Railway Vehicle Model Research Articles

A new hybrid control strategy for improving ride comfort on lateral suspension system of railway vehicle

The ride comfort is a key research area for the quality improvement of railway vehicles. Several control methods have been developed to improve the ride comfort, in which the semi-active control approach inherits the advantages of passive and active control approaches. However, the semi-active control may perform ineffectively in vibration attenuation when the carbody load changes. To address this issue, we proposed a novel hybrid control method that combines the skyhook (SH) and displacement velocity (DV) control methods to reduce vibrations of the carbody in the lateral direction under carbody load changes. First, a hybrid control model built in Matlab software was applied to a quarter railway vehicle model for a preliminary assessment of the ride comfort. Second, to provide a more comprehensive evaluation, the proposed model was applied to a whole railway vehicle model using co-simulation (Matlab-Simpack). In the quarter model, under the sinusoidal excitation, the hybrid control showed a lower acceleration by 48.5% and 42.8% when the carbody load reduced to a half and a quarter, respectively, compared to the passive control. This finding was confirmed with the whole model. Moreover, in the whole model, under the track irregular excitation, the hybrid control showed a lower acceleration by 26.6% and 17.4% when the carbody load reduced to a half and a quarter, respectively. Further, the proposed method showed an acceptable safety level, measured by the derailment coefficient (0.0743 at a half load and 0.089 at a quarter load). In conclusions, the proposed hybrid SH-DV control exhibits high robustness, adaptability, effectiveness, and acceptable safety level in response to variations in body load.

Simplified prediction models for acoustic installation effects of train-mounted equipment

Acoustic models of railway vehicles in standstill and pass-by conditions can be used as part of a virtual certification process for new trains. For each piece of auxiliary equipment, the sound power measured on a test bench is combined with measured or predicted transfer functions. It is important, however, to allow for installation effects due to shielding by fairings or the train body. In the current work, fast-running analytical models are developed to determine these installation effects. The model for roof-mounted sources takes account of diffraction at the corner of the train body or fairing, using a barrier model. For equipment mounted under the train, the acoustic propagation from the sides of the source is based on free-field Green’s functions. The bottom surfaces are assumed to radiate initially into a cavity under the train, which is modelled with a simple diffuse field approach. The sound emitted from the gaps at the side of the cavity is then assumed to propagate to the receivers according to free-field Green’s functions. Results show good agreement with a 2.5D boundary element model and with measurements. Modelling uncertainty and parametric uncertainty are evaluated. The largest variability occurs due to the height and impedance of the ground, especially for a low receiver. This leads to standard deviations of up to 4 dB at low frequencies. For the roof-mounted sources, uncertainty over the location of the corner used in the equivalent barrier model can also lead to large standard deviations.

Integration of brake block thermal equations within a railway vehicle multibody model: a multiphysics approach

ABSTRACT The paper shows the development of a finite-difference (FD) railway brake block thermal model and its integration within the multibody (MB) formalism of the Simpack commercial code. The block nodal temperatures are included among the dynamic states computed by the MB solver, through the definition of a user-defined force element, which determines the braking torque based on the applied brake cylinder pressure. The proposed approach overcomes the main limitations of existing detailed railway vehicle models, which solve the thermal and vehicle dynamics equations in different computational environments. Furthermore, the new strategy can thrust the development of models able to account for the coupling between the wheel and block thermal behaviour and the whole vehicle dynamics. Preliminary simulations of drag and stop braking operations of a reference European freight waggon prove that the proposed model is able to effectively consider the main heat fluxes and nonlinearities involved in tread braking operations.

Parameters optimum of multiple underframe suspended equipment on high-speed railway vehicle carbody vibration control by using an improved genetic algorithm

Carbody vibration control and ride comfort improvement are important research parts of high-speed railway vehicle dynamic. The effectiveness of utilizing carbody underframe suspended equipment as dynamic vibration absorbers for carbody vibration suppression has been validated. While previous research has focused mainly on a single suspended equipment without considering its vibration tolerance, a balance must be struck between reducing carbody vibration and maintaining equipment performance. To address the challenging, a multi-objective and multi-parameter optimization method is employed, integrating an improved niche genetic algorithm (INGA) into the numerical simulation process. Considering carbody flexible and multi-suspended equipment, a rigid-flexible dynamics model of a high-speed railway vehicle is established and validated on a vehicle dynamics test rig. Based on the numerical analysis, the optimal parameter combination of the stiffness and the longitudinal installation position is obtained from an evaluation function that comprehensively assesses the vibration performance of both the vehicle carbody and the equipment. Comparative analysis between the results obtained from the optimal and primitive parameters demonstrates that the optimization process not only achieves significant improvements in carbody vibration reduction but also effectively controls equipment vibration within reasonable limits. The multi-objective and multi-parameter optimization method applied on carbody underframe suspended system proves to be valuable in improving the dynamic performance of high-speed railway vehicles.

A novel metaheuristic algorithm based FOPID approach for decentralized control of vibration of a railway vehicle

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.

Measuring vertical track irregularities from instrumented heavy haul railway vehicle data using machine learning

This paper proposes a data-driven approach to estimating geometric track irregularities from instrumented railway vehicle (IRV) data. Machine learning is used to find the nonlinear mapping between IRV data and track irregularities. A dynamic model of the BRA1 railway vehicle was used to generate an artificial dataset that contains variables that are measured by the real BRA1 IRV and other variables measured by IRVs found in the literature. An extensive data analysis step was done to verify if the current instrumentation of the BRA1 IRV is sufficient for obtaining both lateral and vertical track irregularities. Feature engineering based on wagon movements, signal integration and time domain statistical metrics were applied to extract features and then the best features were selected using a wrapper method. Eight different regression ML models were trained and optimized after the feature selection using Optuna. The results show that, with the current instrumentation of the BRA1 IRV, obtaining lateral track irregularities is unlikely due to low correlation, however, vertical irregularities can be obtained with a root mean squared error (RMSE) of 0.556 mm. With postprocessing, the RMSE was further reduced to 0.410 mm.

On-Board Random Vibration-Based Robust Detection of Railway Hollow Worn Wheels under Varying Traveling Speeds

The problem of the prompt detection of early-stage hollow worn wheels in railway vehicles via on-board random vibration measurements under normal operation and varying speeds is investigated. This is achieved based on two unsupervised statistical time series (STS) methods which are founded on a multiple-model (MM) framework for the representation of healthy vehicle dynamics. The unsupervised MM power spectral density (U-MM-PSD) method employs Welch-based PSD estimates for wheel wear detection and the unsupervised MM autoregressive (U-MM-AR) method for the parameter vectors of multiple AR models. Both methods are assessed via two case studies using thousands of test cases. The first case study includes Monte Carlo simulations using a SIMPACK-based detailed railway vehicle model, while the second is based on field tests with an Athens Metro train. Wheel wear detection is pursued using lateral or vertical vibration signals from the bogie or the carbody of a trailed vehicle traveling with three different speeds (60, 70, 80 km/h) using wheels under healthy conditions or with early stage hollow wear. Both methods exhibit remarkable performance with the U-MM-AR method to achieve the best overall results, reaching correct detection rates of even 100% with false alarm rates below 5% based on a single accelerometer either on the carbody or bogie.

Vibrations control of railway vehicles using decentralized proportional integral derivative controller with flow direction optimization algorithm

The reduction of vibration-induced discomfort in vehicles is an important goal in the field of transportation engineering. Several mathematical models with various controlling techniques, from classical to modern, have been employed to achieve better ride comfort. Still, no comprehensive solution has yet been found. Therefore, this paper proposes a 17-degree-of-freedom (minimum number of coordinates) dynamic model of a full-scale railway vehicle integrated with wheel-rail contact forces and an active suspension system. Two controllers, termed system and force tracking controllers, suppress the vehicle body's vibrations. Based on a multi-loop control structure, three optimally tuned Proportional Integral Derivative controllers evaluate the desired control forces and performs the system controller’s action. While the force-tracking controller generates the command voltage to track that forces. The parameters of controllers are tuned with a novel metaheuristic optimization algorithm known as the flow direction algorithm (FDA), and the results are compared with two other optimization techniques, i.e., particle swarm optimization and ant colony optimization. The simulated results show that the ride comfort of the vehicle is improved with FDA, as the root mean square values of the lateral, roll, and yaw accelerations are reduced by 42.01%, 33.12%, and 48.24%, respectively. Moreover, the simulated results of the proposed model are validated with the experimental results of accelerations. The simulated results show that the proposed system tuned with the metaheuristic algorithm outperforms with a significant reduction in vehicle vibrations.

Effects of Crosswind on Pantograph–Catenary Wear Using Nonlinear Multibody System Dynamic Algorithms

In this study, a multibody system (MBS) computational framework is developed to determine the exact location of the contact point and wear prediction resulting from the pantograph–catenary interaction. The railroad vehicle models in the MBS computational framework comprise rigid-body railroad vehicles, rigid-body pantograph systems, and flexible catenary systems. To avoid incremental rotation, the nonlinear finite element absolute nodal coordinate formulation is used to model a flexible catenary system in the MBS computational framework. To avoid co-simulation processes, the rigid-body railroad vehicle and the pantograph and flexible catenary systems were integrated into the MBS algorithms. The pantograph–catenary interaction is modeled using an elastic contact formulation developed to include the effect of pantograph–catenary separation and sliding contact. The proposed MBS approach evaluates the location of the contact point, contact force, and normal wear rate (NWR) from the mechanical and electrical contributions. This investigation considers the vibration caused by a crosswind scenario and determines the numerical result in the case of a steady crosswind scenario. The steady crosswind scenario contains the advantage of pantograph–catenary aerodynamic design, and the vibration of the catenary system remains significant after the excitation of a steady crosswind. In the case of a steady crosswind, the higher value of the steady crosswind effect significantly increases the mean contact force and the NWR from the mechanical contribution. After crosswind load disturbances, the mean contact force decreases, but the standard deviation of the contact force increases. Therefore, the NWR from the electrical contribution increases significantly. However, the total NWR increases with the crosswind velocity.

Dynamic modeling and ride comfort evaluation of railway vehicle under random track irregularities: A case study of a Linke-Hofmann-Busch coach

The ride comfort of passengers is an important parameter for evaluating the performance of railway vehicles. Many standards/ models, such as quarter car, half car, and full car, have been proposed to evaluate the human comfort of railway vehicles. However, a full-scale coupled railway vehicle model is rarely considered for calculating ride comfort. Therefore, this paper proposes a twenty-seven-degree-of-freedom (27-DOF) coupled dynamic model of railway vehicles integrated with wheel-rail contact forces. The developed model is solved using the two-dimensional (2-D) state space method, and the effects of different track irregularities on human comfort are evaluated. The outputs are described in terms of three-dimensional (3-D) Power Spectral Densities (PSDs) under three types of random track irregularities: vertical profile, lateral alignment, and cross-level. Furthermore, Sperling's method is used to evaluate the human comfort index. For the case study, a Linke-Hofmann-Busch coach (LHB) based model has been employed, and the results are validated with the experimental data of ride comfort reported by the Research Design and Standard Organization (RDSO). The simulated results of the proposed model demonstrate a remarkable alignment with the experimental data, exhibiting a small error ranging from 2.36 % to 8.81 % for vertical motion and 5.84 % to 8.30 % for lateral motion, respectively. Such promising results offer valuable insight for the design of future coaches, ensuring enhanced ride comfort even at high speeds.

Dynamic Characteristics and Fault Mechanism of the Gear Tooth Spalling in Railway Vehicles under Traction Conditions

Gear tooth spalling is one of the inevitable fault modes in the long-term service of the traction transmission system of railway vehicles, which can worsen the dynamic load of the rotating mechanical system and reduce the operating quality. Therefore, it is necessary to study its fault mechanism to guide fault diagnosis scientifically. This paper established a planar railway vehicle model with a traction transmission system and an analytical time-varying meshing stiffness (TVMS) model of the spalling spur gear. Then, it analyzed the dynamic characteristics under traction conditions. The research found that the spalling length and depth affect the amplitude of the TVMS at the defect, while the width affects the range of the TVMS loss. The crest factor is the best evaluation indicator in ideal low-noise environments due to its sensitivity and linearity, but it is not good in strong-noise environments. Similarly, a time–frequency analysis tool cannot significantly detect the sideband characteristics that are excited by spalling. After high-pass filtering, the root mean square and variance exhibit excellent classification and vehicle speed independence in strong-noise environments. This research achievement can provide adequate theoretical support for feature selection and making strategies for fault diagnosis of railway vehicle gear systems.

A degraded adhesion model for creep force calculation based on the CONTACT algorithm

Degraded adhesion is observed extensively during the braking or traction process. An accurate degraded adhesion law, on the other hand, is difficult to acquire since it is characterized by a complicated non-linear behaviour involving various surface phenomena. This work provides a new local degraded adhesion model, its implementation in a wheel-rail contact model, and its application in a multibody railway vehicle model. The present degraded adhesion model takes into account large sliding and adhesion recovery phenomena, which are strictly related to the power dissipated at the contact interface. Implementation of the current local degraded adhesion model enhances Kalker’s CONTACT algorithm. The application into multibody dynamics simulation demonstrates the high accuracy of computations. The model is validated by comparing it to experimental findings obtained from on-field tests. Simulated results regarding the tangential pressures, the slip velocity, and the dissipated power under degraded adhesion and partial adherence conditions are reported.

Fabrication and Vibration Analysis of Railway Vehicle Model with Box Structure

Fabrication and Vibration Analysis of Railway Vehicle Model with Box Structure

The Experimental Loop of Railway Research Institute celebrates its 90th Anniversary

In 2022, the main testing centre of Russian railways, the Experimental Loop of the Railway Research Institute, turns 90 years old.The experience accumulated by the Experimental Loop is unique at a global scale: at the time of its creation, it was the world's first designated testing area for the latest models of railway vehicles and materials.The contribution of the Experimental Loop to the development of Soviet and Russian railways cannot be overestimated. A specially built proving ground and highly professional staff equipped with all the necessary tools made it possible to radically accelerate the development of new railway technologies and their implementation in the transportation process. The reputation and importance of the Experimental Loop is confirmed by the constant attention and visits of top state officials and industry leaders.The presented historical essay shows the main stages in the development of the Experimental Loop, as well as its significance both for the transport industry of our country and for Russian railway science.

Calibration of the numerical model of a freight railway vehicle based on experimental modal parameters

The simulation of the dynamic behavior of the train-track system is strongly dependent on the accuracy of the numerical models of the train and track subsystems. The use of calibrated numerical models of the railway vehicles, based on experimental data, enhances their ability to correctly reproduce the dynamic responses of the train under operational conditions. In this scope, studies involving the experimental calibration of freight wagon models are still scarce. This article aims to fill this gap by presenting an efficient methodology for the calibration of a numerical model of a freight railway wagon based on experimental modal parameters. A dynamic test was performed during the unloading operation of the train, adopting a dedicated approach which does not interfere with its tight operational schedule. From data collected during the dynamic test, five natural frequencies and mode shapes associated with rigid-body and flexural movements of the wagon platform were identified through the Enhanced Frequency-Domain Decomposition (EFDD) method. A detailed 3D finite-element (FE) model of the loaded freight wagon was developed, requiring precise knowledge of the vehicle design details which, in most situations, are difficult to obtain due to confidentiality reasons of the manufacturers. The model calibration was performed through an iterative method based on a genetic algorithm and allowed to obtain optimal values for seven numerical parameters related to the suspension’s stiffnesses and mass distribution. The stability of the parameters considering different initial populations demonstrated the robustness of the optimization algorithm. The average error of the natural frequencies decreased from 8.5% before calibration to 3.2% after calibration, and the average MAC values improved from 0.911 to 0.950, revealing a significant improvement of the initial numerical model.

Comparison of numerical and computational aspects between two constraint-based contact methods in the description of wheel/rail contacts

The numerical and computation aspects of the Knife-edge Equivalent Contact (KEC) constraint and lookup table (LUT) methods are compared in this paper. The LUT method implementation uses a penetration-based elastic contact model for the flange and a constraint-based formulation at the wheel tread. For the KEC method, where an infinitely narrow rail contacts an equivalent wheel, regularization of the tread-flange transition is adopted to simultaneously account for tread and flange contacts using constraints. A comparison between the two methods is carried out using well-known numerical integrators to show the applicability and limitations of both methods.Two fixed-step-size integrators, the explicit Runge–Kutta (RK4) and the predictor–corrector Adam–Bashforth–Moulton (ABM) methods, and two variable-step-size Matlab built-in function integrators, the explicit ode45 and implicit ode15s, were applied to get the numerical solutions to the dynamic problems and study the relative numerical performance of the two contact description methods. To complete the railway vehicle model, both contact methods were implemented for the multibody model of a benchmark railway vehicle (the Manchester wagon 1). Numerical results were obtained for different railway tracks with and without irregularities. Profiles of the S1002 wheel and LB-140-Area rail, which demonstrate the two-point contact phenomenon, were considered. Both methods were implemented in Matlab and validated against commercial simulation software. The kinematic results for both approaches show good agreement, but the KEC method was up to 20% more efficient than the LUT method regardless of integrator used.

Influence of wheel flat on railway vehicle helical gear system under Traction/Braking conditions

The gear system is an essential component of railway vehicles. However, wheel flat often affects the gear system's fault diagnosis and fatigue life and further jeopardizes vehicle operation safety. This paper develops a railway vehicle model equipped with a helical gear system. The model validation uses the experimental data under various operating conditions. The discussion of the simulation results involves the time-domain and time–frequency domain responses of the gear system of a vehicle with the wheel flat under variable speed conditions. Simultaneously, the analysis of its regularity uses the peak-to-peak value as characteristic vibration indicators. The results show that the wheel-rail contact status has two regions: the continuous contact region and the intermittent contact region. The vibration of the gear system is relatively stable in the continuous contact region. However, it fluctuates sharply in the intermittent contact region. In the time–frequency domain results, the fundamental frequency of the wheel flat and its multiplier gradually replaces the healthy gear meshing frequency and its multiplier as the primary contributor to energy. Furthermore, the peak-to-peak value shows that the gear system vibrates significantly under critical conditions. The above results can help improve the gear system's stability and thus the running stability and safety of railway vehicles.

Development of Bogie-Mounted Dynamic Vibration Absorbers for Reducing Elastic Vibration of Railway Vehicle Carbodies

This paper describes the improvement of passenger comfort in railway trains. Elastic vibrations of railway vehicle carbodies, which occur in a frequency range that is easily perceived by humans, affect comfort of passengers. Therefore, methods to reduce elastic vibration are required. In this study, we focused on bogie vibration to develop a Bogie-Mounted Dynamic Vibration Absorbers (BMDVA) to reduce them. First, after specification study, design, and fabrication of the BMDVA, vibration test of the BMDVA alone was conducted. Second, an analytical model of a railway vehicle was created using Matlab, a numerical analysis software. Third, the vibration characteristics of this model were evaluated to demonstrate its usefulness. Finally, a railway vehicle model with the BMDVA installed was created, and vibration reduction effects were verified through excitation and running simulations. As a result, it was confirmed that the proposed BMDVA was effective in reducing elastic vibration.

Torsional Vibration Reduction of Railway Vehicle Model by Controlling Internal Pressure of Air Springs using H-infinity Methods

As railway vehicles become faster and lighter, the vibration of carbody tends to increase and that makes the ride comfort worse. In lateral and vertical rigid-body vibration, a number of reduction technologies have been put into practical use, such as semi-active suspensions and variable vertical dampers installed between carbody and bogie. In elastic vibration, various methods have been studied, such as control by previously mentioned dampers, stack-type piezoelectric actuators. However, these methods focused on only the bending vibrations, it has been difficult to reduce multiple elastic vibration modes simultaneously. The authors propose a method to simultaneously reduce multiple elastic vibration modes, including torsional vibration, by controlling internal pressure of air springs. Since this method uses existing devices, it is superior in weight, cost, and maintenance compared to installing a new vibration compensator. First of all, we developed railway vehicle analytical model that can express elastic vibration including torsional vibration. Furthermore, we designed a control system by H-infinity methods and verified vibration-reduction effect on the stationary excitation test of simple railway vehicle model. As a result, it was confirmed that multiple elastic vibration modes, including torsional vibration, can be reduced simultaneously.

Building a multibody dynamics simulation model of railway vehicle considering wheel slide re-adhesion control

The contact between wheel and rail of railway has a strong influence on the running safety. But under the wet condition, adhesion coefficient between wheel and rail decease, and skid may occur when railway vehicle is breaking. This is a serious safety risk to the operation of vehicle. Therefore, many research to reveal the adhesion between wheel and rail have been performed. In this paper, we built a multibody dynamics simulation model of railway vehicle considering wheel slide re-adhesion control using Simpack, in order to study on the best way of breaking of railway vehicle under wet condition reflecting the previous research results. In addition, breaking simulation under low adhesion coefficient condition was performed using the simulation model with wheel slide re-adhesion control.