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In this paper, the noise reduction performance of the active steering bogie, developed to address wheel and rail wear and reduce noise during train operation in curved sections, was evaluated. A prototype of the active steering bogie was installed on the test train, and noise reduction performance by active steering control was measured in curved sections of a commercial line with a radius of curve of 300 m or less. The results of the test run confirmed that both the wheel and car interior noise were reduced when active steering control was applied, compared with the case where it was not applied. According to the test results in the curved section with the most noise reduction effect, the equivalent noise level was reduced by 6.6 dB for wheels and 4.7 dB for the car body by active steering control. In addition, analyzing the frequency characteristics by wheel steering control has confirmed that the squeal noise mode generated in the 300 to 2000 Hz band during curve running was significantly reduced. Therefore, the noise reduction performance of the active steering bogie, developed to improve steering performance in curved sections, has been sufficiently verified through the test results. [ABSTRACT FROM AUTHOR]

This article investigates a 27-degree-of-freedom dynamic model of a full-scale railway vehicle. The controlling action is performed by developing a decentralized control structure with five independent Fraction Order Proportional Integral Derivative (FOPID) controllers three types of random track irregularities, vertical profile, lateral alignment, and cross-level. A novel metaheuristic optimization technique named hybrid Particle Swarm Optimization-Gray Wolf Optimization (hybrid PSO-GWO) is proposed to optimize active force for an active suspension system. The simulated results show that the hybrid metaheuristic algorithm outperforms with a significant reduction in vehicle vibration ensuring enhanced ride comfort of the car body. [ABSTRACT FROM AUTHOR]

The air spring for railway vehicles uses the air pressure inside the bellows to absorb vibration and shock to improve ride comfort and adjust the height of the underframe with a leveling valve to control stable driving of the train. This study developed augmented reality content that proposes a novel visual technology to effectively support the training of air spring maintenance tasks. In this study, a special effect algorithm that displays the dispersion and diffusion of fluid, and an algorithm that allows objects to be rotated at various angles, were proposed to increase the visual learning effect of fluid flow for maintenance. The FDG algorithm can increase the training effect by visualizing the leakage of air at a specific location when the air spring is damaged. In addition, the OAR algorithm allows an axisymmetric model, which is difficult to rotate by gestures, to be rotated at various angles, using a touch cube. Using these algorithms, maintenance personnel can effectively learn complex maintenance tasks. The UMUX and CSUQ surveys were conducted with 40 railway maintenance workers to evaluate the effectiveness of the developed educational content. The results showed that the UMUX, across 4 items, averaged as score of 81.56. Likewise, the CSUQ survey score, consisting of 19 questions in 4 categories, was very high, at 80.83. These results show that this AR content is usable for air spring maintenance and field training support. [ABSTRACT FROM AUTHOR]

Comfort has traditionally been assessed as a single deterministic index that can be assigned to each railway vehicle type (at a given speed on a given track quality level). However, it is now well established that passengers influence vibration and, as a consequence, occupancy level and seating arrangement influence comfort, thus turning it into a stochastic variable. The concept of Compound Comfort, presented in Palomares et al. [Is the standard ride comfort index an actual estimation of railway passenger comfort? Veh Syst Dyn. 2022;1–14. doi: ], is used in this paper to evaluate several train types. Simplified models are used as a first approximation for vibration analysis. Despite model simplicity, since the number of possible seating arrangements is intractable, a Monte Carlo procedure is used to obtain compound comfort probability density distributions from a randomised subset of cases. The results from the work presented here will show that the information provided by stochastic distributions is much richer than a single deterministic index. Nevertheless, obtaining distributions from Monte Carlo tests (numerical or experimental) is impractical for any commercial assessment of comfort. Therefore, an inference procedure is called for and has been devised in order to obtain probability density function parameters from just one tare test, along with ten runs of a half laden test. This recipe has been adapted from one presented previously to be able to accommodate the skewed distributions that emerge when a wide range of train configurations is considered. [ABSTRACT FROM AUTHOR]

Recently, research on condition-based maintenance (CBM) using artificial intelligence has attracted attention to reduce the maintenance costs of railway vehicles. The air compressor of a railway vehicle that adopts an air brake system is a target for CBM, and in order to reduce maintenance costs and ensure driving stability, technology to detect anomalies in the air compressor is necessary. The long short-term memory (LSTM) autoencoder is used to process sequence data. However, LSTM has limitations in that it cannot perform parallel processing due to its recurrent neural network characteristics, and it is difficult to learn the dependency between data as the sequence data lengthens. In this paper, we propose a novel transformer architecture as an anomaly detection model to learn dependency between air compressor data of a railway vehicle and we demonstrate superior data reconstruction and generalization ability of proposed transformer. We conduct simulation tests based on actual railway vehicle air compressor data and confirm improved anomaly detection performance. We propose an anomaly score definition method using mean squared error to perform reconstruction error-based anomaly detection. With the successful anomaly detection results in the air compressor of a railway vehicle, we demonstrate the effectiveness of a proposed anomaly detection algorithm that applies the moving average of anomaly scores and defines anomaly criteria using three-sigma. We test the proposed anomaly detection method using sensor data received from actual urban railway air compressors and prove its usefulness. [ABSTRACT FROM AUTHOR]

In recent years, railway vehicles have become lighter since it corresponds not only to the improvement of the running speed but also to the reduction of running cost and environmental noise. On the other hand, this causes an increase in the vertical elastic vibration of the car body and the riding comfort has deteriorated. Therefore, various strategies to reduce vertical vibration have been studied. In this study, vertical vibration reduction, by controlling the internal pressure of the air spring using µ-synthesis control, is proposed. The merit of µ-synthesis control is that it can guarantee robust performance. A controller by µ-synthesis was designed for vibration reduction of a 1/6 scale railway model and compared nominal performance and robust performance with H∞ control theory. Moreover, a feasibility study of this strategy was investigated for full-scale railway vehicles through simulation. [ABSTRACT FROM AUTHOR]

Objective As a braking mode,electromechanical brake adopts the motor controlled screw rod drive to implement the pushing action, making the brake shoe to contact with the wheel and complete the transmission of brake force and friction brake. It is necessary to study the influence of the new brake mode on the vibration performance of rail transit vehicle. Method The basic structure and the composition of the electromechanical brake and air brake are introduced. The push-out stiffness test and track vibration test of the above two brakes are carried out and the influence of the brake push-out stiffness on vehicle vibration is analyzed. Result & Conclusion The stiffness test shows that the push-out stiffness of the electromechanical brake is much higher than that of the air brake in the normal working area and shows nonlinear characteristics, because it is driven by the motor and not equipped with stomatal piston as the air brake does. In line testing when the electromechanical brake is installed on the vehicle, it is found that compared with the air brake, the electromechanical brake will aggravate the vehicle brake vibration due to the large push-out stiffness, and the vibration acceleration of key components of the vehicle will also increase. Based on the research results, it is suggested that the push-out stiffness of the electromechanical brake shall be reduced to ensure smooth and safe brake processes for vehicles.

Modifying the car body structure from the existing train to another car body type requires an analysis of several factors. The strength of the design due to overload and the durability of the structures due to operational loads need to be re-evaluated. Furthermore, stiffness analysis also needs to determine the characteristics of the structure when it is not loaded. This study numerically analyzed the considerations in selecting the structural steel profile for modification of the existing car body into a panoramic type using the ANSYS Workbench R19. The underframe structure can still be used, and other structures are modified with the UNP profile. The side wall, and roof are changed in shape and size following the glass design of the panoramic train. The solid 3D model is rebuilt into a surface model to simplify the analysis. Static structural analysis is used to clarify the strength of the design under overload, a combination of static and transient structural analysis is applied to calculate the operating life, and modal analysis is chosen to figure out the stiffness. The simulation results showed that the modified design had met the needs and requirements based on the PM 175 standard of 2015 by the Indonesian Ministry of Transportation and the international standard EN-12663.

Track irregularities directly affect the quality and safety of railway vehicle operations. Quantitative detection and real-time monitoring of track irregularities are of great importance. However, due to the frequent variable vehicle speed, vehicle operation is a typical non-stationary process. The traditional signal analysis methods are unsuitable for non-stationary processes, making the quantitative detection of the wavelength and amplitude of track irregularities difficult. To solve the above problems, this paper proposes a quantitative detection method of track irregularities under non-stationary conditions with variable vehicle speed by order tracking analysis for the first time. Firstly, a simplified wheel–rail dynamic model is established to derive the quantitative relationship between the axle-box vertical vibration and the track vertical irregularities. Secondly, the Simpson double integration method is proposed to calculate the axle-box vertical displacement based on the axle-box vertical acceleration, and the process error is optimized. Thirdly, based on the order tracking analysis theory, the angular domain resampling is performed on the axle-box vertical displacement time-domain signal in combination with the wheel rotation speed signals, and the quantitative detection of the track irregularities is achieved. Finally, the proposed method is validated based on simulation and field test analysis cases. We provide theoretical support and method reference for the quantitative detection method of track irregularities. [ABSTRACT FROM AUTHOR]

Copyright of Urban Mass Transit is the property of Urban Mass Transit Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We developed a driving energy simulator to study fuel cell output control of a hybrid test train. The simulator takes into account that the powering and regenerating performance of the test train depends on the SOC of the battery. The simulator was validated by confirming that it matched the driving test data. And the running simulation was carried out on a 15 km virtual route to show the efficiency and fuel consumption of the fuel cell. [ABSTRACT FROM AUTHOR]

Copyright of Rolling Stock (1002-7602) is the property of Rolling Stock Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper presents the implementation of the dual extended Kalman filter (DEKF) to estimate wheelset equivalent conicity, an accurate understanding of which can facilitate the implementation of an effective model-based estimator. The estimator is developed to identify the wheelset equivalent conicity of high-speed railway vehicles while negotiating a curve. The designed DEKF estimator employs two discrete-time extended Kalman filters combining state and parameter estimators in parallel. This estimator uses easily available measurements from acceleration sensors measuring at axle boxes and a rate gyroscope measuring bogie frame yaw velocity. Two tests, including linearized and actual wheel-rail geometry, are carried out at a speed of 250 km/h with stochastic and deterministic track features using multibody simulations, SIMPACK. The results with acceptable estimation errors for both track conditions indicate adequate performance and reliability of the designed DEKF estimator. They demonstrate the feasibility of utilizing this DEKF method in rail vehicle applications as the knowledge of time-varying parameters is not only important in achieving an effective estimator for vehicle control but also useful for vehicle condition monitoring. [ABSTRACT FROM AUTHOR]

This study investigates a new method for the effective application of active secondary suspension for reducing vertical vibration of the carbody to improve ride comfort of railway vehicles. So far, most previous control methods have contributed to reducing the vibration of the rigid body modes of the carbody at approximately 1 Hz or the first bending mode at approximately 10 Hz. However , in modern high-speed vehicles, higher frequency vibrations generally have a relatively greater influence on vertical ride comfort than vibrations of around 1–2 Hz. Focusing on this fact, the authors propose active secondary suspension with feedback control of the vertical vibration velocity of the bogie frame as a method for reducing carbody vibrations in a wide frequency band above 2 Hz to improve ride comfort. Numerical simulations were carried out to simulate the actual running of a Shinkansen using a vehicle model corresponding to a Shinkansen vehicle with 14 degrees of freedom, considering the vertical and longitudinal dynamics of the vehicle. The results show that this method is mainly effective in reducing vertical carbody vibration above 3 Hz and that the frequency band for vibration reduction can be extended to 1 Hz or lower by combining this method with feedback control of the vertical displacement of the bogie.

The gear transmission system is one of the essential subsystems of railway vehicles. The wheel polygonalization can affect the gear transmission system's condition monitoring and fault diagnosis, causing fatigue failure of the gear system and influencing driving safety. Therefore, to explore the mechanism of the wheel polygonalization in the gear system, this paper develops a Lagrangian form dynamic model of a railway vehicle with a gear transmission system. The model validation uses the data from the field test. The analysis explores the influence of the wheel polygonal fault on the gear transmission system under the traction condition. The results indicate that the wheel polygonal fault has amplitude/frequency modulation effects on the time/frequency response of the gear system. Also, the wheel polygonal fault causes the envelope of the speed curve to fluctuate periodically at a low frequency under traction conditions. The waveform asymmetry is gradually apparent as the traction continues. In the non-resonant region, the statistical analysis of the rotational speed fluctuation illustrates that the order of the wheel polygonal fault has more impact on the rotational speed fluctuation than the amplitude. Besides, in the resonance region, the eigenvalues of the system determine the magnitude of the amplitude. [ABSTRACT FROM AUTHOR]

It is a challenging task to accurately diagnose a railway bearing fault since bearing vibration signals are under strong interferences from wheel–rail excitations. The commonly used Kurtogram-based methods are often trapped in components induced by the wheel–rail excitations while adaptive mode decomposition methods are sensitive to input control parameters. To address these issues, based on a recently developed powerful signal decomposition method, that is, adaptive chirp mode decomposition (ACMD), a novel method called bandwidth-aware ACMD (BA-ACMD) is proposed in this article. First, the filter bank property of ACMD is thoroughly analyzed based on Monte-Carlo simulation and then a bandwidth expression with respect to the penalty parameter is first obtained by fitting a power law model. Then, a weighted spectrum trend (WST) method is proposed to partition frequency bands and then guide the parameter determination of ACMD through the integration of the obtained bandwidth expression. In addition, according to the order of magnitude of the WST in each band, the BA-ACMD adopts a recursive framework to extract signal modes one by one. In this way, dominating signal modes related to wheel–rail excitations can be extracted and then subtracted from the vibration signal in advance so that the bearing faults induced signal modes can be successfully identified. Both simulation and experimental validations are conducted showing that BA-ACMD can effectively detect single and compound faults of railway bearings under strong wheel–rail excitations. [ABSTRACT FROM AUTHOR]

The most general purpose of the current paper is to trace and discuss the history and state of the art of studies on vehicle motion (dynamics) in a transition curve above the critical velocity, with the aim of potentially increasing the circle of researchers involved in studying this issue and strengthening the will of the authors to continue their studies. This general goal is achieved in two ways: first, through a profiled literature analysis, showing the historical progress and current state of the research; and second, through reference to the history of stability studies as an example of selected studies' development. In addition, this work has two more specific goals. Together, they consist of collecting the literature in a related field in one place and analyzing it on site to accomplish the review. Both specific goals are attained by dividing the literature into two corresponding parts. In the first part, the current issues of rail vehicle stability are analyzed and divided into four problems. The second part includes works that deal with the subject of the motion and dynamics of a rail vehicle on a transition curve section. Here, the works are divided into five groups and discussed. They are put in order from the closest to the furthest from this paper's main subject; however, the last group includes the most recent references. In addition, information on the authors' approach to the problem is provided, including the methods and models used, as well as example results. Based on the analysis of the literature and the state of the art, a summary of the analysis is presented at this paper's end. It highlights the small number of works on the subject of interest, and based on the review of stability studies, it seeks to encourage present and potential authors to study this field and share their results with society. [ABSTRACT FROM AUTHOR]

To effectively implement condition-based maintenance for the air compressor in a railway vehicle, a thorough understanding of its fault characteristics and the collection of abnormal data is crucial. However, obtaining sufficient abnormal data from actual railway vehicles is challenging due to the rarity of air compressor failures in commercial railway services. This paper presents a detailed mathematical model of a two-stage piston air compressor that takes into account heat transfer effects. The mathematical model and the fault characteristics of the air compressor are analyzed through MATLAB simulation studies. The accuracy of the proposed model and analysis is verified by comparing it to real pressure data collected from a commercial Seoul subway train. The paper also generates abnormal data through simulations for specific fault conditions, including discharge valve leakages, air cooler malfunctions and pressure switch malfunctions. [ABSTRACT FROM AUTHOR]

The effects of structural nonlinearity (including rubber material and contact boundary nonlinearities) and variable wheel/rail contact point on the dynamic characteristics of resilient wheels are studied to investigate the mechanical properties of these wheels. Primarily, static and dynamic tests are designed to determine the nonlinear constitutive relationship of rubber materials in resilient wheels, and the viscoelastic properties of rubber are discussed. On this basis, the mapping relationship between the elastic modulus and stiffness of rubber in a resilient wheel system is deduced, and the stiffness characteristics of viscoelastic rubber materials are determined. The dynamic models of four types of wheels namely, a solid wheel (SW), a resilient wheel that considers linear rubber (RWL), a resilient wheel that considers nonlinear rubber (RWNL), and a resilient wheel that considers nonlinear rubber and contact boundary (RWNC), are established on the basis of the Yeoh constitutive model for hyper-elastic materials. The changes in wheel/rail contact point and wheel/rail force during train running are obtained under long/short wave irregularity excitation by adopting an established vehicle–track coupled dynamic model. Then the nonlinear dynamic behavior of resilient wheels subjected to varying wheel/rail contact point and wheel/rail force is studied. Finally, the influences of rubber material parameters on the dynamic characteristics of resilient wheels are explored. Results show that the acceleration of a resilient wheel is effectively reduced compared with that of SW. Resilient wheel acceleration that considers variable wheel/rail contact point is larger than that without considering the change in wheel/rail contact point. The deformation rates of rubber subjected to variable and constant wheel/rail contact behavior are 7 and 10%, respectively, and the midpoint deformation of rubber is less than its endpoint deformation. Compared with that of SW, the acceleration of RWL is reduced by 10 and 17% respectively under variable and constant wheel/rail contact points, respectively. Meanwhile, the acceleration of RWNL is reduced by 9 and 7% compared with that of RWL. The influences of nonlinear material characteristics and contact boundary on the dynamic characteristics of resilient wheels are not evident. The major vibration frequencies of the four types of wheels are 3–5, 10, and 22 Hz. The vibration and deformation of resilient wheels increase with an increase in the hardness of rubber. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Applied Mechanics is the property of Chinese Journal of Applied Mechanics Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A comprehensive modeling strategy for studying the thermomechanical tribological behaviors is proposed in this work. The wear degradation considering the influence of temperature (T) is predicted by Archard wear model with the help of the UMESHMOTION subroutine and arbitrary Lagrangian–Eulerian (ALE) remeshing technique. Adopting the proposed method, the thermomechanical tribological behaviors of railway vehicle disc brake system composed of forged steel brake disc and Cu-based powder metallurgy (PM) friction block are studied systematically. The effectiveness of the proposed methodology is validated by experimental test on a self-designed scaled brake test bench from the perspectives of interface temperature, wear degradation, friction noise and vibration, and contact status evolution. This work can provide an effective way for the investigation of thermomechanical tribological behaviors in the engineering field. [ABSTRACT FROM AUTHOR]

This paper describes a practical method for estimating the contact condition between wheel and rail using an instrumented wheelset in a railway vehicle. In a previous study, it was confirmed that an observer based on Kalman filter can estimate wheelset motion variables from measurement data of the instrumented wheelset using a single-wheel creep-force model. However, in the previous method, there is still a problem in that a precise value of friction coefficient between wheel and rail is required as a model parameter to estimate the wheelset motion variables with high accuracy. The accuracy of the value of friction coefficient affects the accuracy of estimation values since a single-wheel creep-force model refers to the creep force and the creepage. Moreover, the decision of the creep force heavily depends on the friction coefficient. To solve the problem, this study proposes a method to estimate the wheelset motion variables and the friction coefficient simultaneously by modifying the plant model. The estimation performance of the proposed method is verified by vehicle dynamics simulations and running test data. The verification results show that the proposed method is effective in estimating the friction coefficient when the track curve radius is smaller than or equal to 600m. In addition, the proposed method can improve the estimation accuracy of the wheelset motion variables compared to the previous method.

This paper proposes a control strategy for active lateral secondary suspension that uses preview data. Based on a derived analytical model, a model predictive controller (MPC) is implemented. The influence of the track irregularities upon carbody lateral dynamics is considered explicitly. The controller developed is applied to a full-scale rail vehicle model. Ride comfort is evaluated according to EN 12299. Multibody simulations show that there is a significant increase in continuous ride comfort on poor-quality tracks.

Although research has shown that through the additional rigidity introduced in the secondary suspension, traction rods can affect the vertical dynamic performance of railway vehicles, this topic has been less studied by researchers in the field. In this paper, the effect of a traction rod on the vertical vibration behavior of a carbody of a railway vehicle is analyzed, using the results obtained through numerical simulations. Numerical simulation applications are developed based on a vehicle model, where the vehicle carbody is modeled using a free-free equivalent beam Euler–Bernoulli, and the bogie chassis and wheelsets are represented by rigid bodies linked together by Kelvin-Voigt systems that model the secondary suspension and the primary suspension. The novelty element of this paper is found in the model of the traction rod. This includes traction rod damping, which has been neglected in previous research. The stiffness and damping of the traction rod are represented by a longitudinal Kelvin–Voigt system integrated into a secondary suspension model. The effect of the traction rod on the vertical vibration behavior of the vehicle carbody is analyzed based on the power spectral density of the acceleration, the root mean square of acceleration, and the ride comfort index, for three cases for analysis: a ‘without traction rod’ case, a ‘with traction rod—with damping’ case, and a ‘with traction rod—without damping’ case. The conclusions of the paper highlight the influence of the stiffness and damping of the traction rod on the vibration level of the carbody, especially in its middle. Depending on the stiffness of the traction rod, significant increases in the ride comfort index are obtained, which at high velocities can exceed 300%. Damping of the traction rod reduces the ride comfort index by up to 10%.

The air spring for railway vehicles uses the air pressure inside the bellows to absorb vibration and shock to improve ride comfort and adjust the height of the underframe with a leveling valve to control stable driving of the train. This study developed augmented reality content that proposes a novel visual technology to effectively support the training of air spring maintenance tasks. In this study, a special effect algorithm that displays the dispersion and diffusion of fluid, and an algorithm that allows objects to be rotated at various angles, were proposed to increase the visual learning effect of fluid flow for maintenance. The FDG algorithm can increase the training effect by visualizing the leakage of air at a specific location when the air spring is damaged. In addition, the OAR algorithm allows an axisymmetric model, which is difficult to rotate by gestures, to be rotated at various angles, using a touch cube. Using these algorithms, maintenance personnel can effectively learn complex maintenance tasks. The UMUX and CSUQ surveys were conducted with 40 railway maintenance workers to evaluate the effectiveness of the developed educational content. The results showed that the UMUX, across 4 items, averaged as score of 81.56. Likewise, the CSUQ survey score, consisting of 19 questions in 4 categories, was very high, at 80.83. These results show that this AR content is usable for air spring maintenance and field training support.

Copyright of Rolling Stock (1002-7602) is the property of Rolling Stock Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Although research has shown that through the additional rigidity introduced in the secondary suspension, traction rods can affect the vertical dynamic performance of railway vehicles, this topic has been less studied by researchers in the field. In this paper, the effect of a traction rod on the vertical vibration behavior of a carbody of a railway vehicle is analyzed, using the results obtained through numerical simulations. Numerical simulation applications are developed based on a vehicle model, where the vehicle carbody is modeled using a free-free equivalent beam Euler–Bernoulli, and the bogie chassis and wheelsets are represented by rigid bodies linked together by Kelvin-Voigt systems that model the secondary suspension and the primary suspension. The novelty element of this paper is found in the model of the traction rod. This includes traction rod damping, which has been neglected in previous research. The stiffness and damping of the traction rod are represented by a longitudinal Kelvin–Voigt system integrated into a secondary suspension model. The effect of the traction rod on the vertical vibration behavior of the vehicle carbody is analyzed based on the power spectral density of the acceleration, the root mean square of acceleration, and the ride comfort index, for three cases for analysis: a 'without traction rod' case, a 'with traction rod—with damping' case, and a 'with traction rod—without damping' case. The conclusions of the paper highlight the influence of the stiffness and damping of the traction rod on the vibration level of the carbody, especially in its middle. Depending on the stiffness of the traction rod, significant increases in the ride comfort index are obtained, which at high velocities can exceed 300%. Damping of the traction rod reduces the ride comfort index by up to 10%. [ABSTRACT FROM AUTHOR]

This paper proposes a control strategy for active lateral secondary suspension that uses preview data. Based on a derived analytical model, a model predictive controller (MPC) is implemented. The influence of the track irregularities upon carbody lateral dynamics is considered explicitly. The controller developed is applied to a full-scale rail vehicle model. Ride comfort is evaluated according to EN 12299. Multibody simulations show that there is a significant increase in continuous ride comfort on poor-quality tracks. [ABSTRACT FROM AUTHOR]

This paper presents a study on the dynamic model and robust controller design for enhancing ride comfort in railway vehicles. An analytical model is introduced, encompassing the lateral, roll, and yaw motions of wheelsets, bogies, and the car body, while incorporating an efficient method for computing wheel-rail interactions. Rail irregularities and their impact on vibration excitation are also examined. A robust controller design methodology is proposed to address uncertainty and ride comfort quality, considering the significant variations in mass and moment of inertia experienced by railway vehicles. Through simulations, the designed controller consistently demonstrates an approximate 2 dB improvement in ride comfort across different levels of uncertainty. Future research directions include developing controller designs considering actuator response characteristics and identifying additional conditions for practical implementation. This study contributes to understanding railway vehicle dynamics and lays the foundation for effective control strategies to enhance ride comfort while accommodating uncertain operating conditions. [ABSTRACT FROM AUTHOR]

Comfort on railway vehicles has been proven to depend on the number of passengers on the car, on their seating arrangement, as well as on the position in which it is assessed. The number of possible seating arrangement combinations is so large that comfort at a given location becomes a random variable even if passengers are considered deterministic vibration absorbers. In this paper we determine probability density functions (PDF) of comfort using a Monte Carlo scheme in which the number of passengers, their seating locations and their vibration characteristics (derived from passenger mass) are all random parameters with their own PDFs. Two types of distributions are obtained: the expected comfort of a single passenger and the compound comfort of all passengers on a given railway car. The carbody is represented by a beam model in which the first bending mode frequency has been allowed to vary so that the scope of results widens slightly. This variation is within the range of human sensitivity because this is the case in current lightweight construction, making carbody flexibility a key contributor to passenger comfort (or discomfort). Results confirm that comfort is indeed a stochastic variable with sizeable variance, and this prompts questions about the relation between the stochastic distribution and the tests prescribed in standard EN–12299. It will be shown that, surprisingly, comfort PDFs may be inferred with a high degree of accuracy (errors lower than 2%) from the tests in standard EN–12299. This is a most fortunate finding that radically transforms the interpretation of said standard, and allows rolling stock manufacturers and rail transport operators to have a much richer assessment of comfort on their vehicles from the same tests they now conduct, without having to perform Monte Carlo tests or simulations. [ABSTRACT FROM AUTHOR]

This paper presents an adaptive optimal control strategy focused on improving ride comfort by minimising the frequency-weighted acceleration measured at three locations on a flexible carbody floor. Front and rear suspensions adapt the restriction orifice, which connects each pneumatic spring to its auxiliary air reservoir, thus conferring different dynamic stiffness and damping depending on train speed and track quality. In this work, as opposed to previous publications by our group, the optimal control problem aims at the particular frequency range which affects passenger comfort in accordance to standard UNE-EN-12299. In addition, a rigorous statistical analysis based on Monte Carlo and Bootstrap sampling techniques has been used to deal with the stochastic nature of track irregularities. Results prove that focusing on the comfort frequency range improves the performance of the adaptive suspension, and that the proposed statistical analysis of optimisation results guarantees the appropriate selection of optimal diameters. [ABSTRACT FROM AUTHOR]

The dynamic behaviour and dynamic phenomena in traction drives of railway vehicle has been studied for decades. Generally, in these days the motivation for this research is to look for answers related with service problems, which has been risen, e.g. an overloading of mechanical components as wheelsets or an intention to improve control systems of traction drives of railway vehicles. This problematic has also motivated the research at the Faculty of Mechanical Engineering at the Czech Technical University (CTU) in Prague. Nowadays it is also usual, that the main research tool has been a simulation based on a mathematical model of a railway vehicle or its specific components, as testing on real vehicles is very demanding regarding costs. However, there is an alternative - a roller rig. At the CTU in Prague there has been modernized the second roller rig for purposes of measurement regarding the torsion dynamics research, to support PhD students for their theses and possibly to extend the education for students oriented on the railway vehicle's design. This contribution brings results of measurements just from the problematics of torsion oscillations and dynamics. Specifically, further presented measurements are on the loss of the adhesion in the contact of the wheelset and rollers, as the substitution for the railway, its impact on the reaction rod overloading and study of the axle load influence on the transition phenomena. [ABSTRACT FROM AUTHOR]

The fatigue life of coil springs is usually predicted with a stationary Gaussian vibration load and deterministic structural parameters. However, the obtained fatigue life is inconsistent with the observed fatigue life of fractured springs which varies within a wide range. The work aims to propose a method to predict the fatigue life of the coil spring by considering the time-varying vibration load, i.e., root mean square (rms) varies with time and the uncertainties of geometric parameters. First, a synthetic method for time-varying vibration loads is proposed. The time-varying load is decomposed into multiple stationary Gaussian short samples represented by their power spectral density (PSD). These PSDs are synthesized according to the distribution characteristics of spectral values, in which data that are non-Gaussian are processed with the Johnson system. Second, the influence of parameter uncertainties in the coil spring is studied by a Monte Carlo analysis of the stress frequency response function. Finally, the fatigue life is calculated and compared with the results predicted by using the measured stress. The results show that the synthetic spectrum has almost the same damage potential as the measured time-varying load. In comparison with results predicted from the measured stress, the synthetic spectrum gives much better estimates of the fatigue life of the coil spring than the average spectrum. Parameter uncertainties of coil springs significantly affect fatigue life and should be taken into account. [ABSTRACT FROM AUTHOR]

The interior noise characteristics of railway vehicles vary depending on the position of the cabin. In general, interior noises are louder in the area directly above bogies (ends of the cabin) than in the center of the cabin. It has been known that structure-borne sounds from bogies contribute greatly to the interior noises directly above bogies. This paper describes, using measured data obtained with the rolling stock test plant at Railway Technical Research Institute (RTRI), the application of the operational transfer path analysis (OTPA) to determine the contribution ratio of each transmission path of vibration from bogies to cabin floors. It is considered that structure-borne sounds from bogies propagate mainly through the parts connecting the bogie and car body such as single-link-type traction devices (traction links), yaw dampers, and air springs. As a result of applying the OTPA and determining the contribution ratios, it has been confirmed that the contribution ratios varied depending on the position of the floor and the frequency band. In addition, the validity of the contribution has been verified by examining the linearity of input/output data and the correlations of input data using multiple coherence functions and partial coherence functions. Although a bogie vibrates rigidly in the low frequency range with the very high correlation between the vibrations of the bogie and the parts connecting the bogie and car body, the correlation becomes low in the high frequency region. Therefore, it is expected that the contribution of each transfer path can be well estimated by applying the OTPA in the high frequency range for structure-borne sounds from bogies.

The evaluation of the vibration behavior of railway vehicle car bodies based on the results of numerical simulations requires the adoption of an appropriate theoretical model of the suspension which considers the important factors that influence the vibration level of the car body. In this paper, the influence of the secondary suspension model on the vertical vibration behavior of the railway vehicle car body is investigated, based on the results of numerical simulations on the frequency response functions of the acceleration, the power spectral density of the acceleration and the root mean square of the acceleration of the car body. Numerical simulation applications are developed based on a rigid-flexible coupled vehicle model with seven degrees of freedom, corresponding to car body vibration modes: bounce, pitch, and first vertical bending mode, and bogie vibration modes: bounce and pitch. Four different models of secondary suspension are integrated into the vehicle model, namely a reference model and four analysis models. Analysis models include systems through which the pitch vibration of the bogies is transmitted to the car body, influencing its vibration behavior and, respectively, a system that takes the relative angular displacement between the car body and the bogie and a system that models the transmission system of the longitudinal forces between the bogie and the car body are analyzed. The effects of these two systems on the vibration behavior of the railway vehicle car body are analyzed both for each system separately and together. In the conclusions of the paper, the influence of the secondary suspension model on the vibration level at the resonance frequencies of the vertical bending of the car body and the pitch of the bogie is pointed out. It also highlights the important contribution of the transmission system of the longitudinal forces between the bogie and the car body in transmitting pitch vibrations of the bogies to the car body, with effects on the vibration level of the car body at high speeds.

Track irregularities directly affect the quality and safety of railway vehicle operations. Quantitative detection and real-time monitoring of track irregularities are of great importance. However, due to the frequent variable vehicle speed, vehicle operation is a typical non-stationary process. The traditional signal analysis methods are unsuitable for non-stationary processes, making the quantitative detection of the wavelength and amplitude of track irregularities difficult. To solve the above problems, this paper proposes a quantitative detection method of track irregularities under non-stationary conditions with variable vehicle speed by order tracking analysis for the first time. Firstly, a simplified wheel–rail dynamic model is established to derive the quantitative relationship between the axle-box vertical vibration and the track vertical irregularities. Secondly, the Simpson double integration method is proposed to calculate the axle-box vertical displacement based on the axle-box vertical acceleration, and the process error is optimized. Thirdly, based on the order tracking analysis theory, the angular domain resampling is performed on the axle-box vertical displacement time-domain signal in combination with the wheel rotation speed signals, and the quantitative detection of the track irregularities is achieved. Finally, the proposed method is validated based on simulation and field test analysis cases. We provide theoretical support and method reference for the quantitative detection method of track irregularities.

Abstract A comprehensive modeling strategy for studying the thermomechanical tribological behaviors is proposed in this work. The wear degradation considering the influence of temperature (T) is predicted by Archard wear model with the help of the UMESHMOTION subroutine and arbitrary Lagrangian–Eulerian (ALE) remeshing technique. Adopting the proposed method, the thermomechanical tribological behaviors of railway vehicle disc brake system composed of forged steel brake disc and Cu-based powder metallurgy (PM) friction block are studied systematically. The effectiveness of the proposed methodology is validated by experimental test on a self-designed scaled brake test bench from the perspectives of interface temperature, wear degradation, friction noise and vibration, and contact status evolution. This work can provide an effective way for the investigation of thermomechanical tribological behaviors in the engineering field.

The dynamic behaviour and dynamic phenomena in traction drives of railway vehicle has been studied for decades. Generally, in these days the motivation for this research is to look for answers related with service problems, which has been risen, e.g. an overloading of mechanical components as wheelsets or an intention to improve control systems of traction drives of railway vehicles. This problematic has also motivated the research at the Faculty of Mechanical Engineering at the Czech Technical University (CTU) in Prague. Nowadays it is also usual, that the main research tool has been a simulation based on a mathematical model of a railway vehicle or its specific components, as testing on real vehicles is very demanding regarding costs. However, there is an alternative – a roller rig. At the CTU in Prague there has been modernized the second roller rig for purposes of measurement regarding the torsion dynamics research, to support PhD students for their theses and possibly to extend the education for students oriented on the railway vehicle’s design. This contribution brings results of measurements just from the problematics of torsion oscillations and dynamics. Specifically, further presented measurements are on the loss of the adhesion in the contact of the wheelset and rollers, as the substitution for the railway, its impact on the reaction rod overloading and study of the axle load influence on the transition phenomena.

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Ensuring the safety of the railway vehicles over bridges shaken by earthquakes is a practical issue in the seismic design of railway bridges. To improve the vehicle's running safety on railway bridges during earthquakes, the stopper (or bump-stop) between the bogie and the car-body of the vehicle was modified as a fuse-type element, i.e., it was designed to break under large impact due to earthquake occurrence. The efficacy of the fuse stopper was illustrated by a full-scale vehicle-track shake table test. The fuse stopper element was introduced to the vehicle-bridge interaction model, whose accuracy was also demonstrated by comparison with the test results. The fuse stopper was designed to remain intact under service level earthquakes (SLE) to avoid frequent replacement or repair, while it should fuse to improve vehicle safety on a group of bridges under design basis earthquakes (DBE). The bridge group includes 24 simply-supported bridges with pier heights ranging from 6m to 60m, covering the most simply-supported bridges in the China railway network. A total of 10 ground motion records were used in the analysis to account for the uncertainty of ground motions. Through vehicle-bridge incremental dynamic analysis (IDA) simulation, the optimal fusion strength of 188 kN and the extended gap of 0.04 m were proposed for the fuse stopper at DBE intensity, in which the bridge group can achieve derailment-free. The design procedure of the fuse stopper may provide a cost-effective way to improve the vehicle's running safety on a group of bridges during earthquakes. [ABSTRACT FROM AUTHOR]