 × 105 to 2.2 × 107. • With the increase of Re , the fluctuation degree of velocity and pressure, and the vorticity in the wake region increase. [ABSTRACT FROM AUTHOR]