In-train Forces Research Articles

A novel approach for longitudinal train dynamics simulations with multibody codes

The paper describes a novel approach to include longitudinal train dynamics within multibody codes by means of a dummy user force element. The latter solves the ordinary differential equations describing longitudinal train dynamics through the definition of additional dynamic states, and it calculates the in-train forces, which have a strong effect on the running safety of railway vehicles. The novel strategy allows to evaluate longitudinal train dynamics and multibody dynamics within the same computational framework, thus solving the dynamic states of both problems with the same numerical integrator. The method is first validated in simulation scenarios of an international benchmarking activity against traditional approaches and then it is applied to evaluate the dynamic safety of an emergency braking operation of a European freight train. With respect to developing multibody models with one body per vehicle in the train consist, the novel approach can be up to four times faster. Moreover, the novel method proves to be faster by up to one order of magnitude when compared to co-simulation strategies, whose accuracy is strongly related to a proper tuning of the communication rate.

A data-driven approach for railway in-train forces monitoring

Railway in-train forces are an essential element in assessing multiple aspects of rolling stocks. Conventional methods for obtaining the forces can be time-consuming and require significant investment in manpower and domain expertise, while only gathering the force data for specific service conditions one at a time. However, automatic train operation (ATO) systems can measure real-time information for trains and tracks by on-board and trackside devices, which could provide an opportunity for in-train forces monitoring. This paper presents a data-driven approach that uses ATO-measured data and a neural network model to monitor in-train forces under service conditions. To develop this approach, longitudinal train dynamics simulations (LTSs) for a freight train were conducted to establish the relationship between ATO measurements and in-train forces on specific couplers, which was embedded in a large amount of training data. After that, a specially developed self-attention-based causal convolutional neural network (SA-CNN) was employed to learn the underlying relationship and estimate the in-train force histories considering temporal dependencies. The comparative evaluation between the SA-CNN against four alternative neural network models revealed that the SA-CNN exhibits a slightly higher level of accuracy. Furthermore, the generalisation capability of the well-trained SA-CNN model was confirmed by numerical LTSs under four different service conditions. The results indicated that the data-driven approach has superior compatibility for arbitrarily combined inputs with significantly reduced computational time compared to LTSs. This approach holds the potential for achieving reliable in-situ monitoring of railway in-train forces, which is beneficial to both in-train force-related research and industrial applications.

Application of machine learning techniques to build digital twins for long train dynamics simulations

The paper shows the feasibility of building closed-form and fast-to-evaluate surrogate models via supervised kernel-based machine learning regressions behaving as digital twins for computationally expensive multibody simulations. The aforementioned surrogate models are adopted to predict the railway vehicle dynamics safety indexes defined in the international standards, depending on the wheel-rail forces, directly from the results of longitudinal train dynamics simulations. The digital twin models are trained with the outputs of Simpack multibody simulations of a reference freight wagon, to which the in-train forces calculated by an in-house MATLAB longitudinal train dynamics simulator are applied. Two machine learning techniques are considered: the support vector machine and the least-squares support vector machine regressions. Both techniques ensure a good accuracy even with a limited number of training samples. The derivation of the surrogate models can strongly enhance the modelling capabilities of common longitudinal train dynamics simulators, that cannot evaluate the wheel-rail contact forces. At the same time, the method shown in the paper allows to strongly reduce the total computational times, as the evaluation of the closed-form surrogate models allows to effectively estimate the safety indexes with no need for computationally demanding multibody simulations.

The influence of AAR coupler features on estimation of in-train forces

Inadequate management of large in-train forces transferred through coupler systems of a railway train leads to running and structural failures of vehicles. Understanding these phenomena and their mitigation requires accurate estimation of relative motions and in-train forces between vehicle bodies. Previous numerical studies have ignored inertia of coupling elements and the impacts between couplers. Thus, existing models underestimate the additional dynamic variations in in-train forces. Detailed multi-body dynamic models of two AAR (Association of American Railroads) coupler systems used in passenger and freight trains are developed, incorporating coupler inertia and various slacks. Due to the modeling and simulation complexities involved in a full train model, with such details of coupler system, actual longitudinal train dynamics is not studied. A system comprising only two coupling units, inter-connecting two consecutive vehicles, is modeled. Considered system has been fixed at one end and an excitation force is applied at the other end, to mimic a relative force transmission through combined coupler system. Simulation results obtained from this representative system show that, noticeable influence in in-train forces are expected due to the combined effect of inertia of couplers and intermittent impacts between couplers in the slack regime. Maximum amplitude of longitudinal reaction force, transferred from draft gear housing to vehicle body, is expected to be significantly higher than that predicted using existing models of coupler system. It is also observed that the couplers and knuckles are subjected to significant longitudinal and lateral contact forces, due to the intermittent impacts between couplers. Thus, accurate estimation of draft gear reaction force and impact forces between couplers are essential to design vehicle and coupler components, respectively.

Finite-Time Control of High-Speed Train With Guaranteed Steady-State and Transient Performance

With considering the inevitable factors of input nonlinearity, aerodynamic resistance, in-train force, external disturbance and unknown actuator failures, this paper investigates the position/velocity finite-time tracking control problem of high-speed train (HST) to improve the steady-state (tracking accuracy) and transient performance (overshoot and settling time) of the traction/braking control system. Since the traction/braking control system of HST requires rapid reaction speed to ensure the safe and reliable operation, an integer-order finite-time controller (IO-FTC) is developed firstly by utilizing finite-time control theory to improve the system transient performance. On the basis of ensuring the system transient performance, a fractional-order finite-time controller (FO-FTC) is designed by using the fractional stability principle and fractional integral to further improve the system steady-state performance and its robustness and anti-jamming capability. It should be noted that both IO-FTC and FO-FTC are essentially independent of the system model and can produce proper traction/braking force with only the actual and desired position/velocity of the leading vehicle. And the settling time of the system can be adjusted through the selection of different control parameters. The feasibility and effectiveness of the designed controllers are verified by theoretical analysis and simulation studies. And the developed methods are compared with the PID controller. Simulation results make it clear that the proposed methods are superior to PID.

The Digital Automatic Coupler (DAC): An Effective Way to Sustainably Increase the Efficiency of Freight Transport in Europe

This paper employs and improves TrainDy software to simulate the in-train forces of single and coupled freight trains with a Digital Automatic Coupler (DAC), having a length from 740 m to 1500 m and hauled mass between 1600 t and 8000 t. Software improvements have focused on the ability to natively simulate the electro-pneumatic (EP) brake, which will be a feature of the future DAC. The various types of DAC and their main features are outlined in the paper. The study shows that it is also possible to increase the trains hauled mass by using radio communication between traction units (TUs). The “relative approach” method is used to demonstrate the safety of these new trains. The paper’s main results are reported in the conclusions and demonstrate the effectiveness of both technologies in increasing freight transport efficiency, even when applied to coupled trains where one train is “classic” and the other is equipped with mechanical DAC.

Car and train platoon simulations

Detailed simulations of car and train platoons are critical steps towards successful implementations of the platooning technologies. This paper developed a simulation method that can be used for both car and train platoon simulations. The method includes three main parts: (1) a scalable adaptive longitudinal space controller, (2) 2D multibody dynamics simulations that consider wheel-rail contact (Polach model), tyre-road contact (Magic Formula), suspensions and in-train forces, and (3) a scalable parallel computing method that processes the dynamics simulation of each individual vehicle (one car or one carriage) by using one independent computer core. Two case studies were conducted to simulate a 6-car platoon and a 3-train platoon on real-world road and track. The maximum space errors for the car platoon and the train platoon results were about 0.32 and 0.23 m, respectively. When the platoons were running at a steady speed, space errors were well controlled within ±0.05 m for both car and train platoons. Example dynamics results were presented including wheel-rail contact forces, tyre-road contact forces, and carbody vibrations. This information can be used to conduct a wide range of related studies such as passenger ride comfort and system damage assessments.

INEW method for experimental-numerical locomotive studies focused on rail wear prediction

Locomotive-track interaction is commonly represented by a complex mechanical system which is modelled in numerical studies. Numerical studies alone are not enough to precisely describe the behaviour of this mechanical system due to the various elements that can only be delivered from field and laboratory experimental programs. One such element is wheel-rail wear that has been found to contribute a considerable portion of the total cost of maintaining heavily used railway systems. Simulation studies are typically used for predicting wear of wheels and rails, but the majority of these do not consider in-train forces nor provide detailed modelling of traction and braking events and often rely on historic wear rates for comparable materials, reducing the accuracy of the wheel-rail volume loss estimation. This paper proposes a methodology for wear rate experimental measurements that allow improving the accuracy of wear analyses using dynamic simulations. The proposed method considers in-train forces by performing longitudinal train simulations whose results are then implemented on a detailed locomotive vehicle dynamic model with a traction mechatronic system co-simulation approach. The wheel-rail contact stress and slip results are then post-processed into a Dynamic Load Spectrum that contains contact stress and wheel slip occurrences. The Dynamic Load Spectrum was used to measure the wear rates for Australian AS60 head hardened rail steel material operating in combination with Class B wheel steel material. The experimental program delivered more realistic wear rates that correspond to actual industry operational scenarios. The measured wear rates were used to estimate the rail material volume loss for a specific train trip.

Comparing the Efficiency and Effectiveness of Different Train-Following Control Algorithms for Fleets of Heavy-Haul Freight Trains under Moving Blocks

With the nationwide installation of positive train control (PTC) technology recently completed, freight railroads are searching for ways to leverage the technology to improve their operations beyond increasing safety. One possibility is reducing train headways through developing and installing a PTC-based moving-block system, thus increasing the capacity of railroad mainlines without adding costly track infrastructure. Though operating trains at shorter headways can theoretically increase line capacity, effectively controlling following trains becomes more difficult compared with a fixed-block system, requiring a fast-reacting train crew or control algorithm that effectively minimizes headway and fuel consumption while attenuating all fluctuations in lead-train speed. Otherwise, rapid changes in throttle and brake settings may be required, reducing following-train fuel efficiency, generating in-train forces, and diminishing the expected capacity gains from shortened headways. This research, sponsored by the Federal Railroad Administration, aims to better understand how closely following freight trains respond to different throttle- and brake-control algorithms. Using insights from connected automobile and truck platooning technology, the project team developed several train-following control algorithms, analyzed their stability, and simulated their performance with fleets of freight trains subject to different speed profiles. While moving-block systems do require additional train spacing beyond the minimum safe braking distance to account for train control actions, effective train-following control algorithms can minimize this distance. Also, the developed control laws exhibit a trade-off between minimizing train headway and fuel consumption, potentially allowing railway operators to choose an optimal balance.

Problems, assumptions and solutions in locomotive design, traction and operational studies

Locomotive design is a highly complex task that requires the use of systems engineering that depends upon knowledge from a range of disciplines and is strongly oriented on how to design and manage complex systems that operate under a wide range of different train operational conditions on various types of tracks. Considering that field investigation programs for locomotive operational scenarios involve high costs and cause disruption of train operations on real railway networks and given recent developments in the rollingstock compliance standards in Australia and overseas that allow the assessment of some aspects of rail vehicle behaviour through computer simulations, a great number of multidisciplinary research studies have been performed and these can contribute to further improvement of a locomotive design technique by increasing the amount of computer-based studies. This paper was focused on the presentation of the all-important key components required for locomotive studies, starting from developing a realistic locomotive design model, its validation and further applications for train studies. The integration of all engineering disciplines is achieved by means of advanced simulation approaches that can incorporate existing AC and DC locomotive designs, hybrid locomotive designs, full locomotive traction system models, rail friction processes, the application of simplified and exact wheel-rail contact theories, wheel-rail wear and rolling contact fatigue, train dynamic behaviour and in-train forces, comprehensive track infrastructure details, and the use of co-simulation and parallel computing. The co-simulation and parallel computing approaches that have been implemented on Central Queensland University’s High-Performance Computing cluster for locomotive studies will be presented. The confidence in these approaches is based on specific validation procedures that include a locomotive model acceptance procedure and field test data. The problems and limitations presented in locomotive traction studies in the way they are conducted at the present time are summarised and discussed.

Running safety analysis of a freight train passing through a single crossover during braking

In addition to the discontinuity of the rail profile of a normal turnout, the unique S-shaped curve of a crossover significantly affects the negotiation performance of a train. For heavy-haul freight trains, the in-train forces generated during the braking process may further deteriorate the running safety. Investigating the dynamic behaviour of the train passing through the crossover under braking forces, therefore, can provide a reasonable basis for ensuring train safety. This paper analyses the dynamic response and wheel wear of a three-vehicle train negotiating a single crossover under variable conditions, including variable braking forces, wheel-rail friction coefficient, and crossover layout forms. The results show that the three factors have considerable influences on train safety. If one of the three factors keeps an ideal level, the safe probability of empty wagons can be significantly improved. Considering that there are still some crossovers with tight curves in the existing railway system, avoiding large braking or lubricating the wheel flange in the crossover is still an effective solution to improve the vehicle's performance. In addition, for a new single crossover, a 600-m-radius curve is a good option for balancing permissible train speeds and construction costs of the crossover.

Hill-starting a heavy haul train with a 24-axle locomotive

Head-end trains are more efficient than Distributed Power trains in terms of train marshalling. This paper studied an unprecedent real-world engineering problem to hill-start a long heavy haul train at a 1.2% up-hill gradient by using a 14400 kW 24-axle AC electric locomotive (maximum traction force 2280 kN). Longitudinal Train Dynamics simulation were conducted to assess five potential driving strategies in terms of train speed and in-train forces. The simulation results show that the locomotive can hill-start the heavy haul train with 80% traction throttle. However, maximum locomotive coupler forces (1840 kN) exceeded coupler knuckle yield strength (1780 kN) of the original coupler system design. Sensitivity analyses were conducted to assess the implications of train starting resistance for train speeds and in-train forces. The study recommends increasing coupler knuckle yield strength to 2450 kN. The increased knuckle yield strength is still lower than that of the chassis, which is able to meet system design requirement; it also enables the locomotive to hill-start by using traction throttles of 80, 90, and 100% with safety factors of 1.3, 1.2 and 1.1 respectively.

The influence of resistant force equations and coupling system on long train dynamics simulations

In the simulation of the longitudinal dynamics of long trains, the modeling of the resistant forces and of the coupling system are two essential aspects. The modeling of the resistant forces directly affects the speed reached by each vehicle as well as the in-train forces. A literature review witnesses different laws for the calculation of both ordinary and accidental resistances. One of the objectives of this paper is to evaluate from the numerical point of view the influence of the resistant forces modeling strategy on the simulation outputs, i.e., on the speeds and in-train forces, by comparing different laws for propulsion and curving resistances. For what concerns the connection between the vehicles of the train, it is well known that the connection system is of utmost importance for the safety and running stability of the train. In this paper, the two existing coupling systems, i.e., the European buffer-hook system and the coupler used outside the European continent are first described, both in terms of operation and modelling techniques, and then they are compared on the same simulation scenario. All the simulations are performed on the first scenario of the International benchmark of the longitudinal train dynamic simulators, using the LTDPoliTO code developed by the railway research team from Politecnico di Torino.

Experimental assessment of the dynamic performance of slave control locomotive couplers in 20,000-tonne heavy-haul trains

Coupler jack-knifing and derailment of slave control locomotives in 20,000-tonne heavy-haul trains usually occur due to the combinations of large in-train forces with poor track conditions. This paper presents an experimental investigation on the dynamic performance of slave control locomotive couplers in 20,000-tonne heavy-haul trains. A field test method for measuring and monitoring the dynamic behavior of heavy-haul locomotive couplers is proposed. The on-track tests involved coupler forces, coupler yaw angles, and coupler dynamic motion monitoring of the test locomotive in the whole traveling process. The dynamic process of coupler jack-knifing is exhibited, and the distribution characteristics of the coupler forces and yaw angles are investigated. The test results indicate that the front and rear couplers of the slave locomotive group respectively suffer the largest draw (tensile) and buffing (compressive) forces, and the maximum yaw angle appears at the middle coupler between the slave locomotives. The maximum draw and buffing forces attain 1551 kN and 2067 kN, respectively. The maximum absolute yaw angle is about 13 degrees. During the cycle braking operation conditions, the intense buffing forces and the excessive coupler yaw angles are more likely to appear in the release process. The coupler instability generally occurs under train run in buffing forces. Moreover, the coupler status, the track conditions as well as the duration of buffing forces are also supposed to have an important effect on the coupler stability of slave control locomotives.

Design of sliding mode observer for the estimation of train car positions and in-train forces

Abstract For the control design of freight trains, the estimation of in-train forces is crucial to avoid safety issues caused by the possible failure of car couplers under excessive stress. However, the in-train forces and the relative positions of adjacent train cars are not directly measurable. To address this issue, this paper designs estimators of train car positions and in-train forces using only locomotive-based measurements. Using the multi-point train model, a cascade structure of robust sliding mode differentiators is developed. It provides finite-time estimation of train car positions and in-train forces. Simulation results illustrate the feasibility of the proposed approach.

Development and validation of a new code for longitudinal train dynamics simulation

Longitudinal train dynamics have a significant impact on both safety and performance of railway systems. Numerical simulation of long heavy haul trains can thus provide essential information for the development of diagnostic and signaling systems as well as coupling elements and braking systems. Long trains are usually modeled by considering only the longitudinal degree of freedom and by adding extra resistant forces to represent the track curvature and gradients. The prediction of in-train forces represents the most critical aspect in modeling the longitudinal dynamics of long trains made up of several vehicles. In fact, coupling elements have non-linear force–deflection characteristics, with different behavior in loading and unloading states, thus featuring a hysteretic loop. Look-up tables storing data from experimental tests are generally used to model these elements; however, other strategies, such as fitting curves and white-box models are witnessed in the literature. Recently, an international benchmarking of longitudinal train dynamics simulator was established in order to compare the output results obtained by different models with the same input data. The research group from Politecnico di Torino performed the simulations using the multibody software Simpack, but computational inefficiencies and numerical divergences occurred. To overcome these issues, a new dedicated in-house code was developed in the MATLAB environment. The paper focuses on the description of this new code and its validation, which was carried out by performing the simulations according to the benchmark inputs and comparing the results with the outputs from the other participants.

Latin hypercube designs based on strong orthogonal arrays and Kriging modelling to improve the payload distribution of trains

ABSTRACT Nowadays, computer experiments are used increasingly more to solve complex engineering and technological issues. Computer experiments are analysed through suitable metamodels acting as statistical interpolators of the simulated input-output data: Kriging is the most appropriate and widely used one. We optimise the braking performance of freight trains through computer experiments and Kriging modelling by focussing on the payload distribution along the train, so as to reduce the effects of in-train forces among wagons during a train emergency braking. One contribution of this manuscript is that to improve the freight train efficiency in terms of braking performance, we consider that the train is composed of several train sections with each one characterised by its own overall payload. A suitable Latin hypercube design is planned for the computer experiment that achieves excellent space-filling properties with a relatively low number of experimental runs. Kriging models with anisotropic covariance function are subsequently applied to assess which is the best payload distribution capable of reducting the in-train forces according to the specific train-set arrangement considered. The results are very satisfactory and confirm that our approach represents a valid method to be successfully applied by interested Railway Undertakings.

An integrated numerical framework to investigate the running safety of overlong freight trains

Long freight trains up to 1500 m in length are currently not in regular operation in Europe. One of the important reasons for the same is high inter-wagon forces generated during the operation, especially when pneumatic (P-type) brake systems are used. For long trains with multiple locomotives at different positions along the train, radio communication with necessary fail-safe mechanisms can be used to apply the brakes. Long freight train operation on a given line is subjected to various attributes such as braking/traction scenarios, loading patterns, wagon geometries, brake-block materials, buffer types, track design geometries, etc., which are referred to as heterogeneities. The complex longitudinal train dynamics arising in the train due to various heterogeneities play a major role in determining its running safety. In this context, the maximum in-train force refers to the maximum force developed between any two wagons along the train during operation. The tolerable longitudinal compressive force is the maximum compressive force that can be exerted on a wagon without resulting in its derailment. Here, the authors adopt a bottom-up approach to model pneumatic braking systems and inter-wagon interactions in multibody simulation environments to study the complex longitudinal train dynamics behavior and estimate maximum in-train forces and tolerable longitudinal compressive forces, subjected to various heterogeneities. These two force quantities intend to facilitate a given freight train operation by providing guidelines regarding the critical heterogeneities, that currently limit its safe operation. In doing so, the authors propose the notion to have an operation-based approval for long freight trains using the simulations-based tool.

Simulation and time-frequency analysis of the longitudinal train dynamics coupled with a nonlinear friction draft gear

AbstractTrain safety and operational efficiency can be improved by investigating the dynamics of the train under varying conditions. Longitudinal train dynamics (LTD) simulations performed for such purposes, usually by utilising a nonlinear time-domain model. This paper covers two modes of LTD results corresponding to the time domain and frequency domain analysis. Time-domain solutions are essential to evaluate the full response used for parameter optimisation and controller design studies while frequency domain solutions can provide significant but straightforward clues regarding system dynamics. An advanced draft gear model, which works under a four-stage process is constructed considering all structural components, geometric relationships, friction modelling and dynamic characteristics such as hysteresis, stiffening, state transition, locked unloading, softening. Then, this model is parametrically reduced and implemented into an LTD simulation. The simulation in the time domain is conducted assuming a locomotive connected with a nine wagon via “ode3” fixed-step solver. The transfer function among the first wagon acceleration (output) and the locomotive force (input) estimated through system identification methodology. Then, the identification results interpreted by investigating step-response characteristic and best response giving parameter set is selected. Next, the modal and spectral analysis performed to reveal the behaviour of the in-train forces and the effects of vibration. This paper discusses a reliable methodology for the longitudinal dynamic analysis of the multi-bodied train in time and frequency domain and clarifies in-train vibration behaviour under the existence of sophisticated draft gear.

Optimizing strain energy extraction from multi-beam piezoelectric devices for heavy haul freight cars

Heavy haul trains used to transport commodities are generally very long and operated by a single individual. Owing to high noise levels from the rolling stock displacement, the driver cannot notice failures in the compartments. It is practically impossible to visually inspect the wagons located far from the locomotive. Sensors that can measure in-train forces may improve the train’s operation, indicating potential failures and preventing accidents and derailments. However, the freight cars employed in most of the railroads are not equipped with electric power sources, making inspections unlikely. Therefore, an energy harvesting system must be developed for the sensors to avoid the need for periodic battery charging or replacement. As a high level of kinetic energy is present in the rolling stock, a vibration energy harvester (VEH) system is an acceptable alternative. Among VEH devices, multi-beam piezoelectric materials used in planar zigzag (PZ) or orthogonal spiral outer fixed (OSo) configurations can be effective alternatives. These can be powered by low-frequency strains readily available in the freight cars. This study investigates the optimum geometries of PZ and OSo aiming to increase the generated power and minimize the structure mass with a focus on their application to ore wagons. Among the optimum solutions, the OSo geometry generates the maximum power, up to 20.93 mW, which is sufficient to feed some critical devices. Conversely, the PZ configurations present the highest energy density, up to 16.595 mW/kg(m s−2)2, which allows for a more suitable solution to be combined in serial and/or parallel pack configurations.