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Railway switches and crossings constitute a small fraction of linear track length but consume a large proportion of the railway track system maintenance budget. While switch and crossing (S&C) faults rarely prevent trains from running, switches and crossings are the source of many faults and need continual attention. On the rare occasions when trains are prevented from running the cost of the disruption is very high. Condition monitoring of the point operating equipment that moves the switchblades has been in use for many years but condition monitoring of the state of the switch in terms of the support and mechanical damage as trains pass over has only recently started to become possible. To this end, it is important to understand the correlation between S&C faults and sensor data that can detect those faults. This paper assesses some of the data collected from multiple sensors variously positioned on and around a switch and crossing on the UK mainline for a few days of normal train operation. Accelerometers, geophones, and strain gauges were installed at the locations where they were anticipated to be most useful. Forces at the load transfer point on the crossing nose were estimated from two separate strain gauge bridges and possible use of acceleration on the crossing is discussed. Correlations between different data are analysed and assessed and correlation between peak estimated load transfer forces and accelerations is presented. Based on the analysis, conclusions are drawn about the different types of dynamic information around S&Cs that can be obtained from a variety of sensor types.

In October 2018, Porterbrook and the University of Birmingham announced the HydroFLEX project, to demonstrate a hydrogen-hybrid modified train at Rail Live 2019. The concept of modifying a Class 319 Electric Multiple Unit was developed, with equipment including a fuel cell stack, traction battery, 24 V control system and hydrogen storage elements to be mounted inside one of the carriages. This was followed by procurement of a fuel cell stack, traction batteries, and control equipment, which was then installed inside the train, being fixed to the seat rails. One substantial change from the concept was the provision of considerably more hydrogen storage than the minimum necessary, providing the train with more potential to be further modified to allow for higher speed mainline testing. After the Rail Live exhibition where HydroFLEX was demonstrated, numerous modifications were performed to increase the reliability and power of the HydroFLEX train, primarily concerned with modifying the base train logic, with the aim of a successful mainline test. Supporting this effort was a multitude of documentation concerning safety, operations, and approvals to gain approvals from the relevant approvals bodies. The project demonstrated the feasibility of using hydrogen fuel cells as an autonomous fuel for railway propulsion systems, which has the potential for full decarbonisation.

In railways, using a track- and ride-quality monitoring system on in-service train has become desirable for coordination and security. Identification of the track- or train-related rough rides via ...

Defects in railway axle bearings can affect operational efficiency, or cause in-service failures, damaging the track and train. Healthy bearings produce a certain level of vibration and noise, but a bearing with a defect causes substantial changes in the vibration and noise levels. It is possible to detect the bearing defects at an early stage of their development, allowing an operator to repair the damage before it becomes serious. When a vehicle is scheduled for maintenance, or due for overhaul, knowledge of bearing damage and severity is beneficial, resulting in fewer operational problems and optimised fleet availability. This paper is a review of the state of the art in condition monitoring systems for rolling element bearings, especially the axlebox bearings. This includes exploring the sensing technologies, summarising the main signal processing methods and condition monitoring techniques, i.e. wayside and on-board. Examples of commercially available systems and outputs of current research work are presented. The effectiveness of the current monitoring technologies is assessed and the p– f curve is presented. It is concluded that the research and practical tests on axlebox bearing monitoring are limited compared to the generic bearing applications.

Railway pantographs are used around the world for collecting electrical energy to power railway vehicles from the overhead catenary. Faults in the pantograph system degrade the quality of the contact between the pantograph and catenary and reduce the reliability of railway operations. To maintain the pantographs in a good working condition, regular inspection tasks are carried out at rolling stock depots. The current pantograph inspections, in general, are only effective for the detection of major faults, providing limited incipient fault detection or fault diagnosis capabilities. Condition monitoring of pantographs has the potential to improve pantograph performance and reduce maintenance costs. As a first step in the realisation of practical pantograph condition monitoring, a laboratory-based pantograph test rig has been developed to gain an understanding of pantograph dynamic behaviours, particularly when incipient faults are present. In the first work of this kind, dynamic response data have been acquired from a number of pantographs that have allowed fault detection and diagnosis algorithms to be developed and verified. Three tests have been developed: (i) a hysteresis test that uses different excitation speeds, (ii) a frequency response test that uses different excitation frequencies, and (iii) a novel changing gradient test. Verification tests indicate that the hysteresis test is effective in detecting and diagnosing pneumatic actuator and elbow joint faults. The frequency response test is able to monitor the overall degradation in the pantograph. The changing gradient test provides fault detection and diagnosis in the pantograph head suspension and pneumatic actuator. The test rig and fault detection and diagnosis algorithms are now being developed into a depot-based prototype together with a number of industrial partners.

The inexorable increase in energy demand around the world has put the energy-saving technology in hot spot for railway transportation. Train speed trajectory optimization based on optimal control, coasting control, and collaborative control inside railway systems is a popular methodology to enhance energy efficiency. This paper studies a special and interesting problem, i.e., the partial train speed trajectory optimization problem, and proposes a complete mathematical model where a mixed-integer linear programming algorithm can be directly applied. During the transient operation process of a train, the speed of the train is often considered to be monotonically increasing and decreasing in normal conditions without extreme gradients. Given that, the proposed method can quickly locate the train speed profile under practical engineering constraints, and the objective function is either to maximize the regenerative braking energy or to minimize the traction energy. Such a method with a short computational time may become particularly interesting for online cases where a train is altering its speed in a fixed distance and time due to the operational requirement. The generated speed trajectory can be used to guide the train to control its speed or in a normal braking operation. The robustness and effectiveness of the method has been demonstrated through a number of detailed simulation results in this paper.

Train simulation software is conventionally validated by checking simulation results against equivalent data collected from real train runs. It is typically expected that these results will be within 5–10% accuracy of the recorded data. However, such a large margin could allow errors in the programming to be overlooked, resulting in an inaccurate model. This paper presents a method for error checking and validating the kinematics of train simulators based on comparison with calculated results, which are found by solving the fundamental equations governing train motion. A typical train run comprises of a combination of two or more of the four stages: accelerating, cruising, coasting and braking. Each stage is considered as a separate scenario for which the equations must be solved, in order to find the running time, distance travelled and energy consumption of the vehicle. This validation method is applied to two train movement simulators currently used for research. Certain specific scenarios for which analytical solutions are available are run in each simulator. The differences from the analytical solution in each test case are quantified, allowing the simulators to be compared to each other and the exact solution.

In order to reduce energy consumption on DC railways where regenerative braking is not available, train control strategy or ‘driver style’ is a practical alternative. In 2011, instrumentation to monitor energy consumption on the Merseyrail network was fitted to a British Rail Class 508 DC camshaft-operated electrical multiple unit. In this paper, seven services from Hunts Cross to Southport are highlighted to demonstrate a number of driver styles and their correlation with energy consumption. The differences in energy consumption were observed to be related to driver aggression in both the acceleration and deceleration phases.

This paper presents a view of the current state of monitoring track geometry condition from in-service vehicles. It considers technology used to provide condition monitoring; some issues of processing and the determination of location; how things have evolved over the past decade; and what is being, or could/should be done in future research. Monitoring railway track geometry from an in-service vehicle is an attractive proposition that has become a reality in the past decade. However, this is only the beginning. Seeing the same track over and over again provides an opportunity for observing track geometry degradation that can potentially be used to inform maintenance decisions. Furthermore, it is possible to extend the use of track condition information to identify if maintenance is effective, and to monitor the degradation of individual faults such as dipped joints. There are full unattended track geometry measurement systems running on in-service vehicles in the UK and elsewhere around the world, feedin...

Regenerative braking improves the energy efficiency of railway transportation by converting kinetic energy into electric energy. This paper proposes a method to apply the Bellman-Ford (BF) algorithm to search for the train braking speed trajectory to increase the total regenerative braking energy (RBE) in a blended braking mode with both electric and mechanical braking forces available. The BF algorithm is applied in a discretized train-state model. A typical suburban train has been modeled and studied under real engineering scenarios involving changing gradients, journey time, and speed limits. It is found that the searched braking speed trajectory is able to achieve a significant increase in the RBE, in comparison with the constant-braking-rate (CBR) method with only a minor difference in the total braking time. An RBE increment rate of 17.23% has been achieved. Verification of the proposed method using BF has been performed in a simplified scenario with zero gradient and without considering the constraints of braking time and speed limits. Linear programming (LP) is applied to search for a train trajectory with the maximum RBE and achieves solutions that can be used to verify the proposed method using BF. It is found that it is possible to achieve a near-optimal solution using BF and the solution can be further improved with a more complex search space. The proposed method takes advantage of robustness and simplicity of modeling in a complex engineering scenario, in which a number of nonlinear constraints are involved.

Electric railways collect power from the infrastructure via various current collection systems. For high-voltage AC- and DC-powered railways, this is usually achieved using overhead electrification equipment and a train-borne pantograph. The dynamics of such systems are well understood, and the systems are able to be operated under a range of conditions and speeds. Lower-voltage DC-powered railways ( This article presents some experimental results from a bogie-mounted instrumentation system designed to monitor a typical example of a shoegear assembly operated on the UK railway system. The results indicate that the shoegear broadly performs in accordance with the design guidelines. Several points of loss of contact were observed, and it is shown that the contact force between the conductor shoe and rail can be estimated. The mean force was found to vary with third rail height, but a wide distribution of forces is found at any one height because of hysteresis in the shoegear. Large, but short-term, forces and torques occur because of third rail irregularities and ramps.

Recent increases in railway patronage worldwide have created pressure on rolling stock and railway infrastructure through the demand to improve the capacity and punctuality of the whole system, and this demand must also be balanced with reducing life-cycle costs. Condition monitoring is seen as a significant contributor in achieving this. The emphasis of this article is on the use of sensors mounted on rolling stock to monitor the condition of infrastructure and the rolling stock itself. This is set in the context of modern rolling stock being fitted with high-capacity communication buses and multiple sensors, resulting in the potential for advanced processing of collected data. This article brings together linked research that uses a similar set of rolling stock sensors, and discusses: general usage and benefits, a track defect detection method, running gear condition monitoring, and absolute train speed detection.

This paper discusses the maintenance of accurate track alignment. The authors note that accurate track alignment is important in guaranteeing the smooth ride quality and safe passage of railroad vehicles, avoiding both flange contact and flange climb. To accurately measure horizontal track geometry, the authors use a full track geometry recording system comprised of mounted sensors on the bogie of an in-service vehicle. The system estimates the mean track alignment without using either optical or contact sensors. The authors observe that while either a yaw rate or bogie lateral acceleration, in principle, can be processed to estimate mean lateral track irregularity, a yaw rate gyro provides consistent estimates down to lower vehicle speeds. It is noted that yaw rate estimates are more efficient than those of an accelerometer, without needing to compensate for the effects of bogie roll. Also observed is the improved estimate obtained by inverting the dynamic relationship between the mean track alignment and the bogie yaw motion. The research demonstrates this with results from a Class 175 vehicle. The authors conclude that continual monitoring of the lateral response of a bogie on an in-service vehicle that uses only a yaw rate gyro can provide the data needed prioritize track maintenance operations.