Validation of vehicle dynamics simulation models – a review

In this work, a literature survey on the validation of vehicle dynamics simulation models is presented. Estimating the dynamic responses of existing or proposed vehicles has a wide array of applications in the development of vehicle technologies, e.g. active suspensions, controller design, driver assistance systems, etc. Although simulation environments, measurement tools and mathematical theories on vehicle dynamics are well established, the methodical link between the experimental test data and validity analysis of the simulation model is still lacking. This report presents different views on the definition of validation, and its usage in vehicle dynamics simulation models.     

Comparison of wheel-rail contact codes for railway vehicle simulation: an introduction to the Manchester Contact Benchmark and initial results

A new benchmark is being undertaken to assess the impact of wheel-rail contact modelling assumptions on the simulation of railway vehicle dynamics. The benchmark is split into two distinct simulation cases: the first, Case A, using a single wheelset to pinpoint the differences between the contact models and the second, Case B, using a simplified railway vehicle to assess the effect of the different contact models on the simulation of vehicle behaviour. After an open discussion of the Case A specification, the initial call for contributions was made in November 2006. The discussion of simulation Case B specifications was opened in April 2007 and to date is ongoing. This paper briefly introduces the new Manchester Contact Benchmark and presents some of the initial findings from simulation Case A.     

Pareto optimisation of railway bogie suspension damping to enhance safety and comfort

This paper presents the optimisation of damping characteristics in bogie suspensions using a multi-objective optimisation methodology. The damping is investigated and optimised in terms of the resulting performances of a railway vehicle with respect to safety, comfort and wear considerations. A complete multi-body system model describing the railway vehicle dynamics is implemented in commercial software Gensys and used in the optimisation. In complementary optimisation analyses, a reduced and linearised model describing the bogie system dynamics is also utilised. Pareto fronts with respect to safety, comfort and wear objectives are obtained, showing the trade-off behaviour between the objectives. Such trade-off curves are of importance, especially in the design of damping functional components. The results demonstrate that the developed methodology can successfully be used for multi-objective investigations of a railway vehicle within models of different levels of complexity. By introducing optimised passive damping elements in the bogie suspensions, both safety and comfort are improved. In particular, it is noted that the use of optimised passive damping elements can allow for higher train speeds. Finally, adaptive strategies for switching damping parameters with respect to different ride conditions are outlined and discussed.     

Railway vehicle performance optimisation using virtual homologation

Unlike regular automotive vehicles, which are designed to travel in different types of roads, railway vehicles travel mostly in the same route during their life cycle. To accept the operation of a railway vehicle in a particular network, a homologation process is required according to local standard regulations. In Europe, the standards EN 14363 and UIC 518, which are used for railway vehicle acceptance, require on-track tests and/or numerical simulations. An important advantage of using virtual homologation is the reduction of the high costs associated with on-track tests by studying the railway vehicle performance in different operation conditions. This work proposes a methodology for the improvement of railway vehicle design with the objective of its operation in selected railway tracks by using optimisation. The analyses required for the vehicle improvement are performed under control of the optimisation method global and local optimisation using direct search. To quantify the performance of the vehicle, a new objective function is proposed, which includes: a Dynamic Performance Index, defined as a weighted sum of the indices obtained from the virtual homologation process; the non-compensated acceleration, which is related to the operational velocity; and a penalty associated with cases where the vehicle presents an unacceptable dynamic behaviour according to the standards. Thus, the optimisation process intends not only to improve the quality of the vehicle in terms of running safety and ride quality, but also to increase the vehicle availability via the reduction of the time for a journey while ensuring its operational acceptance under the standards. The design variables include the suspension characteristics and the operational velocity of the vehicle, which are allowed to vary in an acceptable range of variation. The results of the optimisation lead to a global minimum of the objective function in which the suspensions characteristics of the vehicle are optimal for the track, the maximum operational velocity is increased while the safety and ride quality measures of the vehicle, as defined by homologation standards, are either maintained in acceptable values or improved.     

Black-box modelling of nonlinear railway vehicle dynamics for track geometry assessment using neural networks

ABSTRACT

The use of vehicle dynamics simulation for the track geometry assessment gives rise to new demands. In order to analyse the responses of the vehicles to the measured track geometry defects, the integration of the simulation process in the measurement chain of the track geometry recording car is envisaged. Fast and reliable simulation results are required. This work studies the use of black-box modelling approaches as an alternative to multi-body simulation. The performances of different linear and nonlinear black-box models for the simulation of the vertical and lateral bogie accelerations are compared. While linear transfer function models give good results for the simulation of the vertical responses, their use is not suitable for the highly nonlinear lateral vehicle dynamics. The lateral accelerations are best represented by recurrent neural networks. For the training and validation on high-speed lines using measured vehicle responses, the performance of the black-box simulation outperforms the multi-body simulation. Due to the larger variability of track design and track quality conditions on conventional lines, the model performance degrades and depends significantly on the analysed vehicle type and the track characteristics.     

Influence of wheel–rail contact modelling on vehicle dynamic simulation

This paper presents a comparison of four models of rolling contact used for online contact force evaluation in rail vehicle dynamics. Until now only a few wheel–rail contact models have been used for online simulation in multibody software (MBS). Many more models exist and their behaviour has been studied offline, but a comparative study of the mutual influence between the calculation of the creep forces and the simulated vehicle dynamics seems to be missing. Such a comparison would help researchers with the assessment of accuracy and calculation time. The contact methods investigated in this paper are FASTSIM, Linder, Kik–Piotrowski and Stripes. They are compared through a coupling between an MBS for the vehicle simulation and Matlab for the contact models. This way the influence of the creep force calculation on the vehicle simulation is investigated. More specifically this study focuses on the influence of the contact model on the simulation of the hunting motion and on the curving behaviour.     

Modelling the Contact Between Wheel and Rail Within Multibody System Simulation

In modern railway industry the simulation of the behaviour of railway vehicles has become an important design method during the last years. Modern simulation packages offer modelling elements that are highly adapted for standard and unusual simulation scenarios. A specific application case is the simulation of a railway vehicle travelling through a switch. It makes high demands on the simulation software due to the inconvenient modelling elements needed: the changing rail profiles on the blade rail and in the crossing vee area as well as the guard rail with its additional contact at the back of the wheel. The article gives an overview over the state of the art in railway vehicle simulation and presents a simulation of a passenger car running through a switch as an application example.     

Modelling the Contact Between Wheel and Rail Within Multibody System Simulation

In modern railway industry the simulation of the behaviour of railway vehicles has become an important design method during the last years. Modern simulation packages offer modelling elements that are highly adapted for standard and unusual simulation scenarios. A specific application case is the simulation of a railway vehicle travelling through a switch. It makes high demands on the simulation software due to the inconvenient modelling elements needed: the changing rail profiles on the blade rail and in the crossing vee area as well as the guard rail with its additional contact at the back of the wheel. The article gives an overview over the state of the art in railway vehicle simulation and presents a simulation of a passenger car running through a switch as an application example.     

Validation of railway vehicle dynamic models in training simulators

Training simulators play an important role for sustaining safety, efficiency and cost effective railway transportation. Dynamic modelling of train systems is one of the main modules of training simulators. Validation of the dynamic models with collected real data ensures the fidelity of the simulator utilising the respective models. In this study, a validation process (Dynamic Modelling Validation Process (DyMVaP)) which is developed to support the validation of railway dynamic models is introduced. However, the proposed process can also be used in validating other dynamic models as well. The developed process is based on five steps including the preparation of validation scenarios, sensor deployment, real data collection, data preparation, and comparison of simulated and measured data. Note that the proposed DyMVaP was used for the validation of a full-mission training simulator so called TRENSIM, which was developed for Turkish State Railways. During the study it is realised that the current speed, travelled distance, acceleration (in x, y, z directions), rotation angles (around x, y, z axes), air pressure, in-train pressure/tension forces, traction motor currents, catenary voltage, positions of controllers must be collected synchronously by using proper sensors in order to ensure simulation validation. The required data was collected from locomotive body, bogies, wheel sets and connection of railway cars. The data (～200?GB) collected from the field by applying 27 different scenarios and transformed into appropriate data for utilising the generated dynamic models within the simulator. The measured and simulated data were also compared visually using graphical representation of the parameters as well as performing computations regarding the magnitude, phase and comprehensive error factors.     

A railway vehicle multibody model for real-time applications

Hardware in the loop (HIL) techniques are widely used for fast prototyping of control systems, electronic and mechatronic devices. In the railway field, several mechatronic on board subsystems are often tested and calibrated following the HIL approach. The accuracy of HIL tests depends on how the simulated virtual environment approximates the physical conditions. As the computational power available on real-time hardware grows, the demand for more complex and realistic models of railway vehicles for real-time application increases. In past research activities, the authors worked on the implementation of simplified real-time models for several applications and in particular for an HIL test rig devoted to the type approval of wheel slide protection systems. The activity has then been focused on the development of a three-dimensional model of the dynamics of a railway vehicle for more complex applications. The paper summarises the features and the results of the study.     

Dynamics of railway freight vehicles

This paper summarises the historical development of railway freight vehicles and how vehicle designers have tackled the difficult challenges of producing running gear which can accommodate the very high tare to laden mass of typical freight wagons whilst maintaining stable running at the maximum required speed and good curving performance. The most common current freight bogies are described in detail and recent improvements in techniques used to simulate the dynamic behaviour of railway vehicles are summarised and examples of how these have been used to improve freight vehicle dynamic behaviour are included. A number of recent developments and innovative components and sub systems are outlined and finally two new developments are presented in more detail: the LEILA bogie and the SUSTRAIL bogie.     

Dynamic vehicle–track interaction in switches and crossings and the influence of rail pad stiffness – field measurements and validation of a simulation model

A model for simulation of dynamic interaction between a railway vehicle and a turnout (switch and crossing, S&C) is validated versus field measurements. In particular, the implementation and accuracy of viscously damped track models with different complexities are assessed. The validation data come from full-scale field measurements of dynamic track stiffness and wheel–rail contact forces in a demonstrator turnout that was installed as part of the INNOTRACK project with funding from the European Union Sixth Framework Programme. Vertical track stiffness at nominal wheel loads, in the frequency range up to 20?Hz, was measured using a rolling stiffness measurement vehicle (RSMV). Vertical and lateral wheel–rail contact forces were measured by an instrumented wheel set mounted in a freight car featuring Y25 bogies. The measurements were performed for traffic in both the through and diverging routes, and in the facing and trailing moves. The full set of test runs was repeated with different types of rail pad to investigate the influence of rail pad stiffness on track stiffness and contact forces. It is concluded that impact loads on the crossing can be reduced by using more resilient rail pads. To allow for vehicle dynamics simulations at low computational cost, the track models are discretised space-variant mass–spring–damper models that are moving with each wheel set of the vehicle model. Acceptable agreement between simulated and measured vertical contact forces at the crossing can be obtained when the standard GENSYS track model is extended with one ballast/subgrade mass under each rail. This model can be tuned to capture the large phase delay in dynamic track stiffness at low frequencies, as measured by the RSMV, while remaining sufficiently resilient at higher frequencies.     

Application of Elementary Neural Networks and Preview Sensors for Representing Driver Steering Control Behaviour

This paper demonstrates the use of elementary neural networks for modelling and representing driver steering behaviour in path regulation control tasks. Areas of application include uses by vehicle simulation experts who need to model and represent specific instances of driver steering control behaviour, potential on-board vehicle technologies aimed at representing and tracking driver steering control behaviour over time, and use by human factors specialists interested in representing or classifying specific families of driver steering behaviour. Example applications are shown for data obtained from a driver/vehicle numerical simulation, a basic driving simulator, and an experimental on-road test vehicle equipped with a camera and sensor processing system.     

Vehicle response-based track geometry assessment using multi-body simulation

The assessment of the geometry of railway tracks is an indispensable requirement for safe rail traffic. Defects which represent a risk for the safety of the train have to be identified and the necessary measures taken. According to current standards, amplitude thresholds are applied to the track geometry parameters measured by recording cars. This geometry-based assessment has proved its value but suffers from the low correlation between the geometry parameters and the vehicle reactions. Experience shows that some defects leading to critical vehicle reactions are underestimated by this approach. The use of vehicle responses in the track geometry assessment process allows identifying critical defects and improving the maintenance operations. This work presents a vehicle response-based assessment method using multi-body simulation. The choice of the relevant operation conditions and the estimation of the simulation uncertainty are outlined. The defects are identified from exceedances of track geometry and vehicle response parameters. They are then classified using clustering methods and the correlation with vehicle response is analysed. The use of vehicle responses allows the detection of critical defects which are not identified from geometry parameters.     

Improved calibration of simulation models in railway dynamics: application of a parameter identification process to the multi-body model of a TGV train

This paper aims at estimating the vehicle suspension parameters of a TGV (Train à Grande Vitesse) train from measurement data. A better knowledge of these parameters is required for virtual certification or condition monitoring applications. The estimation of the parameter values is performed by minimising a misfit function describing the distance between the measured and the simulated vehicle response. Due to the unsteady excitation from the real track irregularities and nonlinear effects in the vehicle behaviour, the misfit function is defined in the time domain using a least squares estimation. Then an optimisation algorithm is applied in order to find the best parameter values within the defined constraints. The complexity of the solution surface with many local minima requires the use of global optimisation methods. The results show that the model can be improved by this approach providing a response of the simulation model closer to the measurements.     

Numerical Model of a Tilting Body Railway Vehicle Compared With Rig and on Track Tests

The aim of the paper is to describe and verify a numerical model for the simulation of the dynamic behaviour of a tilting body railway vehicle, with particular attention to the curve negotiation conditions. In the model the dynamics of the tilting active control devices are reproduced, combining the numerical mechanical model of the vehicle with the control software used on the real vehicle. In order to validate the numerical simulation model, numerical results and experimental ones, from both a test rig and out-door tests, were compared.     

Numerical Model of a Tilting Body Railway Vehicle Compared With Rig and on Track Tests

The aim of the paper is to describe and verify a numerical model for the simulation of the dynamic behaviour of a tilting body railway vehicle, with particular attention to the curve negotiation conditions. In the model the dynamics of the tilting active control devices are reproduced, combining the numerical mechanical model of the vehicle with the control software used on the real vehicle. In order to validate the numerical simulation model, numerical results and experimental ones, from both a test rig and out-door tests, were compared.     

Fundamentals of vehicle–track coupled dynamics

This paper presents a framework to investigate the dynamics of overall vehicle–track systems with emphasis on theoretical modelling, numerical simulation and experimental validation. A three-dimensional vehicle–track coupled dynamics model is developed in which a typical railway passenger vehicle is modelled as a 35-degree-of-freedom multi-body system. A traditional ballasted track is modelled as two parallel continuous beams supported by a discrete-elastic foundation of three layers with sleepers and ballasts included. The non-ballasted slab track is modelled as two parallel continuous beams supported by a series of elastic rectangle plates on a viscoelastic foundation. The vehicle subsystem and the track subsystem are coupled through a wheel–rail spatial coupling model that considers rail vibrations in vertical, lateral and torsional directions. Random track irregularities expressed by track spectra are considered as system excitations by means of a time–frequency transformation technique. A fast explicit integration method is applied to solve the large nonlinear equations of motion of the system in the time domain. A computer program named TTISIM is developed to predict the vertical and lateral dynamic responses of the vehicle–track coupled system. The theoretical model is validated by full-scale field experiments, including the speed-up test on the Beijing–Qinhuangdao line and the high-speed running test on the Qinhuangdao–Shenyang line. Differences in the dynamic responses analysed by the vehicle–track coupled dynamics and by the classical vehicle dynamics are ascertained in the case of vehicles passing through curved tracks.