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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]