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The yaw damper serves as a hydraulic system connecting the bogie frame with the carbody and is the most critical component to prevent unstable oscillations of high-speed vehicles. Accidently, some unexpected factors can cause the yaw damper to fail, resulting in vehicle hunting instability. In this paper, a severe bogie-hunting phenomenon was monitored during the operation of a Chinese high-speed train. Specific research on the cause and solutions was performed by experimental and numerical methods. The wheel-rail contact relationship and the dynamic performance of the yaw damper were measured and analysed to identify the primary contributor to violent bogie hunting. The results indicated that the abnormal dynamic stiffness and damping of the yaw damper caused by the compression empty stokes serve as the primary origin of this abnormal vibration. The multi-body dynamics model of the high-speed train was established by integrating the field-tested parameters. The bogie hunting phenomenon was reproduced successfully, and the influences of yaw damper parameters on bogie hunting stability were analysed to propose the optimisation scheme. Finally, two solutions were adopted to suppress the empty compression strokes of the yaw damper and verified by the roller rig test. [ABSTRACT FROM AUTHOR]

Cross-line operation that can improve the utilization of railway equipment and transportation efficiency is expected to be the development of the future, and the key to realizing this is to guarantee the dynamics performance of high-speed trains operating on different railway lines. To this end, this study focuses on determining the parameters of a suspension system for a high-speed train equipped with semi-active dampers. Multi-body dynamics method is used to establish a mathematical model of a high-speed vehicle, and a numerical integration method is applied to calculate the system response. An improved genetic algorithm adopting the dynamic Hamming distance, dynamic crossover, and mutation coefficients is integrated into the numerical simulation process to determine the parameters. Based on the numerical analysis, the optimized damping values for various hydraulic dampers in their passive modes are obtained. Finally, an experimental validation based on roller-rig and field loop-line tests is performed, and the test results verify the effectiveness of the optimized parameters. Thus, the study findings can serve as a reference to enhance the realization of cross-line operation. [ABSTRACT FROM AUTHOR]

The dynamic characteristics of the hydraulic damper are time-varying in the complex working environment. To reveal the internal influence mechanism of the boundary conditions on the dynamic performance of the hydraulic damper and take it into account in the multi-body dynamics calculation, the laboratory test of the hydraulic damper is carried out firstly, and it is confirmed that the hydraulic damper has significant frequency-dependent and amplitude-dependent and temperature-dependent characteristics. Then, combining the physical parameter model with the neural network model, an accurate hybrid neural network model of the hydraulic damper is proposed. The physical parameter model considers the damper structure, including orifice, damping valve, rubber joint and the relationship between temperature and viscosity of hydraulic oil. The neural network model describes the personality characteristics of the hydraulic damper, such as oil leakage, the internal friction force and the percentage of entrapped air in oil. Finally, the responses and the dynamic parameters of the hybrid neural network model are calculated and compared with the experimental results by considering various exciting amplitudes and frequencies. The results show that the proposed model can fully simulate the dynamic performance of the hydraulic damper under various operating conditions. [ABSTRACT FROM AUTHOR]

To fully consider the influences of the exciting frequency (0–20 Hz) and the environmental temperature (−50–20°C) on the dynamic characteristics of the rubber bushing in the railway vehicle, a hybrid neural network model is applied to develop the detailed model of the rubber bushing. The nonlinearities of the rubber bushing existing in the elastic element, the friction element and the viscous element are involved in the model to reflect the frequency- and amplitude-dependent characteristics of the rubber bushing. The experimental data are collected and exploited to find out the relationship between the input and output with the help of the neural network model. Furthermore, the influences of the environmental temperature on the dynamic parameters of the rubber bushing are considered. By testing the dynamic performance of the rubber bushing under the excitation with different frequencies, amplitudes and temperatures, the hybrid neural network model is trained and its critical parameters are identified. In this way, the trained hybrid neural network model for the rubber bushing can accurately reflect the dynamic performance in the presence of various excitation and environment temperatures. [ABSTRACT FROM AUTHOR]

The dynamic mechanical properties of rubber spring have great influence on the vehicle dynamic performance, so the accurate description of the mechanical properties of rubber spring has always been the focus of the train dynamics. Among the mechanical properties of rubber springs, the study of non-hyperelastic properties are the most difficult and complex. Therefore, this paper mainly studies non-hyperelastic forces. Based on the experimental data of rubber springs, an elliptic analysis model is derived to describe the non-hyperelastic properties of rubber springs. On the basis of this model, a modified model based on time change and a modified model based on displacement change are also proposed. The results show that the ellipse analysis model is simple, but the error of calculation is large; the calculation precision of time correction model is high, but the calculation process is complex; the displacement correction model is between the previous two models, with both accuracy and convenience. Compared with other models, the displacement correction model has great advantages, which can improve the accuracy of the calculation of train dynamics. It is suggested to adopt the rubber spring displacement correction model in engineering application. [ABSTRACT FROM AUTHOR]