A thermomechanical model has been developed and implemented to couple temperature, thermal expansion, contact, and wear using the finite element method. This three-dimensional, transient, and nonlinear model is unconditionally stable because of the use of an implicit solver. The weak form of the nonlinear heat transfer and elasticity equations has been derived, incorporating penalty contact, conduction, convection, radiation, and deformation. Several boundary conditions, including Dirichlet, Neumann, and Robin conditions, have been applied. We focus on mechanical train brakes due to their strong thermomechanical coupling effect. The simulation results have been validated against full-scale experimental data. Additionally, mesh sensitivity and time step sensitivity analyses are conducted to further assess the model’s accuracy. Friction heat is calculated at each time step through contact conditions, enabling the identification of hot spots and thermal cracks. The results demonstrate that this thermomechanical model is both efficient and robust. This model has been open-sourced, providing a powerful tool for advanced research in thermomechanical multiphysics analysis.

Pantograph collector strips on rail vehicles are subject to high wear, and a homogeneous wear distribution is crucial for reliable operation and for reducing replacement rates. This study uses numerical simulations and a drive cycle perspective to estimate wear patterns using a heuristic wear model. The purpose is a sensitivity analysis of the wear estimates with respect to variations in the pantograph-catenary dynamics. The simulated contact force dynamics at each time step are used to calculate the instantaneous wear rate and location. Operational conditions are replicated using a drive cycle comprising representative power-speed couples. Wear patterns are calculated for each operational stage and related to the underlying dynamic contact patterns. The wear patterns and rates for each stage are combined to form the resulting patterns for the entire drive cycle. The study finds that accurately estimating the wear pattern requires knowledge of the dynamic contact distribution of the wire on the collector strip. The contact pattern in section overlaps has a noticeable influence and should always be considered. The distributions of dynamic contact instances and wear rate closely match across the studied cases. Considering variations in mean contact force dependent on lateral contact position further improves the wear estimate.

A railway switch is a vital component for its safe, reliable, and time-bound operations. Faults in switches are common in locations experiencing winters due to snow or ice buildup, despite using heating systems. The majority of switches are electrically heated, and guidelines for their efficient operations have been studied in this work. A computational model has been created to understand the temperature distributions in switch heating systems, and it has been verified from the annual heating data of an operational switch in Sweden. The results from a parametric study by varying ambient temperature, wind load, and heating element power can be used to implement heating control strategies in existing heaters, which will support their sustainable operations. In addition, the feasibility of using ground-source borehole renewable energy is also investigated for different bedrocks. The results of the temperature drop in the borehole for a constant winter heating load over 15 years give insights on the potential usage of ground heat in switch heating.

The electrical road system (ERS) truck formation operation is the most common working condition of this new road freight transportation system. Because two neighbouring trucks with unfavourable distance can interrupt the current collection process, the favourable distance must be obtained to prevent it. In this work, the influence of truck formation operation on pantograph-catenary interaction dynamics in ERS is first investigated to determine this favourable distance. Based on the structure of the ERS test line, an ERS pantograph-catenary model with double pantograph is formulated, and the measurement data from the ERS test line are used to validate the present model and provide truck vibration inputs. Through the present model, the influence of double pantograph distance on its dynamic behavior is investigated. It is found that the pantograph distance without truck vibration has little influence on pantograph-catenary interaction, but the truck vibration can heavily influence the same within a certain distance. This influence is dominated by the second frequency peak of the truck vibration, and its change in the panhead can be used to monitor the distance. Based on this, a method is finally given to determine the closest favorable distance between neighboring trucks in ERS.

The continuous movement of high-speed train results in the pantograph interacting with a long catenary structure. The traditional methods based on the Lagrangian description can only model the whole long catenary structure, which decreases their calculation efficiency. In this work, a reduced pantograph–catenary interaction model is developed to accurately and efficiently simulate the pantograph-catenary interaction with the long catenary structure. In the model, the long catenary is reduced to a small region around the moving pantograph, and the arbitrary Lagrangian‒Eulerian (ALE) method and modal superposition method (MSM) are used to model this small area. The pantograph is modeled as a multi-rigid body system. The pantograph and reduced catenary model formulate the reduced pantograph–catenary interaction model. Because the long catenary structure is reduced to a small moving region, the number of degrees of freedom (DOF) of the model is significantly decreased. The present model is validated by the EN 50318:2018 standard with a long catenary structure considered. The calculation results show that the present model is accurate and efficient in the investigation of long-term pantograph-catenary interaction dynamics.

Crosswind is a critical environmental factor affecting the dynamic interaction between the pantograph and catenary in high-speed trains, which can severely compromise the operational stability of the system. To address this challenge, this study develops an active pantograph control scheme for crosswind disturbances by employing a neural network-based PID controller. First, the target value is determined based on the train operating speed and inherent data of the pantograph-catenary system, and a PID controller is constructed. Subsequently, a neural network is integrated into the controller to train the system's output contact force and PID parameters using its nonlinear approximation capability, thereby optimizing the parameters and achieving effective control of the system. The effectiveness of the controller is then validated by applying the proposed method to a high-speed train pantograph-catenary system under crosswind conditions, with its control performance thoroughly analyzed. The results indicate that the proposed control scheme demonstrates effective regulation of the pantograph-catenary system across various typical crosswind scenarios, achieving significant reduction or even complete elimination of pantograph-catenary's contact loss rate while exhibiting strong robustness, thereby proving fully applicable for practical implementation in high-speed railway engineering applications.

Electrified roads, as a novel low-carbon / zero-carbon heavy-duty truck transportation system, are essential for achieving“dual-carbon”targets in the transportation sector. However, the economic feasibility of this system relative to other heavy-duty truck transportation modes has not been sufficiently discussed. [Objective] Therefore, a cost model for different modes of heavy-truck transportation systems is constructed to promote the transformation of heavy-truck transportation modes from an economic perspective and promote the sustainable development of road transport. [Methods] The lifecycle cost method is used to integrate the costs of infrastructure construction, vehicles, battery replacement, energy consumption, and maintenance. By performing a sensitivity analysis of the key factors, the cost differences between different heavy-duty truck transportation system modes are examined. The cost variation trends for each transportation mode over different operational lifespans are disclosed. [Results] As the number of operational years increases, electrified roads demonstrate substantial advantages owing to their lower energy consumption costs and the gradual amortization of initial construction expenses. In particular, the segmented contact-network installation scheme incurs a low cost. Electricity tariffs and battery prices significantly affect the cost of the segmented contact-network installation plan. However, oil-price fluctuations have the most pronounced effect on conventional fuel-based schemes compared with other factors. [Conclusions] As the cost of fossil fuels increases gradually and the cost of batteries decreases, an electrified road system with a segmented catenary erection scheme is show to be optimal for reducing carbon emissions and transportation costs.

The emissions from traditional fossil heavy-duty trucks have become a conspicuous issue worldwide. The electrical road system (ERS) can offer a viable solution for achieving zero CO₂ emissions and has high energy efficiency in long-distance road cargo transport. While many kinds of pantograph structures have been developed for the ERS, their corresponding pantograph-catenary dynamic characteristics under different road conditions have not been investigated. This work performs a numerical study on the dynamics of the pantograph-catenary interaction of an ERS considering different pantograph structures. First, a pantograph-catenary-truck-road model is proposed. The reduced catenary model and reduced-plate model transmission method are used to minimize model scale. Three different types of ERS pantograph structures are considered in the model. After validation, the pantograph-catenary dynamics under the influence of truck-road interactions with complex road roughness and different pantographs are studied and compared. The corresponding vibration transmission mechanism is further focused. The results show that the truck-road interaction has a significant effect on the pantograph-catenary interaction, but the pantograph with only one lower and upper arm can isolate the roll vibration motion transmission from the truck to the collector head, which has the best dynamic performance and is suggested for use in the ERS.

Traction motors, as essential electromechanical energy conversion devices, play a vital role in heavy-haul locomotives. The transition of railway transportation to higher power, higher speeds, and heavier axle loads intensifies dynamic interactions within locomotive traction systems. This shift results in more frequent motor failures, significantly affecting the performance of the traction transmission system. Previous studies have relied on dq-axis motor models, making it challenging to adjust motor parameters to accurately simulate various motor fault types and severities. Consequently, the impact of motor faults on locomotive traction transmission systems has not been thoroughly explored. To address this gap, this paper aims to develop a locomotive dynamics model incorporating the traction transmission system. The model replaces the dq-based motor model with an improved multiple coupled circuit model considering the interaction between the stator and rotor-bearing system. This enables a more precise simulation of the electromechanical dynamic interactions of traction motors within the traction transmission system under varying levels of fault severity. The electromechanical response characteristics and influence laws of the traction transmission system under conditions of broken rotor bars and stator inter-turn short-circuit faults are investigated. The results indicate that broken rotor bars cause low-frequency fluctuations in stator current, pulsating torque, and significant variations in wheel–rail longitudinal forces. An increase in broken rotor bars further amplifies fluctuations in the electromechanical response. Stator inter-turn short circuits result in three-phase current unbalances and elevated amplitudes at specific frequencies. The short-circuit turn ratio exerts a more significant influence on current unbalance than the short-circuit resistance. Under motor faults, the electromechanical coupling effects become weakened. This research provides a theoretical foundation for fault diagnosis in locomotive traction motors.

Rail corrugation is a typical rail cyclical disease which often occurs on heavy haul, urban transit, and high-speed railways. Rail corrugation has a significant impact on vehicle dynamic performance, especially on the axle box acceleration. It may cause the bolts of axle box to loosen or break the rail fastener, and even affect the operation of vehicle. Therefore, it is necessary to discover rail corrugation in time and to repair it by rail grinding, which is an important way to improve the safety of the vehicle. A numerical analysis method based on adaptive time-frequency feature extraction is proposed in this paper. First, acceleration sensors are installed on both the left and right side of the axle box. Then the vibration features of the axle box are extracted according to the line mileage segmentation based on the adaptive time-frequency feature extraction method proposed in this paper. Finally, the impact of different wavelength and different section length of rail corrugation is compared using field test data. The test results show that the method proposed in this paper can accurately extract the features of different wavelength and different section length of rail corrugation. Moreover, compared with traditional methods, this method is proven to be strongly adaptive and highly accurate.