Search Results (45)

This study has developed a novel measurement-based computational method that accurately determines the vertical and lateral wheel–rail contact forces transmitted from railway vehicles to the rails. A major contribution—and the first in the literature—is the analytical distribution of the total lateral wheelset force into its outer-wheel and inner-wheel components, thereby enabling precise individual evaluation of derailment risk on each wheel in curved tracks. Analytical equations derived from Newton’s second law were first formulated to express both vertical forces and total axle lateral force directly from bogie/axle-box accelerations and suspension reactions. To eliminate the deviations caused by conventional simplifying assumptions (neglect of creep effects, wheel diameter variation, and constant contact geometry), surrogate functions and distribution equations sensitive to curve radius, vehicle speed, and cant deficiency were introduced for the first time and seamlessly integrated into the equations. Validation was performed using the Istanbul Tramway multibody model in SIMPACK 2024x.2, with the equations implemented in MATLAB/Simulink R2024b. Excellent agreement with SIMPACK reference results was achieved on straight tracks and curves, after regression-based calibration of the surrogate functions. Although the method requires an initial regression calibration within a simulation environment, it relies exclusively on measurable parameters, ensuring low cost, full compatibility with existing vehicle sensors, and genuine suitability for real-time monitoring. Consequently, it supports predictive maintenance and proactive safety management while overcoming the practical limitations of instrumented wheelsets and offering a robust, fleet-scalable alternative for the railway industry. Full article

Dry friction dampers are widely used in railway vehicle suspensions due to their simplicity, robustness, and cost-effectiveness compared to hydraulic alternatives. However, accurately modelling their behaviour remains challenging because of the discontinuous nature of friction forces. This paper presents a comparative study between two modelling approaches: continuous (regularized) models, which smooth out discontinuities, and discontinuous (switch-based) models, which explicitly capture stick–slip transitions. Using a two-degree-of-freedom suspension system, both models are implemented and analyzed under steady-state and transient conditions. Results show that while continuous models are easier to implement and integrate numerically, they fail to capture key physical phenomena such as zero relative velocity intervals and force discontinuities. In contrast, discontinuous models offer superior physical fidelity and significantly better computational efficiency, especially during static friction phases. This study highlights the trade-offs between modelling simplicity and accuracy, providing valuable insights for the simulation and design of railway suspension systems. The findings support the use of discontinuous models in safety-critical simulations and suggest avenues for hybrid modelling strategies. Full article

In this paper, the rail mean vertical alignment is estimated through double integration of wheel–rail contact forces measured using dynamometric wheelsets on a dedicated track recording vehicle (TRV). A simplified three degrees of freedom (DOF) linear model of half a train coach has been developed for this purpose. The model’s ability to simulate the average left and right longitudinal level has been tested using vertical contact force recordings from a constant speed track section, as measured by the TRV. The results are compared with available track geometry (TG) data, recorded by the optical system of the same vehicle, used for condition monitoring of the Italian railway infrastructure. Model parameters, such as masses, stiffness, and damping of the suspensive system have been optimized. An error analysis has been conducted on results. A good agreement is found between simulated and recorded vertical alignment at the D1 level, suggesting the feasibility of using contact forces measured with instrumented wheelsets for railway TG condition monitoring. This computationally efficient approach highlights the potential of strain gauges and instrumented wheelsets as alternative or complementary technologies to the widely adopted accelerometers, rate gyros, and optical devices for railway condition monitoring. Given its low computational cost, embedded and real-time TG estimation could be further investigated. Full article

A condition-based monitoring (CBM) system provides the possibility for the railway industry to guarantee reliability by executing prompt and low-cost maintenance. In this study, a simple model-based condition monitoring strategy for the railway vehicle suspension system is demonstrated. The method is based on a recursive least-square (RLS) algorithm regarding a deterministic parametric model. The fault detection approach for the locomotive suspension system is illustrated with three diagnostic modules. Multi-body simulation data are employed to validate the feasibility of this CBM strategy. The designed diagnostic model reveals that the suspension parameter estimates are consistent with the reference values. The corresponding demonstrator provides evidence that the monitoring system has potential applications and is suitable for further development. Full article

This study investigates the dynamic interaction between railway vehicles and tracks, focusing on the effects of elastic–viscous properties of spring suspensions and track inertia. This research examines vertical oscillations of a railway car moving on a non-uniformly elastic track, modeled as a system with lumped parameters. Analytical and numerical methods are employed to derive track parameters by comparing frequency characteristics of continuous and discrete models. Key findings reveal that adjacent wheelsets influence interaction forces and bending moments by approximately 10%, while rail deflections are affected by up to 20% within the speed range of 60–180 km/h and for disturbances up to 20 Hz. Experimental validation using a roller test rig confirms the theoretical predictions, demonstrating the significance of track inertia and damping in dynamic analyses. This study provides practical recommendations for improving railway vehicle design and track maintenance, emphasizing the need to account for nonlinearities and inertial effects in high-speed scenarios. Full article

This document comprehensively analyses the literature on accelerometers used in monitoring systems designed for rail vehicle applications. It reviews the current research on this topic and highlights key findings, methodologies, and trends in the field. Additionally, it discusses the role of accelerometers in enhancing safety and performance within rail vehicle systems. This review is structured into several sections: Introduction, Fundamentals of Accelerometer Data, Signal-Processing Techniques, Examples of Accelerometers Used in Railway Monitoring Systems, and a Guide for Choosing the Right Accelerometer. One of the primary contributions of this paper is recommending the best accelerometer in terms of cost and performance for use in the rail vehicle industry. Future work will consider using an online detection tool for the acceleration of the frame of the railway coach and signalization of the peak values using the train intercom to the driver and static diagnosis systems. This approach aims to facilitate the detection of track irregularities, wind influence, and failures of the coach suspensions, which can be easily detected. Full article

A reduction of forces acting between the railway track and the vehicle is one of the key issues in the design of modern rolling stock. Because the capabilities of reducing wheel–rail contact forces in track curves by conventional methods are encountered at their limits, innovative approaches in the design of vehicle suspension and wheelset guidance occur. Among them, an active wheelset steering appears to be very promising. However, an active wheelset steering system is rather complicated and expensive and raises many safety issues. Therefore, a passive hydraulic system that links longitudinal motions of axle boxes is proposed. The system is relatively simple and, compared to the active wheelset steering, does not need any energy supply or sensor system for the detection of a track shape. Two arrangements of the hydraulic system had been proposed and implemented in a simulation model. The simulation model is based on a cosimulation of two separate models, a multibody model of an electric locomotive, and a model of the hydraulic system. The goal of this study is to evaluate the contribution of the hydraulic system to the natural radial alignment of wheelsets in curves and thus to reduce the wear of wheels and to determine the parameters of the hydraulic system to maximize the wear reduction benefits while minimizing a decrease in critical speed. Simulations of a vehicle running in various scenarios, including a run in a real track section of a length of 20 km, have been performed. As a criterion for the wear of wheels and rails, a T-gamma wear number was used, from which a sum of frictional work in wheel–rail contacts was calculated. The results of the simulations and the comparison of hydraulic axle box connection systems and a standard locomotive are presented and discussed in the paper. The results obtained confirmed a significant potential benefit of the proposed hydraulic system in reducing wheel wear on curved tracks. Full article

This paper aims to present a hybrid steering control method combining the self-guidance capability of a wheelset and fuzzy logic controller (FLC), which were applied to our new micro-autonomous railway inspection vehicle, enhancing the vehicle’s stability. The vehicle features intelligent inspection systems and a suspension system with variable damping capability that uses smart magnetorheological fluid to control vertical oscillations. A mathematical model of the steering dynamic system was developed based on the vehicle’s unique structure. Two simulation models of the vehicle were built on Simpack and Simulink to evaluate the lateral dynamic capability of the wheelset, applying Hertzian normal theory and Kalker’s linear theory. The hybrid steering control was designed to adjust the torque differential of the two front-wheel drive motors of the vehicle to keep the vehicle centered on the track during operation. The control simulation results show that this hybrid control system has better performance than an uncontrolled vehicle, effectively keeps the car on the track centerline with deviation below 10% under working conditions, and takes advantage of the natural self-guiding force of the wheelset. In conclusion, the proposed hybrid steering system controller demonstrates stable and efficient operation and meets the working requirements of intelligent track inspection systems installed on vehicles. Full article

When a railway train runs along a curved track with braking, the dynamic behaviors of the vehicle are extremely complex and difficult to accurately reveal due to the coupling effects between the wheel–rail interactions and the disc–pad frictions. Therefore, a rigid–flexible coupled trailer car dynamics model of a railway train is established. In this model, the brake systems and vehicle system are dynamically coupled via the frictions within the braking interface, wheel–rail relationships and suspension systems. Furthermore, the effectiveness of the established model is validated by a comparison with the field test data. Based on this, the dynamic response characteristics of vehicle under curve and straight braking conditions are analyzed and compared, and the influence of the curve geometric parameters on vehicle vibration and operation safety is explored. The results show that braking on a curve track directly affects the vibration characteristics of the vehicle and reduces its operation safety. When the vehicle is braking on a curve track, the lateral vibration of the bogie frame significantly increases compared to the vehicle braking on a straight track, and the vibration intensifies as the curve radius decreases. When the curved track maintains equilibrium superelevation, the differences in primary suspension force, wheel–rail vertical force, and wheel axle lateral force between the inner and outer sides of the first and second wheelsets are relatively minor under both straight and curved braking conditions. Additionally, under these circumstances, the derailment coefficient is minimized. However, when the curve radius is 7000 m, with a superelevation of 40 mm, the maximum dynamic wheel load reduction rate of the inner wheel of the second wheelset is 0.54, which reaches 90% of the allowable limit value of 0.6 for the safety index, and impacts the vehicle running safety. Therefore, it is necessary to focus on the operation safety of railway trains when braking on curved tracks. Full article

Demands for increasing the velocity and load carrying capacity of railway vehicles are a challenge to the passive suspension systems used for isolating the lateral vibrations of the carbody of a railway vehicle, especially under a wide range of vibration frequencies. Semiactive suspension systems, especially systems with a magnetorheological damper (MRD), have been investigated as promising alternatives. Many control algorithms have been developed for fine-tuning the damping force generated by MRDs, but they have been ineffective in isolating carbody vibrations at or around the resonance frequencies of the carbody and bogie. This study aims to develop a mixed control algorithm for a new skyhook (SH) control and a new displacement–velocity (DV) control to improve the effectiveness of vibration isolation in resonance frequency regions while producing high performance across the remaining frequencies. The damping coefficient of the new SH controller depends on the vibration velocity of the components of the suspension system and the skyhook damping variable, whereas that of the new DV controller depends on the velocity and displacement of the components of the suspension system and the stiffness variable. The values of the skyhook damping variable and stiffness variable were identified from the vibration velocity of the carbody using the trial and error method. The results of a numerical simulation problem indicated that the proposed control method worked effectively at low frequencies, similar to the conventional SH–DV controller, whereas it significantly improved ride comfort at high frequencies; at the resonance frequency of the bogie (14.6 Hz), in particular, it reduced the vibration velocity and acceleration of the carbody by 50.85% and 45.39%, respectively, compared with the conventional mixed SH–DV controller. The simplicity and high performance of the new mixed SH–DV control algorithm makes it a promising tool to be applied to the semiactive suspension of railway vehicles in real-world applications. Full article

As a crucial component of CRH (China Railway High-speed) trains, the safety and stability of the suspension system are of paramount importance to the overall vehicle system. Based on the framework of probabilistic relevant principal component analysis (PRPCA), this paper proposes a novel method for incipient fault diagnosis in the CRH suspension system using PRPCA and support vector machine (SVM). Firstly, simulation data containing multiple types of fault information are obtained from the Simpack2018.1-Matlab2016a/Simulink co-simulation platform. Secondly, the nonlinear PRPCA approach, based on the Wasserstein distance, is employed for fault detection and data preprocessing in the suspension system. Furthermore, SVM is used for fault recognition, and the F1-Measure index is utilized for a comprehensive evaluation to assess the fault diagnosis performance more intuitively. Finally, based on the comparison results with traditional principal component analysis (PCA) and SVM-based methods, the proposed incipient fault diagnosis method demonstrates superior efficiency in fault detection and recognition. However, the proposed method is not very sensitive to sensor faults, and the performance of sensor fault diagnosis needs to be further improved in subsequent research. Full article

This study primarily investigates the adaptability and performance of hydraulic–electric regenerative dampers for high-speed trains by substituting conventional primary dampers with hydraulic–electric regenerative dampers. The primary objectives are to develop a detailed model of primary suspension regenerative damper (PSRD) energy conversion that incorporates factors such as oil pressure loss, motor efficiency, and overall system efficiency, and to perform a comprehensive comparative analysis of vibration responses, wheel wear, comfort indices, and power generation using an integrated MATLAB and SIMPACK co-simulation platform. The results reveal that at an operational speed of 350 km/h, the dynamic responses of the carbody, bogie, wheelset, and dampers equipped with the proposed PSRD systems closely align with those of conventional primary vertical damper systems. The detailed PSRDs’ hydraulic–mechanical–electrical model effectively captures the subtleties of oil pressure fluctuations and their impacts. The wear distribution and magnitude across the vehicle remain consistent during acceleration, constant, and deceleration speeds, ensuring uniform wear characteristics. Under real-world railway operational conditions, the ride comfort metrics of vehicles fitted with regenerative dampers are comparable to those with conventional primary vertical dampers. Furthermore, each regenerative damper can generate up to 21.72 W of electrical power, achieving a generation efficiency of 45.28%. Finally, a test rig was designed and fabricated to validate the primary suspension regenerative damper (PSRD) model, showing good agreement between predicted and actual damping force and power regeneration, with results indicating a peak damping force of 12.5 kN and approximately 230 W of regenerated power. This research provides a theoretical foundation and experimental validation for implementing power regeneration mechanisms in railway transportation, demonstrating that the hydraulic–mechanical–electrical PSRD model can fulfil the performance criteria of conventional dampers while offering substantial energy harvesting capabilities. This advancement not only enhances energy efficiency but also contributes to the sustainable development of high-speed rail systems. Full article

A battery track engineering vehicle faces challenges such as derailment and other safety concerns when navigating an R20m minimum radius curve, primarily owing to its low vertical and horizontal stabilities. To address these issues, a methodology integrating genetic optimization algorithms with a rigid and flexible coupled multi-body dynamics simulation is proposed to optimize the primary suspensions of the bogie of the vehicle. Initially, a multi-objective optimization model combining rigid and flexible coupled multi-body dynamics of battery track engineering vehicles with a genetic optimization algorithm was formulated. Subsequently, the optimal Latin hypercube design was applied to analyze the sensitivity of vertical and horizontal stability to various suspension parameters. Finally, a non-dominated sorting genetic algorithm (NSGA-II) and an archive-based micro genetic algorithm (AMGA) were applied to optimize the primary suspensions to enhance stability. Consequently, a set of optimal suspension parameter combinations was obtained. A notable enhancement was observed in the lateral stability of the optimized battery track engineering vehicles by 23.33% and in the vertical stability by 3.5% when traversing the R20m minimum radius curve, thereby establishing a theoretical foundation for further improving the running safety of railway vehicles and resolving the shortcomings of less research on the smallest radius curve. Full article

For better small-radius curve negotiation performance, the independently rotating wheelset has the potential to be equipped in urban rail transit. As a crucial part of the running gear, its dynamic characteristics directly affect the railway vehicle’s stability and curve negotiation ability. This study follows a model–simulation–experiment method to delve into the dynamic process and steady convergent process of the independently rotating wheelset. An improved mathematical dynamic model of the independently rotating wheelset is established, considering the gravitational restoring forces of the wheelset and different creepages between the left and right wheels. In addition, the gyroscopic effects on the independently rotating wheelset with positive wheel tread conicity and at high speeds are introduced and analyzed. With variations in the longitudinal speed and yaw suspension coefficients, three kinds of motions, derailment, hunting, and offset running, occur on the independently rotating wheelset. We find that the gyroscopic effects contribute to the slight self-guidance ability of the independently rotating wheelset, causing a hunting motion at high speeds. Through sufficient simulations, the improved mathematical dynamic model is verified to be closer to the dynamic model built in the general multibody system simulation software SIMPACK 2018 than the classical mathematical dynamic model. Further, we perform experiments on a scaled independently rotating wheelset experiment system. The dynamic characteristics derived from theoretical analysis, especially the slight self-guidance ability at high speeds, are verified. Full article

The timely detection of faults that occur in industrial machines and components can avoid possible catastrophic machine failure, prevent large financial losses, and ensure the safety of machine operators. A solution to tackle the fault detection problem is to start with modeling the condition monitoring signals and then examine any deviation of real-time monitored data from the baseline model. The newly developed deep long short-term memory (LSTM) neural network has a high nonlinear flexibility and can simultaneously store long- and short-term memories. Thus, deep LSTM is a good option for representing underlying data-generating processes. This paper presents a deep-LSTM-based fault detection method. A goodness-of-fit criterion is innovatively used to quantify the deviation between the baseline model and the newly monitored vibrations as opposed to the mean squared value of the LSTM residual used in many reported works. A railway suspension fault detection case is studied. Benchmark studies have shown that the deep-LSTM-based fault detection method performs better than the vanilla-LSTM-based and linear-autoregression-model-based methods. Using the goodness-of-fit criterion, railway suspension faults can be better detected than when using the mean squared value of the LSTM residual. Full article