Bogie System Research Articles

A proactive opportunistic maintenance decision model based on reliability in train systems

This paper presents an innovative framework for optimizing maintenance strategy in complex electromechanical systems (CEMS), by mitigating over-maintenance and suboptimal resource allocation. This study proposes an optimized maintenance strategy based on opportunistic maintenance with reliability as the core. A topological network model is used to establish a model that forecasts system reliability from function and structure, resulting in the identification of critical components in the system. Subsequently, a maintenance model for mechanical, electrical and information components is proposed and a method for determining maintenance reliability thresholds is suggested. The research imposes constraints in component and system reliability, in constructing an opportunistic maintenance strategies model. The objective of this model was to minimize the maintenance cost. A case study on high-speed railway bogie system supports this strategy, effectively guaranteeing system reliability while reducing maintenance costs. Maintenance resources are allocated reasonably across various stages, thereby reducing wastage of resources.

Steering Mechanism and Capability of Forced Steering Device for Low-Floor Light Rail Train

For 70% low-floor trains on the light rail lines in Changchun, a multi-linkage forced steering device (FSD) is developed aiming at relieving the independently rotating wheelset (IRW) excessive flange wear and improving IRW bogie system running safety on curve line. This FSD employs guiding mode of steering four independently rotating wheels separately in a two-axle bogie, that is, four FSDs are employed to work together to realize the steering of a two-axle bogie. One side of an FSD is connected to the axle of an independently rotating wheel while the other side is attached to the front or rear vehicle body. When train passes through curve, the yaw angle between the IRW bogie and the front or rear carbody drives the linkage system to rotate to guide the independently rotating wheel towards its radial position. The coupled vehicle-track dynamics model for a 6-module single-type low-floor light rail train is developed and simulations of the train passing through tangent and curved tracks with and without FSD proposed are carried out. The results indicate that the FSD can improve the IRW restoring capability on tangent track and curve negotiation performance on whether sharp, medium, or large curved track. For example, passing through a curve with a radius of 200[Formula: see text]m, the IRW friction work has the biggest drop by 62.07% and the wheelset attack angle is second with a reduction rate of 55.02%. Adopting of larger steering stiffness, smaller steering clearance, and lever ratio greater than the ideal value can guarantee the higher steering ability of FSD. Besides, lower longitudinal stiffness of the trailer primary suspension is recommended because it can also enhance the steering ability of the FSD.

Modelling of high frequency vibration of railway bogies’ subcomponent based on structural dynamics: A case study for lifeguard of metro bogie

The sub-components of railway bogie have been frequently reported to be subjected to the vibration fatigue due to the wheel/rail high frequency vibration. An efficiency numerical model is thus desirable to simulate the high frequency vibration of railway bogie, which can substantially enhance the design efficiency of railway bogie system considering the vibration fatigue. Therefore, this paper aims to proposing a modelling methodology for simulating the high frequency vibration of railway bogies’ subcomponents, and a lifeguard of metro bogie was taken as an example. Firstly, a field test measurement of lifeguard for the metro bogie was primarily introduced to demonstrate the high frequency vibration characteristics and the related failure mechanisms arising from the wheel/rail high frequency impact. Subsequently, a random vibration model for the railway bogie system and the lifeguard based on the rigid/flexible coupled dynamics were developed to simulate the high frequency vibration and the dynamic stress developed at the lifeguard. This method was subsequently employed in the structural optimization for the lifeguard. The results showed that the proposed methodology can effectively simulate the high frequency vibration of lifeguard of bogie system based on the measured axle box acceleration, and the optimized structure can effectively increase the service lifetime under the excitation of wheel/rail high frequency vibration.

Simulation on the Effect of Braking Force and Brake Shoe Material Type on The Wear Rate of Railway Bogie Brake Block

The brake block in the railway bogie system is an important component in supporting the operational safety of trains, so it needs to be inspected to determine its performance and service life. A simulation-based study was conducted to predict the wear rate of railway brake block with oriented braking force (F = 25.66 kN - 29.54 kN) and different material types, namely grey cast iron with hardness 170 HBN and metallic composite with hardness 90 HRR. The method of the study was carried out by Finite Element Analysis (FEA) simulation and calculating the wear rate with the Archard wear equation to measure the comparison of the amount of wear volume that occurs on the two materials. The results of the braking ability calculation can be concluded that the different types of brake block materials can affect the ability to decelerate during the deceleration process, causing differences in stopping mileage according to the type of material, such as gray cast iron (μ = 0.30) which has an average mileage of 15 metres and metallic composite (μ = 0.21) has an average mileage of 66 metres. The wear simulation results obtained are that the grey cast iron brake block has an average wear rate of 2,8285e-08 /s which is greater than the metallic composite which is only 1,5391e-08 /s. With this data, it can be concluded that oriented to the braking force load, the metallic composite brake block material has the advantage of a longer service life than grey cast iron.

The Two-Parameter Bifurcation and Evolution of Hunting Motion for a Bogie System

The complex service environment of railway vehicles leads to changes in the wheel–rail adhesion coefficient, and the decrease in critical speed may lead to hunting instability. This paper aims to reveal the diversity of periodic hunting motion patterns and the internal correlation relationship with wheel–rail impact velocities after the hunting instability of a bogie system. A nonlinear, non-smooth lateral dynamic model of a bogie system with 7 degrees of freedom is constructed. The wheel–rail contact relations and the piecewise smooth flange forces are the main nonlinear, non-smooth factors in the system. Based on Poincaré mapping and the two-parameter co-simulation theory, hunting motion modes and existence regions are obtained in the parameter plane consisting of running speed v and the wheel–rail adhesion coefficient μ. Three-dimensional cloud maps of the maximum lateral wheel–rail impact velocity are obtained, and the correlation with the hunting motion pattern is analyzed. The coexistence of periodic hunting motions is further revealed based on combined bifurcation diagrams and multi-initial value phase diagrams. The results show that grazing bifurcation causes the number of wheel–rail impacts to increase at a low-speed range. Periodic hunting motion with period number n = 1 has smaller lateral wheel–rail impact velocities, whereas chaotic motion induces more severe wheel–rail impacts. Subharmonic periodic hunting motion windows within the speed range of chaotic motion, pitchfork bifurcation, and jump bifurcation are the primary forms that induce the coexistence of periodic motion.

Mechanism and performance of a passive auxiliary steering device for low-floor light rail vehicle

For low-floor light rail vehicles, a passive auxiliary steering device (ASD) is developed aiming at relieving the independently rotating wheelset (IRW) excessive wear and improving IRW bogie system running safety on curve line. The ASD can be briefly seen as some longitudinal springs arranged between a carbody with IRW and a carbody ahead or behind it to increase the vehicle horizontal flexural stiffness. Consequently, the vehicle will possess the characteristics of both single-type vehicle and traditional vehicle. When passing curved track, the yaw angle between the adjacent carbodies deforms the springs to generate moment which will reduce the unbalanced centrifugal force of the carbody with IRW. As a result, the centering ability of the IRW bogie is improved. The vehicle-track coupled dynamics model for a 6-module single-type low-floor light rail vehicle is developed and the simulations of vehicle passing through tangent and curve lines with and without ASD are carried out. The results indicate that the ASD can improve the IRW restoring capability on tangent track and the IRW negotiation performance on medium and large curved tracks. Besides, larger spring preload, larger steering stiffness and smaller steering clearance are preferred to guarantee the higher performance of this ASD.

Optimization design for the installation position of hold bracket in railway bogie system by uniform design method

ABSTRACT The sensor hold bracket design is an essential element for running safety in the railway vehicle bogie braking system. The installation position of the hold bracket in the bogie system affects the brake sensing performance. This paper aims to determine the optimal installation position of the hold bracket. Three installation angles and one geometry dimension of a holding bracket are selected for the control factors. The uniform design of the experiment method creates a set of experiments. The surrogate models from input and output data are obtained and compared by applying Kriging interpolation and radial basis functions. The final optimal design models of the holding bracket for two surrogate models are determined using the genetic algorithm. The results show that the optimized parameters could substantially improve the installation angle error of the pressure switch from 4° to 0.04°, which aligns with expectations. Finally, to confirm the effect of the control parameters and their reliability and validity, the impact of the pressure switch is expected when the optimal hold bracket model is installed in the railway vehicle bogie system. As a result, the optimal design procedure can improve and reduce the risk of sensor failure during train operation.

Design and Fabrication of Rocker Bogie System

Design and Fabrication of Rocker Bogie System

The Application and Research of Particle Swarm Optimization Radial Basis Function Network Driven by Edge Computing in Bogie Fault Diagnosis

The bogie system is a key system that affects the safety and quality of high-speed train operation. Constructing a fault diagnosis model for the bogie system can effectively improve the safety and comfort of high-speed train operation. The traditional modeling method uses the BP neural network to fit the temperature and other parameters of the bogie system. However, because the BP neural network is prone to fall into local minima, slow convergence and poor diagnostic accuracy, this paper proposes a radial basis function network bogie fault diagnosis model based on particle swarm optimization based on edge computing. The model combines edge computing and particle swarm optimization algorithm to improve the accuracy and real-time of bogie fault diagnosis. By implementing model training and inference on edge devices, data transmission latency has been reduced and diagnostic efficiency has been improved. A particle radial basis neural network (PSRB) was designed using a highly convergent particle swarm optimization algorithm, and the parameters of the radial basis neural network (RBF Neural Networks) were optimized using the Particle Swarm Optimization algorithm. Based on the complexity of the input parameters of the bogie system, determine the input and output parameters of the model, and use particle swarm optimization algorithm to search for the optimal values of the basis function center, width, and output layer weight threshold of the RBF neural network. The composite algorithm was applied to the fault diagnosis of the bogie system, and a particle radial basis neural network bogie fault diagnosis model was designed. The simulation and experimental results of the model show that the diagnostic model can effectively improve the identification accuracy of fault diagnosis, with a minimum error accuracy of 0.0255, saving computation time. The computation time is reduced to 2.9 seconds, eliminating the influence of non target parameters on the inversion results. This model can also be used in other systems of high-speed trains and has practical application value.

Effect of motor suspension parameters on bifurcations for a nonlinear bogie system

This paper aims to investigate the effect of motor suspension parameters, specifically damping and stiffness, on the bifurcations of a bogie system. A motor bogie model with a nonlinear smooth equivalent conicity function is established. The study includes qualitative analyses of the stability and the Hopf bifurcation of the equilibrium, with the running speed as the single parameter. Furthermore, the generalised Hopf bifurcation and Hopf-Hopf bifurcation of the equilibrium, based on two motor suspension parameters, are also analysed. The paper delves into the codimension-1 and codimension-2 bifurcations of the limit cycles generated by the Hopf bifurcation, including Neimark–Sacker bifurcation, fold bifurcation, cusp bifurcation, 1:3 resonance, and 1:4 resonance. Analytical investigations reveal that the cusp bifurcation alters the type of fold bifurcation (subcritical or supercritical), and the fold bifurcation influences the stability and bifurcation direction of the limit cycle. Additionally, resonance occurs between the motor and the bogie frame. Since the subcritical (supercritical) Neimark–Sacker bifurcation produces an unstable (a stable) torus, the resonance points associated with the subcritical Neimark–Sacker bifurcation will lead to the instability of the motor bogie. The bifurcation analysis on the motor suspension parameters in this paper offers a theoretical reference for enhancing the stability of the motor bogie.

Suspension parameters for low-damped carbody oscillation of high-speed railway vehicle

This study presents an optimization method to design the suspension properties associated with low-damped carbody oscillations for high-speed railway vehicles. In this method, the least damping ratio for the low-frequency modes in the entire service speed range and the critical speed for a worn wheel are proposed for the design objectives. Based on the linearized vehicle model, a genetic algorithm is applied to determine the optimal suspension properties to maximize the least damping ratio while maintaining the critical speed above the desired speed. The optimization results show that the proposed method can enhance lateral ride comfort by eliminating the region where the least damping ratio of the carbody mode decreases excessively and securing a constant for the entire service speed range. The least damping ratio was improved from approximately 5.7% to 15.6% and the critical for the worn wheel increased from approximately 430 to 499 km/h. Parametric studies are conducted to investigate the influence of the tolerances of the suspension properties, and the results provide useful information regarding the manufacture of suspension elements and assembly of the bogie system. The validity of the optimized suspension properties is verified from the simulation results using railway vehicle dynamics software.

A method for reliability assessment of complex electromechanical system based on improved network connectivity entropy

The interconnectivity of components in complex electromechanical system (CMES) plays a critical role in ensuring system reliability. To examine the effect of component failures on system reliability, this work proposes a new reliability assessment method for CEMS based on improved network connectivity entropy. This method takes into account the mechanical, electrical, and information characteristics of components, and employs a comprehensive component importance calculation approach based on PageRank, which considers the functional impact of components. The reliability assessment model, considering both functional and topological attributes of the system, is established through the theory of network connectivity entropy. The proposed method is then demonstrated through an application to a bogie system of the CRH2008A high-speed railway. The proposed approach, rooted in topological networks, integrates component degradation into the physical structure of CEMS, providing a comprehensive way to deduce the impact of component failures on system reliability. Validity is demonstrated through case studies.

A Novel Multi-state Bogie System Reliability Evaluation Approach by Extended d-MC Model for High Speed Train

Abstract Bogie is a pivotal system and plays a critical part in the safety and reliability management of high speed rail. However, the available bogie system reliability analysis methods lack the consideration of multi-state characteristics, and the common multi-state reliability analysis methods, being an NP-hard problem, lead to a low efficiency. In order to overcome the mentioned drawbacks, this paper proposes a novel multi-state rail train bogie system reliability analysis approach based on the extended d-MC model. Three different function interactions within the bogie system are considered to build the multi-state bogie system flow network model. Meanwhile, an extended d-MC model is established to remove unnecessary d-MC candidates and duplicates, which greatly enhances the computing efficiency. The bogie system reliability is calculated, and the examples are provided. Numerical experiments are carried out for the different operational conditions of the bogie system and are used to testify the practicability of the method projected in this article, and is is found that the proposed method outperforms a newly developed method in solving the multi-state reliability problems.

Reliability Analysis on the Bogie System at Indonesian High-Speed Trains in the Design Phase to Improve Service Quality

High-speed train (HST) Indonesia is rail-based public transportation which is planned to be implemented in Jakarta - Surabaya. To maintain the HST for excellence service, it is necessary to conduct a study on the quality of the service. This paper tries to approach the Bogie system quality service from the reliability perspective in the design phase. The steps taken to maintain continuity of service quality are to identify critical sub-systems/components that affect the decline in reliability, Risk Analysis, build Reliability Block Diagram (RBD) from sub-system/components that have been identified in the bogie system, calculate initial reliability based on RBD, develop designs to minimize the potential for a decline in reliability, and compile procedure for evaluating and re-calculation the value for the reliability of the bogie system. Reliability is targeted at 0.9, which means that all service quality designs must always make the reliability value above the target. This paper is expected to provide an overview of potential that may occur based on predictions of decreasing reliability values until the operating period ends. So that anticipation of minimizing the decline in the value of reliability can be done.

Bifurcation analysis of the bogie system with time delay and the influence of parameters on the system

In this paper, a bogie system with time delay is established. The centre manifold theorem and norm form theory are used to reduce the infinite dimensional delay system to the finite dimensional ordinary differential system, and the bifurcation behaviour of the bogie system is analysed. The MatCont toolkit was used to verify the subcritical bifurcation in the system. In addition, the influence of parameters on the bifurcation diagram of the system and the influence of parameters on the critical speed of the bogie system during the hunting motion are also analysed.

Dynamics of moving coupled objects with stabilizers and unconventional couplings

A comprehensive investigation was carried out to analyze the vibration stability of a coupled bogie system moving uniformly along a complexly modeled flexibly supported infinite high-order shear deformable coupled beam system on a viscoelastic base. The main contribution of this study involves a comparative analysis of the specific coupling of the bogie system with and without the proposed additional stabilizer, in comparison to conventional cases. The study demonstrates significant benefits of the newly proposed options of dual coupling and additional stabilizers in terms of stability. Another contribution of the study is the feasibility of the proposed unconventional models in technical practice. A phenomenon has been discovered that increasing the viscous damping in a special coupling leads to the occurrence of motion instability in the mechanical system. The paper also presents a novel technical solution for connecting moving objects at high speeds. The benefits of the additional oscillator as a stabilizer are extensively illustrated through numerous different examples. It is well-known that when the velocity of masses, such as the bogie or any other complex oscillator, exceeds the minimum velocity at which waves propagate in the beam, the oscillation of the system may become unstable. Therefore, it is crucial to determine the conditions and stable regions of motion that involve specific combinations of system parameters. The region of instability is identified within the parameter space of the system using the D-decomposition technique and the argument principle. The bogie is specifically connected to another bogie in two new ways: with an additional stabilizer allowing double transverse displacement and providing an additional contact with the base, or with a specific coupling that enables simultaneous rotational and transverse displacement at the contact point. The analysis reveals two key findings. First, the additional mechanical stabilizer allows for the widest range of permissible suspension stiffness (largest stability region) when the connection is conventional. Second, enabling transverse displacement in the couplings results in a stable regime of motion at much lower suspension stiffness compared to other cases.

Evaluation of the dynamic behaviors of a train braking system considering disc–block interface characteristics

Disc–block interface properties have prominent influence on the dynamic behaviors of train braking systems. In this study, the tribological characteristics of small-scale train friction blocks with different perforation diameters at the centre of the block surface were investigated using a disc–block test rig. And the Stribeck model parameters of the disc–block friction interface were identified to intuitively characterize the evolution law of stick–slip characteristics with the variation of block perforation diameters. Then, a trailer bogie braking system model of a high-speed train considering the coupling effects between the essential brake unit, wheelset and bogie frame was established. And the identified Stribeck parameters were introduced into the proposed braking system dynamics model to establish a relationship between the friction characteristics of the disc–block interface and the dynamic behaviors of the train braking system. Based on this, the cross-scale analysis was performed to evaluate the dynamic performance of a train braking system affected by the perforated friction block via classical stability theory and numerical simulation. The results show that the friction block with a perforation diameter of 3 mm can effectively suppress the stick–slip vibration of the disc–block friction interface, then reducing the oscillation of system components and enhancing the stability of the entire trailer bogie system.

Modeling failure propagation to analyze the vulnerability of the complex electromechanical systems under network attacks

Since the complex electromechanical system (CMES) is a complex integration of multiple minimum maintenance units (MMUs), a single faulty MMU can trigger multi-step failures and eventually damage a substantial portion of the CMES. To investigate the failure propagation process and analyze the impact of the CMES under MMU attacks, we first abstract the system as a directed network composed of MMUs, machine-electricity-information connections, and functional properties. Subsequently, a fault propagation model is constructed based on the fault occurrence probability and matrix transformation, which considers the topological and functional attributes of the system. Then, we build the attack graphs to evaluate the faulty edges on the system’s vulnerability and propose some vulnerable indices based on the node attack strategies to quantify the attack impact of the malfunctioning nodes on the CMES network. Finally, a bogie system of the high-speed train is selected as a case study to verify the validity of the proposed method. Based on the findings, we can clarify the failure propagation behavior and quantify the impact of the faulty nodes and edges on the CMES network. Furthermore, the critical connections and nodes that significantly impact system vulnerability can be identified. Hence, our work can provide guiding significance for developing maintenance strategies to reduce losses and optimize the management scheme.

A dynamic failure mode and effects analysis for train systems failures risk assessment using FCM and prospect theory

Improving the reliability of railway train systems and preventing potential failures in the train operation process is one of the most significant tasks. The failure mode and effects analysis (FMEA) is the most effective and widely applied technique for identification, evaluation, and prevention risk of potential failures in diverse fields. Nevertheless, current risk prioritization approaches for FMEA overlook the transfer of decision makers’ risk preferences under different risk states of potential failures. In addition, little attrition has been paid to addressing the risk prioritization problems in FMEA under a dynamic environment. In order to bridge these research gaps, this paper proposes a dynamic prioritization approach for FMEA by integrating the Fuzzy Cognitive Map (FCM) and the prospect theory. First, improved weighted arithmetic averaging (WAA) operator based on the similarity measure is constructed to aggregate each decision maker’s evaluation information. Then, the FCM is applied to obtain the risk matrix and interaction relationships among failures under different risk states. Next, the dynamic prospect theory is built to determine the risk priority of each failure by considering the risk preference of decision makers, in which the dynamic weight functions are derived based on the risk matrix under different risk states. Finally, the proposed dynamic risk prioritization approach for FMEA is tested by the failures risk analysis of the railway train bogie system in the railway train systems. The comparison study is conducted to demonstrate the reliability and rationality of the proposed risk prioritization approach.

AttGGCN Model: A Novel Multi-Sensor Fault Diagnosis Method for High-Speed Train Bogie

The bogie system is a critical system for a high-speed train, which is composed of various mechanical parts. Therefore, the health of the bogie can directly affect the health of high-speed train. Temperature signals, speed signals and pressure signals are collected from the bogie can reflect its health. Hence, the multi-sensor fault diagnosis methods can provide novel solutions for the bogie health monitoring tool. This paper presents a novel bogie fault diagnosis scheme named the AttGGCN model, using graph convolutional network (GCN), gated recurrent unit (GRU) and attention mechanism. In this fault diagnosis scheme, the bogie data network is established firstly. Then, temporal and spatial features are extracted and fused using GCG unit. Finally, the GCN are used for fault identification. Twenty-four kinds of measured signals and seven types of faults from actual High-speed train in operation are utilized for verification. Results show that the AttGGCN model has the highest accuracy compared to conventional models. In addition, experiments on different scales of training sets suggest that the AttGGCN model has strong robustness in small-scale datasets. Besides, ablation experiments certificate that the attention mechanism is able to strengthen the feature extraction ability.