High-speed Train System Research Articles

Adaptive feature fusion and disturbance correction for accurate remaining useful life prediction of rolling bearings

As a key component in the transmission system of high-speed trains, bearings need to withstand certain loads while rotating at high speeds. Once a failure occurs, it can directly affect the safety of train operations. Therefore, it is of great significance to establish a reliable remaining useful life model to ensure train operation safety. Addressing the problems of redundant features in the existing multi-feature fusion process, which affects diagnostic performance, and the spurious fluctuations in the fusion features, which cause inaccurate determination of the start fault time and lead to low prediction accuracy of remaining useful life, we propose a method based on adaptive feature fusion and the autoregressive integrated moving average model for rolling bearing prediction. Firstly, features from the time domain, frequency domain, and entropy are extracted. A feature selection mechanism with minimum redundancy is constructed to screen the optimal sensitive feature set. Secondly, based on adaptive feature fusion, the optimal sensitive feature set is dynamically fused, and the spurious fluctuations of the health index are corrected using linear regression and the 3σ principle. Next, a bottom-up time series segmentation method is employed to divide the health status of the Improved Health Indicators. Finally, a remaining useful life prediction model based on the autoregressive integrated moving average model is established. This study demonstrates that the proposed method effectively identifies features that are most sensitive to degradation trends, accurately determines the initial fault moment of bearings, and achieves effective prediction of the remaining useful life of bearings.

Numerical investigation on the heat dissipation of phase change materials used in the high-speed train brake system

The massive heat dissipation demands of the brake system in high-speed trains pose a significant obstacle to achieving higher operation speeds. Phase change material has attracted considerable attention in various fields due to their exceptional heat dissipation capabilities, yet their utilization in the brake system of high-speed trains remains unexplored. This study aims to investigate the feasibility of phase change material application in the brake system of high-speed train. Specifically, in Case A, the introduction of phase change material resulted in a notable 21% decrease in the average temperature and a remarkable 40% reduction in the maximum temperature difference within the brake system. The latent heat of the phase change material plays a crucial role in maintaining a substantial temperature differential between the cooling components and discs, thereby enhancing heat flux in the brake system. Phase change materials exhibit superior cooling performance compared to traditional air cooling methods in the brake system. To expedite the cooling process of phase change material and facilitate its transition from liquid to solid, an optimized brake system structure utilizing phase change material was proposed. This optimized design holds promise in enhancing the overall heat dissipation efficiency of the high-speed train brake system.

Mechanical and microstructure characterisation of 2.5D C/C-SiC composites applied for the brake disc of high-speed train

Carbon fibre reinforced silicon carbide (C/C-SiC) composite materials have attracted increasing attention in brake system of high-speed trains, due to their low density, high specific strength, thermal stability, and frictional wear performance. This study aims to explore the mechanical properties of the 2.5D C/C-SiC composites, in order to characterise its potential application to the friction braking system of high-speed trains. To comprehensively evaluate the mechanical performance of the 2.5D C/C-SiC composites, the chemical vapor infiltration (CVI) method was adopted to prepare novel samples with high densification and low content of residual Si. The mechanical properties and failure mechanisms of the composites were investigated under various loading conditions, including tension, compression, bending, and shear tests. The experimental results indicated that the 2.5D C/C-SiC composites exhibited superior mechanical properties, with average in-plane tensile strength, compressive strength, bending strength, and interlaminar shear strength reaching 127.67 MPa, 326.92 MPa, 355.74 MPa, and 9.77 MPa, respectively, which are 2–8 times higher than the mechanical properties of C/C-SiC composites in existing publications. Under different loading conditions, the composites demonstrated characteristics of ductile fracture, pseudo-plastic compression fracture, pseudo-plastic bending fracture, and brittle shear fracture. Both high fibre content and the formation of SiC structure were advantageous for enhancing the load-bearing performance of C/C-SiC composites. The outstanding mechanical properties of the 2.5D C/C-SiC composite render the brake disc highly resistant to deformation and cracking under high stress, thereby enhancing its durability and establishing it as the ideal material for the next generation of high-speed train brake discs.

Dynamic characteristics of electromechanical coupling of body-suspended drive system for high-speed trains under wheel polygonal wear

Wheel polygonal wear can trigger intense wheel–rail interactions in railway vehicles, posing a significant threat to traffic safety. However, the mechanism and interaction of the influence of wheel polygonal wear on the electromechanical coupling characteristics of high-speed trains remain unclear. Therefore, this paper proposes a joint simulation modelling method that takes into account the integration of the electrical subsystem with the complete mechanical subsystem. A comprehensive analysis is conducted on the dynamic response of the high-speed train’s body-suspended drive system under a wide range of frequency excitations arising from harmonic torque, gear meshing, and wheel polygon wear. The results indicate that the electrical system generates a substantial amount of harmonic frequency components, resulting in a significant increase in the vibration of the train. The wheel polygon wear causes a broadening of the low-frequency resonance band, revealing a relatively prominent observation interval for the dynamic characteristics. Concurrently, it is discovered that the 23rd-order wheel polygon wear excites the system’s resonance frequency, and as the wavelength of the wheel polygon increases, the acceleration vibrations intensify progressively. Research reveals first the interaction of electrical system and mechanical system under wheel polygon wear, especially in the resonance gain characteristics under polygons and harmonic torques.

An artificial potential field approach for event-triggered cooperative control of multiple high-speed trains with free initial states

ABSTRACT In this paper, a multi-algorithm-fusion-based cooperative tracking control strategy is proposed for high-speed trains to achieve the control objectives of reference speed trajectory tracking and adjacent safety distance maintenance simultaneously. First, the multiple high-speed train (MHST) system is formulated as a multi-agent system (MAS) with a virtual leader. Second, a coordination controller that considers the dynamic tracking performance and input saturation is designed by combining the MAS leader-follower consensus algorithm and the improved artificial potential field (APF) method. In addition, within the train-to-train (T2T) communication network, an event-triggered mechanism is introduced in the continuous state transmission process to address the communication channel capacity protection limitation issue. Third, the closed-loop stability of the MHST system is ensured by the comprehensive analysis of a novel log-type Lyapunov function. Finally, the effectiveness of the proposed event-triggered cooperative tracking control strategy is verified through a numerical example of the MHST system on a typical line.

Comprehensive degree of nonlinearity in the dynamic response of high-speed Maglev train

The aim of this study is to propose a method for evaluating the comprehensive degree of nonlinearity in the dynamic response of high-speed maglev train system through mathematical modeling and numerical simulation. A model of a typical high-speed maglev vehicle is established based on the principles of maglev vehicle dynamics, and control models for the suspension magnet and the guide magnet are developed using principles from the electromagnetism and automatic control theory. The vibration responses of the vehicle system, including acceleration and electromagnetic forces are calculated using a fast numerical integration method. This calculation is performed for various control parameters and track harmonic excitations. The Hilbert-Huang transform (HHT) is adopted to decompose the response signal and derive the local mean frequency (amplitude) and instantaneous frequency (amplitude) of the response, based on which the Degree of Nonlinearity (DN) of the vibration response of a single component is obtained by calculating the deviation between the instantaneous frequency and the mean frequency. The Comprehensive Degree of Nonlinearity (CDN) of the vibration response in the maglev train system is proposed and defined by incorporating the DNs of the vertical and lateral vibrations of the carbody, bogie, suspension magnet and guide magnet, and by quantitatively evaluating them. The effects of the electromagnet control parameters and harmonic irregularities (wavelength and amplitude) of the track on the DN of each component and the CDN of the entire vehicle system are analyzed in detail. The analysis results show that the DN and CDN can demonstrate the extent of instability in the vehicle system and can be applied for safety warning on maglev vehicles.

Generalized autoencoder-based fault detection method for traction systems with performance degradation

Fault diagnosis of traction systems is important for the safety operation of high-speed trains. Long-term operation of the trains will degrade the performance of systems, which decreases the fault detection accuracy. To solve this problem, this paper proposes a fault detection method developed by a Generalized Autoencoder (GAE) for systems with performance degradation. The advantage of this method is that it can accurately detect faults when the traction system of high-speed trains is affected by performance degradation. Regardless of the probability distribution, it can handle any data, and the GAE has extremely high sensitivity in anomaly detection. Finally, the effectiveness of this method is verified through the Traction Drive Control System (TDCS) platform. At different performance degradation levels, our method’s experimental results are superior to traditional methods.

A Loss-Model-Based Efficiency Optimization Control Method for Induction Traction System of High-Speed Train Under Emergency Self-Propelled Mode

A Loss-Model-Based Efficiency Optimization Control Method for Induction Traction System of High-Speed Train Under Emergency Self-Propelled Mode

Next-Generation Dual Transceiver FSO Communication System for High-Speed Trains in Neom Smart City

Smart cities like Neom require efficient and reliable transportation systems to support their vision of sustainable and interconnected urban environments. High-speed trains (HSTs) play a crucial role in connecting different areas of the city and facilitating seamless mobility. However, to ensure uninterrupted communication along the rail lines, advanced communication systems are essential to expand the coverage range of each base station (BS) while reducing the handover frequency. This paper presents the dual transceiver free space optical (FSO) communication system as a solution to achieve these objectives in the operational environment of HSTs in Neom city. Our channel model incorporates log-normal (LN) and gamma–gamma (GG) distributions to represent channel impairments and atmospheric turbulence in the city. Furthermore, we integrated the siding loop model, providing valuable insights into the system in real-world scenarios. To assess the system’s performance, we formulated the received signal-to-noise ratio (SNR) of the network under assumed fading conditions. Additionally, we analyzed the system’s bit error rate (BER) analytically and through Monte Carlo simulation. A comparative analysis with reconfigurable intelligent surfaces (RIS) and relay-assisted FSO communications shows the superior coverage area and efficiency of the dual transceiver model. A significant reduction of up to 76% and 99% in the number of required BSs compared to RIS and relay, respectively, is observed. This reduction leads to fewer handovers and lower capital expenditure (CAPEX) costs.

The correlation between structural deformation of friction system and friction-induced stick-slip vibration

Friction-induced stick-slip vibration (FISSV) commonly observed in various friction systems, such as the braking system of high-speed trains. The formation and development of FISSV are intricately associated with the structural deformation of the friction system. Therefore, we explored the correlation between structural deformation and FISSV. Using rigid structures with varied deformation capabilities, tests were conducted, and simulations performed. Results show a strong link between structural deformation and FISSV occurrence. Longer rod-holders increased deformation capability, intensifying FISSV. Systems with weaker deformation had stable interfaces and minimal eccentric wear (EW), reducing FISSV likelihood. Conversely, systems with greater deformation experienced prolonged stick durations, intensifying EW and challenging stable interfaces. Structural rigidity is crucial in friction system design to prevent FISSV, ensuring safe operation.

Vibration-Based Detection of Axlebox Bearing Considering Inner and Outer Ring Raceway Defects

The occurrence of an axlebox bearing ring raceway defect is an inevitable and commonly observed phenomenon in railway wheels. It not only leads to surface damage but also poses the potential threat of further damage and degradation, thereby increasing the risks associated with running safety and maintenance costs. Hence, it becomes imperative to detect raceway defects at an early stage to mitigate safety hazards and reduce maintenance efforts. In this study, the focus lies in investigating the effectiveness of vibration-based detection techniques for identifying raceway defects in high-speed train axlebox bearing systems. To achieve this, a dynamic model that accurately represents the coupling dynamics between the vehicle and the track is developed. This model incorporates various dynamic factors, such as traction transmission, gear transmission, and track geometry irregularities. By using the comprehensive dynamic model, the dynamic responses of the axlebox can be accurately calculated. The proposed methodology primarily revolves around analysing the vertical vibrations of the axlebox caused by raceway defects in both the time and frequency domains. Additionally, an envelope analysis using a developed band-pass filter is also employed. The results obtained from this study clearly demonstrate the successful detection of raceway defects in a more realistic vehicle model, thereby providing an efficient approach for the detection of axlebox bearing raceway defects. Consequently, this research contributes significantly to the field of high-speed train systems and paves the way for enhanced safety and maintenance practices.

Effect of Gear Tooth Cracks on the Dynamic Characteristics of Gear Transmission System of High-Speed Train

Abstract In order to study the dynamic characteristics of a high-speed train gear transmission system with cracks, time-varying meshing stiffness of gear teeth with different cracks was obtained using energy method. A torsional vibration model of the gear transmission system of a high-speed train was established. Based on the model, the ρ-value describing the change in stiffness was used to obtain the analytical solution of a system with crack faults. The influence of the degree of crack on the dynamic characteristics of a system under torque excitation of the driving end and load end was analyzed. In contrast with a normal gear system, a system containing a crack fault generated no harmonic response. Moreover, for a given set of working conditions, the degree of crack only affected the resonance amplitude and frequency of the system. These results form a robust guide for the detection of crack faults in the gear transmission system of a high-speed train.

Online Deep Learning for High-Speed Train Traction Motor Temperature Prediction

As the core component of the traction drive system of high-speed trains, the working condition of the traction motor is directly related to the operational safety of the train. During train operation, the temperature signal of the traction motor is constantly changing. Accurate prediction of the traction motor temperature using real-time data generated by sensors at the train end is beneficial for the early detection of abnormal motor conditions. The traditional approach is to apply prediction models from offline learning to the onboard side of the train for real-time temperature prediction, but its prediction accuracy degrades with the online data distribution changed. Therefore, this paper proposes an online deep learning model (ODL) for real-time traction motor temperature prediction. The ODL model uses DNN as its basic structure and hedging strategy to achieve online learning of the model parameters, which can dynamically adjust the model structure and parameters to adapt to streaming data with changing probability distributions. Finally, the study conducts multiple motor temperature prediction experiments using multi-sensor data from train operations. The results show that the ODL model outperforms the currently popular models in temperature prediction and can be effectively applied to real-time temperature prediction on the train end.

Harmonics suppression in high-speed railway via single-phase traction converter with an LCL filter using fuzzy logic control strategy

Introduction. The railway Traction Power Supply System (TPSS) encounters a common challenge related to high-frequency harmonic resonance, especially when employing AC-DC-AC traction drive systems in high-speed trains. This resonance issue arises when the harmonic elements introduced by the traction AC-DC converter on the grid side of trains align with the innate resonance frequency of the TPSS. The novelty the proposed work focuses on the challenges associated with resonance elevation and high-frequency harmonics in high-speed trains, while simultaneously enhancing energy quality. This is achieved by integrating a pulse-width-modulated converter on the grid side with a single-phase configuration and incorporating an LCL filter. Methodology. In order to optimize the system’s efficiency, a robust control system is employed, taking advantage of the capabilities of a fuzzy logic controller (FLC). The choice of the FLC is justified by its straightforward design and reliability, emphasizing the dedication to precise control, as fuzzy logic excels in handling complex, nonlinear systems. Through the use of linguistic variables and heuristic reasoning, the FLC adjusts to dynamic changes in the system, demonstrating its efficacy in enhancing both transient and steady-state responses. Practical value. A grid-side LCL filter-based converter was meticulously designed and rigorously simulated using the MATLAB/Simulink platform. The inclusion of an advanced FLC in the system introduced a novel approach to control strategies, surpassing the traditional PI controller. Through a comprehensive comparative analysis, the simulation results showcased the remarkable efficacy of the proposed solution in an effectively mitigating high-frequency resonance within the TPSS. This outcome underscores the potential of FLC as a sophisticated control mechanism for enhancing the performance systems in railway applications, showcasing its superiority over conventional control methods. The study contributes in shedding light on innovative approaches for optimizing the control and efficiency of grid-side LCL filter-based converters in high-speed train systems.

Investigation of a semi-active suspension system for high-speed trains based on magnetorheological isolator with negative stiffness characteristics

As the operation speed of high-speed train increases, trains with fixed suspension stiffness will encounter dramatical vibrations, especially when its lateral resonance occurs. This greatly affects the ride comfort and safety of the trains. Based on this motivation, a novel stiffness variable suspension system using magnetorheological elastomer (MRE) isolator with negative stiffness is proposed. The controllable stiffness can make the train avoid lateral resonance while the negative stiffness characteristics can provide an actuating force similar to the active control, which further improve the vibration attenuation performance of the suspension. The new MRE isolator was firstly fabricated and tested to verify its stiffness variability, especially negative stiffness characteristics. Four different suspension systems were then tested on a 6-DOF vibration platform for the performance comparison. The experimental results show that this new semi-active lateral suspension system has improved vibration attenuation performance than the passive system and the traditional MRE isolation system without negative stiffness. The vibration attenuation performance of the new suspension system is even comparable to that of some of the existing active suspensions while avoiding the disadvantages of the active control.

Robust Constraint-Following Control for Bio-Inspired Structure Oriented Active Suspension System of High-Speed Trains

Robust Constraint-Following Control for Bio-Inspired Structure Oriented Active Suspension System of High-Speed Trains

Reliability analysis for complex electromechanical multi-state systems utilizing universal generating function techniques

The large-scale adoption of complex electromechanical systems (CMESs) renders it challenging to perform reliability assessments for such systems. In terms of the reliability evaluation of CMESs, previous studies generally assume that only binary states exist within the systems. However, owing to the stochastic failures and various operating characteristics of the system components, not only the good/bad states but also the performance levels within the system should be taken into account when analyzing the reliability of CMESs. Hence, we abstract the CMES as a multi-layer and multi-state network in which minimum maintenance units (MMUs) and three types of connections constitute nodes and edges in different layers. Furthermore, multi-state models for different MMUs in the CMES are developed based on universal generating functions (UGFs). Aggregation operators are then utilized to aggregate these UGFs to obtain the multi-state models. Subsequently, a cascading failure model is introduced to incorporate MMUs into the system reliability assessment. Thus, the effects of the operating mechanism and topological attributes can be considered in the reliability evaluation of the CEMS. Finally, the CRHX high-speed train system is used as an example to demonstrate the applicability and effectiveness of the proposed method in the reliability assessment of the CMES.

Моделирование технического обслуживания и ремонта высокоскоростных электропоездов с использованием данных бортовых систем диагностики

Purpose: High–speed railway lines (HSRL) are the most promising direction of railway transport development in the 21st century, increasing the mobility of the population at a distance of up to 1000 km, contributing to the development of urban conglomerations. Reliable rolling stock is necessary for the functioning of the HSRL. The article describes the performed mathematical simulation of the operation and maintenance and repair system (MRS) of high-speed electric trains in relation to the St. Petersburg — Moscow landfill. The purpose of the simulation is to substantiate the requirements for MRS, including when using on-board automated systems for technical diagnostics. Methods: It is based on the principles of passenger traffic organization, technical requirements for domestic high-speed rolling stock, queue theory methods, as well as probabilistic mathematical modeling methods in MS Excel in the algorithmic language Visual Basic for Applications (VBA). The corresponding software has been developed. Results: A mathematical model and software have been developed, multifactor modeling has been performed, the degree of failure impact on the required fleet of high-speed electric trains has been determined. Methods of optimization of maintenance to reduce the required fleet are proposed. The requirements for the mathematical model itself are defined. A factor analysis of operation and maintenance has been performed by mathematical modeling. Practical significance: The guarantee of safe and reliable high-speed traffic is the creation of a modern system of maintenance and repair of rolling stock. The study of the interaction of operation and maintenance is very important in preparation for the launch of domestic high-speed traffic.

Thermal sensation prediction model for high-speed train occupants based on skin temperatures and skin wettedness.

Passenger thermal comfort in high-speed train (HST) carriages presents unique challenges due to factors such as extensive operational areas, longer travel durations, larger spaces, and higher passenger capacities. This study aims to propose a new prediction model to better understand and address thermal comfort in HST carriages. The proposed prediction model incorporates skin wettedness, vertical skin temperature difference (ΔTd), and skin temperature as parameters to predict the thermal sensation vote (TSV) of HST passengers. The experiments were conducted with 65 subjects, evenly distributed throughout the HST compartment. Thermal environmental conditions and physiological signals were measured to capture the subjects' thermal responses. The study also investigated regional and overall thermal sensations experienced by the subjects. Results revealed significant regional differences in skin temperature between upper and lower body parts. By analyzing data from 45 subjects, We analyzed the effect of 25 variables on TSV by partial least squares (PLS), from which we singled out 3 key factors. And the optimal multiple regression equation was derived to predict the TSV of HST occupants. Validation with an additional 20 subjects demonstrated a strong linear correlation (0.965) between the actual TSV and the predicted values, confirming the feasibility and accuracy of the developed prediction model. By integrating skin wettedness and ΔTd with skin temperature, the model provides a comprehensive approach to predicting thermal comfort in HST environments. This research contributes to advancing thermal comfort analysis in HST and offers valuable insights for optimizing HST system design and operation to meet passengers' comfort requirements.

Применение гармонических полуволн для автоматизации управления высокоскоростными поездами

The emergency braking processes in the European Train Control System (ETCS) of high-speed trains are associated with stepwise regulation of acceleration (deceleration) depending on the braking ability of the train, terrain data and changing weather on the route. These processes are defined in ETCS. The procedure for stepwise regulation of deceleration is carried out by the driver repeatedly in the process of braking until the train stops completely. The beginning of emergency braking and its end, as well as the braking process itself, is accompanied by repeated pulsed operation of the brakes, which leads to jumps in deceleration and, accordingly, to increased wear of the brake system, a decrease in comfort for passengers, which results in the limitation of the maximum allowable speed. The article proposes a new concept and technique for constructing mathematical models of emergency braking curves different from ETCS curves and based on harmonic half-waves. It is shown that the ETCS deceleration curves are described by known second-order power half-waves. Their joint study gives grounds to assert that the application of these curves leads to the obligatory pulsed mode of brake operation. Two new variants of models of emergency braking curves described by harmonic half-waves are proposed. The first option has one pulsed brake application at the end of the braking interval. The second option is free from braking impulses and allows the use of continuous regulation. These models explain the features of ETCS, contain proposals for their elimination, and are applicable to the development of new emergency braking curves that allow smooth control of emergency braking of trains. Efficiency, differences and advantages over ETCS braking curves are shown on the results of mathematical modeling of emergency braking processes.