Rail Vehicle Suspension Research Articles

T-S Fuzzy Data-Driven ToMFIR With Application to Incipient Fault Detection and Isolation for High-Speed Rail Vehicle Suspension Systems

T-S Fuzzy Data-Driven ToMFIR With Application to Incipient Fault Detection and Isolation for High-Speed Rail Vehicle Suspension Systems

Theoretical investigation of the rail vehicle suspension system using different optimised controllers by harmony search algorithm incorporating magnetorheological dampers

Theoretical investigation of the rail vehicle suspension system using different optimised controllers by harmony search algorithm incorporating magnetorheological dampers

Data-Driven ToMFIR-Based Incipient Fault Detection and Estimation for High-Speed Rail Vehicle Suspension Systems

Data-Driven ToMFIR-Based Incipient Fault Detection and Estimation for High-Speed Rail Vehicle Suspension Systems

Optimization of suspension of rail vehicles with coil springs using marine predators algorithm

The topic of this paper is the usage of the algorithm of marine predator (MPA) in the optimization of the suspension of rail vehicles with coil springs. The aim is to reduce the mass of set of coil springs as the main parts of rail vehicles suspension. The optimized set of coil springs must satisfy the appropriate conditions related to the suspension characteristics, with the aim of achieving the required operation quality and running security of the observed rail vehicle. Starting from the bi-linear characteristic of rail vehicles suspension and the analytical description of its parameters, an optimization problem is formulated. It is composed of six optimization parameters, an objective function and 16 constraints (eight for each coil spring in the set). The developed approach is applied in two specific examples of suspension optimization of four-axled freight wagons, the first with axle load of 200 kN and the second with axle load of 225 kN. The optimization problem is resolved using MPA. The acquired results showed that the given optimization approach with MPA provide a significant mass decrease compared to conventional design method of rail vehicles suspension with coil springs. The mass decrease of one set of coil springs in both examples is about 15.5%. Given that each considered four-axled freight wagon has 16 sets of coil springs, the decrease of the total coil springs mass per wagon in both examples is more than 60 kg. Since certified rail vehicles are commonly produced in large series, the proposed approach can be very significant for increasing profitability in the rail vehicles industry.

A modified bidirectional long short-term memory neural network for rail vehicle suspension fault detection

Faults of railway suspension units may endanger vehicle operation safety. Therefore, timely fault detection of railway suspension is necessary. The reported fault detection method that uses Bidirectional Long Short-Term Memory (BiLSTM) neural network in a denoising autoencoder fashion suffers from a shortcoming that the condition monitoring data under faulty states needs to be ultilized to determine the added noise level. Such data is not always available in practice. In this paper, we modified the BiLSTM such that the output data point is excluded from the input when predicting this specific output data point. The requirement of using condition monitoring data under faulty states is therefore relaxed, as the modified BiLSTM is free from determining the level of added noise. A case study on railway suspension fault detection was presented. We used the railway vehicle dynamics model to generate car body vibration under healthy, three levels of reduced first suspension stiffness states, and three levels of reduced first suspension damping states. We compared the performance of the modified BiLSTM with the linear autoregression model, LSTM, and BiLSTM-DAE models. The results have shown that the modified BiLSTM-based fault detection method performs the best, having the highest area under the receiver operating curve.

Optimization of AC–DC Converters for Regenerative Train Suspensions

This article focuses on the dynamic optimization of the operating conditions of two types of ac–dc converters, a diode bridge rectifier and a full bridge active rectifier, which are used for interfacing regenerative rail vehicle suspensions based on ac electromagnetic generators. A theoretical analysis shows that, for both types of converters, the optimal operating conditions, leading to the maximization of the extracted power, can be predicted from the measurement of the generator speed. In particular, as regards the diode bridge rectifier, it is shown that the optimal value of the dc side voltage is related to the generator speed. As regards the active full-bridge rectifier, it is shown that a relationship exists between the optimal converter duty cycle and the generator speed. Experimental results validate the proposed theoretical models both in case of ideal constant generator speeds, and in case of more realistic time-variable generator speeds. The proposed analysis enables the design of high-performance speed-driven maximum power point tracking techniques for regenerative vehicle suspensions.

Research progress of fault detection equipment and methods for track train’s shape part

Rail transit has many advantages such as large capacity, fast speed, energy saving and environmental protection, and has gradually become an indispensable means of transportation in people’s lives. At the same time, the safety and reliability of rail transit is also facing severe challenges. The running part plays the role of load bearing, running and traction guidance, etc. It is one of the most important systems of the train, and it is also the accident-prone part. Aiming at the failures of rail vehicle wheelsets, bearings, overall frame and suspension parts, this article uses CNKI, Wanfang Data Knowledge Service Platform, IEEEXplore and ScienceDirect as the search database to investigate and analyze the research results published at home and abroad in recent years. The fault diagnosis technology of the traveling department summarizes the sensor types, installation positions and usage methods used in various diagnosis technologies, and finally puts forward the prospect of the follow-up research. The work of this paper will help researchers to systematically grasp the relevant research trends of the fault detection of the walking part, and then make clearer and deeper thinking.

Evaluation of Stress and Fatigue of a Rail Vehicle Suspension Component

The article discusses the use of pivot bearing friction liners, made of selected materials, in railway freight wagons’ spherical centre bowls. Comparative studies on the effect of suspension dynamics on the equivalent stresses in the liner material were carried out using the finite element method and multibody simulation. The results show the magnitude and location of the highest stresses in the liner with varying input loads, friction coefficients and interacting materials. The analysis is a basis for a simulation method for predicting the fatigue life of the suspension friction liner placed in the centre bowl between the bogie frame and the vehicle body.

Nonlinear Stability of Rail Vehicles Traveling on Vibration-Attenuating Slab Tracks

Abstract Various vibration-attenuating slab tracks have been introduced into urban railways to minimize the negative effects of train-induced ground vibration and noise. However, compared with traditional slab tracks, vibration-attenuating slab tracks usually have a lower overall stiffness, which reduces the vehicle lateral stability. This paper presents an investigation of the nonlinear hunting stability of fast metro rail vehicles traveling on vibration-attenuating slab tracks. A three-dimensional vehicle–track coupled model considering different vibration-attenuating slab tracks is developed to investigate the nonlinear hunting behavior of metro vehicles running on different elastic vibration-attenuating tracks. The nonlinear critical speed and wheelset hunting limit cycle of two types of metro vehicles traveling on four typical types of vibration-attenuating tracks are compared in detail. The influences of vehicle–track system parameters, including rail fastener stiffness and vehicle suspension parameters, on the vehicle lateral nonlinear stability are reported. The results show that the flexibility of vibration-attenuating slab tracks leads to a large wheelset limit cycle and lowers the nonlinear critical speed. Increasing track lateral stiffness and designing appropriate vehicle suspension parameters can improve the lateral stability of rail vehicles traveling on vibration-attenuating slab tracks.

Adaptive Sensor Fault Detection for Rail Vehicle Suspension Systems

This paper develops an adaptive sensor fault detection scheme for rail vehicle suspension systems with uncertain parameters and sensor faults. A parameterized model of the input-to-output description of the rail vehicle suspension systems is developed, based on which different parameterized output estimators are constructed to detect different unknown sensor fault patterns. As a representative study, three fault detection estimators are presented using estimation errors between the sensor output and the output estimates. Robust adaptive parameter update laws are used to ensure desired system performance of the output estimators, for the construction of the fault detection scheme. The proposed adaptive detection scheme not only can handle large parameter uncertainties in rail vehicle suspension system models, but also can check whether sensor fault occurs in rail vehicle suspension system models or not, and identify the patterns of the sensor faults. Simulation study verifies the effectiveness of the developed adaptive sensor fault detection scheme.

Natural Frequency Region – Fluid-Structural-Interaction approach for dynamic impact predictions and experimental verification of rubber–metal bonded systems with fluid

This paper presents an integrated procedure for dynamic impact predictions and an experimental verification of rubber–metal bonded components with fluid to be used as a potential application in rail vehicle suspensions. There are three steps involved in the procedure. First, a quasi-static analysis was performed to verify the elastic properties of the rubber material using hyperelastic models. Second, a dynamic impact evaluation on selected hydro-mounts without fluid was conducted using the Natural Frequency Region (NFR) approach. Finally, a coupled NFR (with Fluid-Structural-Interaction) approach, different from the usual viscoelastic methods, was initiated to predict the dynamic impact responses of these components with the fluid in time domain. All the analyses have been validated with experimental data. The first two stages have been briefly described and the third stage is detailed in this paper. It should be noted that a powerful computer with multi-central processing units is essential to obtain a reasonable result within an acceptable time frame. It took approximately 40 h wall-clock time to complete the analysis using a workstation with 10 central processing units. It has been suggested that the natural frequency region–fluid–structure interaction methodology is reliable and could be used at the design stage and for engineering applications.

The benefits of mechatronically-guided railway vehicles: A multi-body physics simulation study

Mechatronically-guided railway vehicles are of paramount importance in addressing the increasing interest in reducing wheel-rail wear and improving guidance and steering. Conventional passively-guided rail vehicles are limited by the mechanical constraints of the suspension elements. Currently, a typical rail vehicle suspension needs to be sufficiently stiff to stabilize the wheelsets while being complaint enough to negotiate curved track profiles. The suspension is therefore a compromise for the contradictory requirements of curving and stability.In mechatronic vehicles, actuators are used with the conventional suspension components to provide additional stiffness or damping forces needed to optimise a vehicle for a wide variety of scenarios, and not rely on a sub optimal combination of passive components.This research demonstrates the benefits of active guidance and steering when compared to a conventional vehicle using simulation results from a multi-body simulation software Simpack. It also provides insights into the relative performance of the mechatronic schemes. The Simpack modeling allows for a complex model with high fidelity, which provides an additional level of proof of the control algorithms working on a real rail vehicle. Each vehicle is assessed in terms of guidance on straight track, steering on curved track, actuation requirements and wheel-rail wear. Significant benefits are demonstrated in one of the guided vehicles with independently-rotating wheelsets.

On the mechanical behavior of rubber springs for high speed rail vehicles

There are many engineering design problems that call for rubber components as the best solution. Vulcanized rubber has found its way into all sorts of devices, from the universal automobile pneumatic tire to the ubiquitous compliant bushing. Some high-speed rail vehicle suspensions make use of rubber, not only in the air spring itself, but also in the auxiliary spring. The mechanical characteristics of this component influence vehicle dynamics and, therefore, accurate spring models with which to conduct dynamic analysis would make for powerful design tools. Nevertheless, the mechanical behavior of rubber defies simple modeling on account of stress relaxation, creep, set, viscosity, internal friction, and nonlinear stress–strain relations. Despite the advances in the micromechanical understanding of these phenomena, as well as in the macroscopic modeling of rubber spring behavior, there is ample room for refinement, and this is precisely the goal of this paper. The mechanical behavior of a particular rubber spring for high speed rail vehicles has been characterized. The results reveal the necessary components of the model, and suggest the appropriate procedure for parameter extraction. Our model proposal consists of three elements in parallel: a nonlinear elastic spring; a “soft friction” element; and a Maxwell viscous component. The characterization procedure takes into account both stress relaxation and nonlinear elasticity. The proposed model accurately reproduces experimental results and may then be used with confidence in any type of numerical simulation. Nevertheless, for this statement to be true, the problem of “numerical softening” potentially induced by soft friction models should be resolved. The paper will show that a trailing moving average filter, seamlessly tied to the model, wipes out the softening effect.

Numerical analysis of beam rail bridges - impact factors in the vertical deflection

The impact factors in the vertical deflection obtained in dynamic analysis of BTT systems - bridged / track structure / high speed train (BTT) - are discussed. The BTT system is one of 5 bridges spanning from 15 m to 27 m, modelled as simply supported beams loaded by ICE-3 trains traveling at high speeds. The two-dimensional, physically non-linear BTT model includes: viscoelastic suspension of rail vehicles on two independent axle bogies and non-linear one-sided wheel-rail contact springs according to Hertz theory, access zones for composite construction. The BTT system was divided into subsystems loaded with vertical interactions transmitted by elastic or viscoelastic and physically linear or nonlinear constraints. Using Lagrange equations and internal aggregation of subsystems, discretised according to the finite element method, matrix equations of motion of the subsystems were obtained, with explicit linear left sides and nonlinear implicit right sides, which were integrated numerically using the Newmark method with parameters βN=1/4, γN=1/2. The analysis focus on the effect of random track irregularities on the dynamic response of BTT systems.

Sensor Fault Detection for Rail Vehicle Suspension Systems With Disturbances and Stochastic Noises

This paper develops a sensor fault detection scheme for rail vehicle passive suspension systems, using a fault detection observer, in the presence of uncertain track regularity and vehicle noises that are modeled as external disturbances and stochastic process signals. To design the fault detection observer, the suspension system states are augmented with the disturbances treated as new states, leading to an augmented and singular system with stochastic noises. Using system output measurements, the observer is designed to generate the needed residual signal for fault detection. Existence conditions for observer design are analyzed and illustrated. In term of the residual signal, both fault detection threshold and fault detectability condition are obtained, to form a systematic detection algorithm. Simulation results on a realistic vehicle system model are presented to illustrate the observer behavior and fault detection performance.

Rail vehicle suspension condition monitoring – approach and implementation

Rail vehicle suspension is responsible for providing proper running behavior and safety. In order to keep appropriate safety level, low wear of wheels and rails, and also regular transport services, it should be monitored. The paper deals with the problem of suspension fault detection by introducing methods implemented in rail and track monitoring system developed within the framework of the project: ‘MONIT – Monitoring of Technical State of Construction and Evaluation of its Lifespan’. The approach to suspension fault detection presented in the paper consists of three levels, especially the method based on the multidimensional analysis of acceleration signals statistical parameters.

Modeling and control of rail vehicle suspensions: A comparative study based on the passenger comfort

This paper deals with the modeling and control of rail vehicle suspensions. The analytical models of the quarter rail vehicle with a passenger seat, describing the vertical dynamic, are presented for passive and active suspensions. Three controllers, i.e. PID-ZN, LQR and a PID-LQR are designed in order to improve the passenger comfort. This comfort is evaluated in terms of the passenger displacement, acceleration and frequency as a response of a two types of rail imperfection excitations. Results show that passenger comfort can be improved up to 98%. The obtained results prove that the active suspension with a PID- LQR controller yields the best results by regrouping the advantage of both PID and LQR controllers.

Analysis of Rail Vehicle Suspension Spring with Special Emphasis on Curving, Tracking and Tractive Efforts

The dynamics of the rail vehicle represents a balance between the forces acting between wheel and rail, the inertia forces and the forces exerted by suspension and articulation. Axial loading on helical spring causes vertical deflection at straight track but failures calls to investigate for lateral and longitudinal loading at horizontal and vertical curves respectively. Goods carrying vehicle has the frequent failures of middle axle inner suspension spring calls for investigation. The springs are analyzed for effect of stress concentration due to centripetal force and due to tractive and breaking effort. This paper also discusses shear failure analysis of spring at curvature and at uphill at various speeds for different loading condition analytically and by finite element analysis. Two mass rail vehicle suspension systems have been analyzed for vibration responses analytically using mathematical tool Matlab Simulink and the same will be evaluated using FFT vibration analyzer to find peak resonance in vertical, lateral and longitudinal direction. The results prove that the suspension acquires high repeated load in vertical and lateral direction due to tracking and curving causes maximum stress concentration on middle axle suspension spring as height of this spring is larger than end axle spring in primary suspension system and responsible for failure of middle axle suspension spring due to high stress acquisition.

An efficient recursive least square-based condition monitoring approach for a rail vehicle suspension system

ABSTRACTA model-based condition monitoring strategy for the railway vehicle suspension is proposed in this paper. This approach is based on recursive least square (RLS) algorithm focusing on the deterministic ‘input–output’ model. RLS has Kalman filtering feature and is able to identify the unknown parameters from a noisy dynamic system by memorising the correlation properties of variables. The identification of suspension parameter is achieved by machine learning of the relationship between excitation and response in a vehicle dynamic system. A fault detection method for the vertical primary suspension is illustrated as an instance of this condition monitoring scheme. Simulation results from the rail vehicle dynamics software ‘ADTreS’ are utilised as ‘virtual measurements’ considering a trailer car of Italian ETR500 high-speed train. The field test data from an E464 locomotive are also employed to validate the feasibility of this strategy for the real application. Results of the parameter identification performed indicate that estimated suspension parameters are consistent or approximate with the reference values. These results provide the supporting evidence that this fault diagnosis technique is capable of paving the way for the future vehicle condition monitoring system.

A Nonlinear Model of Mix Coil Spring – Rubber for Vertical Suspension of Railway Vehicle

Abstract The paper focuses on a nonlinear model to represent the mechanical behaviour of a mix coil spring - rubber used in the secondary suspension of passenger rail vehicles. The principle of the model relies on overlapping of the forces corresponding to three components - the elastic component, the viscous component and the dry friction component. The model has two sources on non-linearity, in the elastic force and the friction force, respectively. The main attributes of the model are made visible by its response to an imposed displacement-type harmonic excitation. The results thus obtained from the applications of numerical simulation show a series of basic properties of the model, namely the dependence on amplitude and the excitation frequency of the model response, as well as of its stiffness and damping.