Active secondary yaw control to improve curving behaviour of a railway vehicle

Active primary / secondary suspensions have been proposed as a means to solve the trade-off between curving and stability which represents a key problem in the design of modern railway vehicles. In particular, one concept proposed for active control of the vehicle’s running behaviour is known as Secondary Yaw Control (SYC) and consists of applying a controllable yaw torque between the carbody and the two bogies. This concept has been studied in the past mainly to enhance the vehicle’s curving ability. This paper extends the idea by examining the implications of designing a bogie with soft yaw stiffness between the bogie frame and the wheelsets and using SYC to provide active stabilisation. To this aim, a state feedback control law is designed according to the LQR and LQG techniques. The paper presents the general concept of active suspension control investigated and the control strategies applied. Then the effectiveness of the proposed actuation concept is investigated by means of numerical simulations performed on mathematical models of the passive and actively controlled vehicles implemented in a fully nonlinear multi-body simulator. Comparisons are performed and benefits assessed between the actively controlled vehicle and the passive one in terms of: non-linear stability in straight track running; and safety and wear in curves

Numerical Estimation of Stresses in Railway Axles Using a Train-Track Interaction Model

The fatigue design of railway axles requires that the stresses arising in the axle in real service are accurately quantified. This paper describes a method to compute the dynamic stresses arising in railway axles as the effect of train track interaction, based on the numerical simulation of the dynamic interaction between a flexible wheelset and a flexible track. The wheelset is modelled as a flexible rotating body using an Eulerian approach, whereas track is regarded as an infinite periodic system with the rail modelled as a Timoshenko beam resting on discrete elastic supports, considering the inertia associated with the sleepers. The paper presents an application of the proposed procedure to the calculation of the dynamic stresses caused in the axle by different types of geometric imperfection occurring on the wheel and rail surfaces, considering the cases of a single harmonic rail corrugation, random rail roughness and a wheelflat.The authors gratefully acknowledge the support for this work provided by the Project TRA2010-15669 (Ministerio de Ciencia e Innovacion) and TRA2007-67167 (Ministerio de Educacion y Ciencia-FEDER).Martínez Casas, J.; Mazzola, L.; Baeza González, LM.; Bruni, S. (2013). Numerical Estimation of Stresses in Railway Axles Using a Train-Track Interaction Model. International Journal of Fatigue. 47:18-30. https://doi.org/10.1016/j.ijfatigue.2012.07.006S18304

Early Instability Detection for High Speed Railway Bogies

In this paper a method is proposed to monitor the degradation of the performances of a railway bogie and to detect the incipient instability of the vehicle well in advance the limit values of the lateral acceleration are reached. The same condition based monitoring technique can also be used to detect the presence of faults in some bogie components critical to vehicle stability, and to resolve between different fault types (e.g. wear of the wheel profile, reduction of anti yaw damper characteristic, degradation of the primary suspension parameters). The method is based on the analysis of the lateral accelerations of the bogie frame using the random decrement technique (RTD) to extract the free response of the bogie. The output of the RTD algorithm is then analysed in time domain using the Prony method to identify the characteristic exponent of the systems, eventually allowing to define the stability margin of the bogie together with other characteristic parameters such as bogie natural frequencies and the y/ ratio between the lateral and yaw components of its mode shape. The trend with time of these parameters is used to monitor the degradation of bogie performance, and the results can be used to drive preventive maintenance actions

An efficient condition monitoring strategy of railway vehicle suspension based on recursive least-square algorithm

This paper presents a model-based strategy for condition monitoring of suspensions in a railway bogie. This approach is based on recursive least-square (RLS) algorithm focusing on the ‘Input-output’ model. RLS is able to identify the unknown parameters from a noisy input-output system by memorizing the correlation properties. The identification of the suspension parameter is achieved by establishing the relationship between the excitation and response of a bogie. A fault detection method for vertical primary suspensions of one bogie is illustrated as an example of this scheme. Numerical simulation results from the rail vehicle dynamics software ‘ADTreS’ are utilized as ‘virtual measurements’, considering a trailed car of Italian ETR500 high-speed train. The test data from an E464 locomotive are also employed to validate the feasibility of this strategy for the real situation. Results of the parameter identification performed indicate that estimated suspension parameters are consistent or approximate with the values for reference, thereby supporting the application of this fault diagnosis technique to the future condition monitoring system of the rail vehicle suspensio

Effect of motor connection on the critical speed of high speed railway vehicles

Considering the specific case of a concentrated power locomotive with motors mounted on the bogie frame, the paper reviews the criteria for nonlinear assessment of vehicle stability based on the simulation of vehicle response to random track irregularity, showing the need for more objective criteria than the ones based on physical testing for vehicle homologation. The effect of elastic motor connection on the bogie frame is examined by linear and nonlinear calculations, which shows that stiffness and damping properties of motor connection have a strong influence on vehicle stability

An application of kalman filtering estimation to the condition monitoring of the geometric quality of the railway track

In this paper, an application of the treatment of dynamic datasets of a railway vehicle, as previously described by the same authors in Reference [1], is presented. In the preceding work, the proposed track condition monitoring system was designed to be implemented on board of train being operated in standard revenue service. Through the use of Kalman filter state estimator it was possible to replace some direct measures with their estimation. This paper provides a more comprehensive framework for the study, by investigating the observability of the system. Moreover, the proposed methodology, previously validated exploiting a multi-body simulator, is herein applied to real data collected during measurements campaign on Italian railway network

Evaluation of the hunting behaviour of a railway vehicle in a curve

Experimental evidence, as obtained from line tests, shows that, under some circumstances, the level of hunting motion experienced by a railway vehicle negotiating a curve can be higher than for the same vehicle running at the same speed on tangent track. Starting from this experimental observation, this paper aims to propose a physical explanation for the different hunting behaviour of a railway vehicle running in a curve. After presenting the available experimental evidence, a qualitative examination of the phenomenon is provided. A multi-body model of the vehicle running in a curve is defined and validated against line measurements. This model is then used to numerically evaluate the hunting behaviour of the vehicle in a wide range of curve radii relevant for high-speed lines. In this way, the experimental findings are extended to curve radius and cant deficiency values that were not observed in line tests, due to the use of a specific track section and to the range of speeds covered by the tests

Treatment of driving dynamic datasets of a railway vehicle aimed at condition monitoring of the track

In this paper, a proposal for the treatment of driving dynamic datasets of a railway vehicle is outlined which is aimed at the development of a track condition monitoring system that can be implemented on board of trains being operated in standard revenue service. Compared to monitoring systems installed in special diagnostic trains this concept enables a reduction in the number of sensors used, to meet stringent constraint in terms of space available for the transducers, wirings and power supply. To this aim, use is made of a Kalman-filter state estimator replacing the direct measure of vehicle dynamics at some meaningful locations in the vehicle. A performance index is defined to summarize the performance of the diagnostic unit. The proposed approach is validated using multi-body simulation

Condition monitoring of rail vehicle suspension based on recursive least-square algorithm

This paper presents a model-based method for condition monitoring of suspensions in a railway bogie. This approach is based on recursive least-square (RLS) algorithm focusing on the ‘Input-output’ model instead of the ‘State Space’ model. RLS estimates the unknown parameters from an input-output system by memorizing its correlation properties. The identification of the suspension parameter is achieved by establishing the relationship between the excitation and response of a bogie. A fault detection method for vertical primary dampers of one bogie is illustrated as an example of this scheme. Numerical simulation results from the rail vehicle dynamics software ‘ADTreS’ are utilized as ‘virtual measurements’, considering a trailed car of Italian ETR500 high-speed train. Results of the parameter identification performed on the virtual measurements indicate that estimated suspension parameters are consistent with the values adopted in the numerical simulations, thereby supporting the application of this technique for the fault detection and isolation to real cases