Wheel polygonal wear, especially high-order polygonal wear, has emerged as a significant challenge for Chinese railways over the past decade. The wheels of high-speed trains, locomotives and metro trains suffered from polygonal wear. Wheel out-of-roughness (OOR) of more than 43,000 wheels was collected in this study, including 30,500 high-speed train wheels, 9,136 metro wheels, and 3,396 locomotive wheels, which were measured in various measurement campaigns using high-precision wheel roughness instruments. The features of wheel OOR are analysed based on big-data and formulas for the wheel roughness spectrum of the three rolling stocks are determined. It is found that high-order wheel polygonal wear is a common problem in locomotives, metro trains, and high-speed trains. The OOR of metro wheels is more pronounced compared to that of locomotive and high-speed train wheels. There is a clear correlation between the high incidence period of high-order wheel polygonal wear and the circumference of the wheels, especially for high-speed wheels. The distribution of radial run-out and the peak roughness level of low- and high-order wheel OOR are also obtained. This paper provides statistically meaningful information that can be used to develop wheel maintenance strategies considering vibration and noise, fatigue reliability, and ground-borne vibration.

This paper focuses on the nonlinear shimmy behaviour subjected to the unbalance excitation generated by the unbalanced mass of the wheel. First, a mathematical model of towed wheel is established, the system stability is analysed by neglecting the unbalance excitation. To analytically predict the limit cycle of the system, the complex variables are introduced to derive the slow flow equations, the equilibrium equation and characteristic equation of the towed wheel subjected to the unbalance excitation are also obtained. Then the torsional damping and lateral damping of the suspension are selected as interested parameters, the dynamic bifurcation and system response are explored at the resonance speed, different types of amplitude jump are discovered. Especially, when the system damping is greater than the critical damping, although the self-excited shimmy can be suppressed, the system response suddenly jumps from a limit cycle with small amplitude to a limit cycle with large amplitude for a large enough initial disturbance, which is not conducive to the system stability and needs to be avoided by further increasing the system damping. Finally, numerical experiments are carried out to validate the bifurcation analysis, the results can provide better theoretical guidance to suppress the nonlinear shimmy subjected to the unbalance excitation.

This paper focuses on the difficulty in characterising the complex mechanical behaviour and deformation characteristics of jointless turnouts at high altitudes. Considering its unique characteristics of large altitude differences, large temperature variations, frequent traction actions, vast uninhabited regions, and high failures risks, a rigid-flexible coupling dynamics model of the vehicle-jointless turnout on steep slope under the combined effects of extreme temperatures and actual vehicle loads is established. The model considers the flexible deformations of the turnout along the longitudinal, lateral, and vertical directions, enabling precise representation of temperature loads and the elastic-plastic characteristics of the longitudinal resistance of fasteners within the multi-body dynamics. The research indicates that the coupling effect of extreme temperature and vehicle impact loads can cause the longitudinal resistance of fasteners to exhibit oscillatory effects during the plastic stage, leading to a significant increase in the peak values of longitudinal creep force, shear stress, and wear index of wheel rail, exacerbating rail damage and deterioration. Extreme temperature increases can induce an advancement in the wheel load transition position, with a forward shift value reaching 0.49 m when the temperature increases by 45°C, thereby intensifying wheel-rail impacts.

The bogie frame of high-speed electric multiple units in China is subjected to more complex fatigue loads, significantly increasing the risk of fracture. However, current research lacks a comprehensive dynamic model that accounts for the presence of cracks in the flexible bogie frame within a rigid-flexible coupled vehicle system. To address this gap, this study develops a novel rigid-flexible coupled vehicle dynamic model to investigate the fracture behaviour of bogie frames with cracks. The motion equations of the vehicle model, incorporating crack effects, are firstly derived and validated for accuracy and effectiveness. Numerical results reveal that Mode-II fracture mode primarily governs crack propagation at all critical positions studied. It is observed that during vehicle operation, the maximum dynamic energy release rate generally increases with crack size, with the peak value shifting to different points along the crack front. Among the three critical positions examined, when a single crack is present, the crack at the curved area of the top cover plate exhibits a higher likelihood of propagation. In scenarios where two cracks are present, the crack located at the gearbox suspender seat is more prone to propagation.

In the context of automated driving, articulated HGVs, such as tractor-semitrailers are popularly used for goods transportation. They are advantageous due to their larger capacity, but their increased mass and size pose lateral instability issues which may lead to safety-critical situations. Automated steering controllers capable of precise path-tracking and improved lateral stability may help avoid such problems. Here, we present two lateral controllers: Front Axle Reference (FAR) and Adaptive Reference (AR). FAR provides precise path tracking at the front of the vehicle, while AR drives more like a human driver, reducing the overall offtracking of the vehicle while ensuring stability. Both controllers are designed using Artificial Flow Guidance (AFG), which provides a motion reference based on path geometry. Simulations carried out for a broad range of speeds show centimetre-level path-tracking precision and improved lateral stability compared to the simple and familiar Pure Pursuit method. Controller performance is also seen to be robust to changes in trailer mass. Preliminary experimental results, conducted at low-speeds, tend to support these findings.

This paper focuses on insufficient perception in blind scenes and the failures of the actuator and sensor of vehicle suspension. The safe speed is designed and the fault-tolerant strategy based on the observer is designed when the actuator and sensor fail simultaneously. A speed planning strategy to ensure that vehicles operate at a safe speed is proposed. The Markov suspension fault jump model considering the suspension sensor and actuator faults is established. Based on the fault estimation obtained by the fault observer, a fault tolerance control strategy of sensor signal reconstruction and actuator fault compensation is adopted. The measurement index for evaluating fault tolerance effectiveness has been established, and an exploration of fault tolerance control is conducted across various fault levels, to identify the preferred fault tolerance strategies corresponding to different levels of fault tolerance. The simulation results show that the designed speed control strategy can improve vehicle safety by decelerating in advance, the fault observer is capable of accurately estimating the true values of actuator and sensor faults. The simulation and vehicle test results demonstrate that similar suspension performance has been obtained by fault-tolerant control strategy and preferred fault tolerance under different fault tolerance levels compared with normal fault tolerance.

To investigate the influence of the lag time in braking response of the slave control locomotives caused by the LOCOTROL wireless synchronous control system on the longitudinal impulse of the train, a 30,000-ton heavy-haul train model was established. The model is in the form of ‘1+1+1+1’. The simulation accuracy of the air braking system was verified by comparing with static tests. A dynamic model consisting of two HXD1 locomotives and a 100-type couple was established for study the middle locomotive’s running safety. Results show that, under normal transmission delays, the lag time in the braking response of the slave control locomotives is approximately 2–3 s. The lag time significantly influence the coupler force and its distribution law. During emergency braking, the lag time increased from 0 s to 6 s, and the maximum coupler force increased by 1877.1 kN. Among the three slave control locomotives, the one positioned in the middle has the greatest impact on the coupler force, while the one closest to the leading locomotive has the least impact. When the lag time reaches 5 s, the middle locomotive’s coupler becomes unstable. Increasing the lateral stiffness of the secondary suspension is beneficial for enhancing the locomotive's ability to stabilise the coupler.

Ensuring lateral stability is essential for achieving excellent operation safety and ride comfort of high-speed trains. However, complicated operational environments, particularly various wheel-rail contact geometries, would result in the occurrence of hunting instability. This study presents an innovative passive yaw damper to improve the stability of a high-speed train undergoing extreme wheel-rail contact conicities. A sensitivity analysis of the vehicle stability is first performed to demonstrate the importance of the dynamic stiffness of yaw dampers, promoting the application of the innovative damper. Experimental characterisation procedures enable the detailed investigation into the static and dynamic characteristics of the innovative damper, which are compared with those of conventional passive dampers to highlight the difference. To simulate the dynamic behaviour of the yaw damper, a numerical modelling method based on the Maxwell model is proposed. Using this method, the effectiveness of the innovative damper is assessed in terms of improving the vehicle stability at various wheel-rail conicities. The results show that the innovative yaw damper can ensure carbody stability at low conicity and bogie stability at high conicity, superior to conventional dampers, which fail to balance the vehicle stability at distinct conicities and usually result in hunting instability in specific wheel-rail contact states.

This study proposes the use of active lateral secondary suspension (ALS) to address low-frequency carbody swaying in high-speed rail vehicles under low wheel-rail conicity conditions. Field experiments reveal lateral acceleration exceeding 0.10 g at a dominant frequency of 1.4 Hz, with a Sperling index exceeding 3.0 during carbody swaying occurs. By integrating field-measured wheel/rail profiles and yaw damper parameters into a multibody dynamics model of vehicle system, the coupling between bogie hunting and carbody yaw and upper-center roll modes is identified as the root cause of swaying. Evaluating classic sky-hook ALS controls, damping control proves highly effective. Doubling the damping coefficient and blow-off force becomes essential when only half of the four actuators per vehicle are active. Stiffness control adjusts carbody suspension modal characteristics to prevent resonances with the bogie hunting mode, effectively suppressing swaying. In contrast, inerter control exhibits limited efficacy. Semi-active control, with optimised gain settings, can also alleviate swaying, with control system delay identified as a critical factor, suggesting a 100 ms limit for effective swaying suppression.

Modelling train dynamics is essential for the platoon control of virtually coupled train sets (VCTS). Variable rail-wheel conditions and high data collection costs pose substantial challenges for both physics-based and data-driven models, especially when unit trains in the VCTS are heterogenous. This study introduces a train dynamics model that integrates parameter identification of basic resistance with physics-informed neural networks. The developed physics-informed neural network for train dynamics modelling (PINN-TDM) identifies key resistance parameters using the Davis formula. By combining the strengths of traditional modelling and data-driven approaches, the PINN-TDM provides accurate predictions of train dynamics, accommodating variations due to changes in rail-wheel conditions and heterogeneity among unit trains. Compared to conventional neural network models that lack physical guidance, the PINN-TDM demonstrates enhanced performance in data-limited conditions. Furthermore, this study incorporates the PINN-TDM into a model predictive control framework and derives the sufficient condition for heterogeneous string stability in the frequency domain using the Laplacian transformation. This enables the analysis of the impact of train dynamics heterogeneity on the stable region. Simulation experiments show that the integrated controller improves the precision of trajectory tracking and the stability of the VCTS under diverse rail-wheel conditions.