This work presents an analysis of the sensitivity and impact of various vehicle parameters on the estimation of ballast settlement cost in passenger and freight systems in the Universal Cost Model (UCM). The study compares the vertical force obtained from multibody simulation results to analytical solutions for passenger and freight wagons. These results highlight the significance of considering unsprung mass, vehicle type, and vertical suspension parameters when estimating ballast settlement cost with the analytical representation of the P2 force. For passenger vehicles, the simulated P2 force is sensitive to all investigated parameters, with an average sensitivity of approximately 18%. The choice of method for determining vertical force for simulated track irregularities also influences the impact of these parameters. The simulated P2 force for the track section with track irregularities exhibits a higher percentile difference compared to other track cases, indicating that the parameters have a greater impact on the simulation of P2 force. In contrast, for freight vehicles, the simulated P2 force shows sensitivity only to two out of seven investigated parameters: the vertical stiffness of the outer and inner coil springs. The impact of these parameters is dependent on track irregularities and the chosen method for determining vertical force. The standard deviation measure has the highest impact on the outer coil spring, while the 99-percentile and mean value measure show a medium and minimal impact, respectively. The inner coil spring has an overall minimal impact across all track cases and comparison methods. These results show that the existing UCM methods can be improved by incorporating the identified parameters, thereby enhancing the accuracy of ballast maintenance cost estimation modules.

Active wheelset steering has been studied and implemented to improve the curving performance and stability of the wheelsets to overcome the drawbacks of the passive system. A control system for active wheelset steering must be robust to parameter variations and disturbances. A robust sliding mode controller with integral action (SMC + I) for active wheelset steering is therefore proposed and implemented in this paper to control wheelset lateral displacements to achieve perfect rolling conditions during curve negotiation. The robustness of the controller is achieved by deriving the control inputs bounded with known uncertain parameters. The control input is derived as a combination of the equivalent term and a switching term to reduce the amplitude of the switching input. A saturation function is used instead of a sign function in the switching term to provide continuous control. The integral action (I) is added to the sliding surface function to minimize the zero steady-state error. Co-simulation is executed to evaluate the performance and robustness of the designed controller. A conventional railway vehicle with two two-axle bogies with a maximum operating speed of 250 km/h is modelled in SIMPACK®, while the SMC + I controller is implemented in MATLAB/Simulink® for co-simulation. Two hydraulic servo actuators (HSAs), modelled with Simscape hydraulic libraries, are implemented in the longitudinal direction to steer each wheelset. The proposed controller ensures stability, finite-time convergence and zero steady-state errors for all possible running scenarios. This indicates robust performance of the designed SMC + I controller.

The Universal Cost Model (UCM) is a comparison framework originally developed in the EU S2R project Roll2Rail, that accounts for all aspects of running gear innovations that influence the whole railway system's Life Cycle Costs. It is a simulation-based framework enabling the comparison of a reference vehicle against an innovative one, showcasing the differential costs and benefits of said innovation. In the recently completed EU project NEXTGEAR, the UCM 2.0 was re-developed to address shortcomings of the original version, in particular the user friendliness but also refining some the theoretical foundation in aspects of wheel and rail wear, ballast damage and track settlement. One key aspect, not present in the original version and developed from scratch in UCM 2.0 was the addition of a switches and crossings (S&C) metal parts calculation to the infrastructure module, otherwise focused on plain line ballast settlement and rail degradation through wear and RCF. This paper describes the modelling work done to show how the driving forces on track damage were derived from a number of representative cases to achieve a simpler calculation process for the user. This enables the UCM 2.0 user to carry out the calculation without the need for access to detailed expert knowledge on S&C simulation.

The expectations of railway companies are not always aligned with the skills and abilities that university graduates bring when finishing their studies. This work firstly analyses the higher education study paths related to railways and their flexibility; then surveys the expectations of a set of European railway stakeholders in order to get the most looked after skills and abilities; next it analyses sectors other than the railways looking for academic best practices; and in the end it matches the most sought after skills within the Rail Careers Matrix for determining the relative importance of these skills in the operational, tactical, and strategic levels. The final result is a visual representation of the skills gaps and mismatches that European railway companies need to cover in the context of the actual Higher Education in the European landscape.

This paper provides with a panorama of the review conducted on existing studies and structured information from various sources related to rail education and skills development. The purpose of this review was to gather insights from previous EU projects, research papers, web portals, and reports to better understand the current landscape and teaching approaches in rail higher education. To give a comprehensible visualization, preferably in a website format, a simple but tangible concept has been developed, facilitating a smooth connection between the concrete real-world application and more abstract fields of developments within the scope of study.

A validated overhead conductor rail and a well-known wear model have been programmed to perform closer-to-reality simulations. Reliable wear rate estimates for two configurations of overhead conductor rails and three models of pantographs at different speeds and supply currents have been obtained. Results show that wear decreases with increasing speed at high currents and when the distances between supports are uniform. In addition, the use of different types of pantographs in the same facility has a positive effect in terms of wear reduction. Consequently, an adequate selection of the operating conditions contributes to reducing the wear rate.

Magnetic levitation (maglev) offers unique opportunities for guided transport; however, only a few existing maglev systems have demonstrated their potential benefits. This paper explores the potential of maglev-derived systems (MDS) in conventional rail, focusing on the use of linear motors to enhance freight operations. Such traction boosters provide additional propulsion capabilities by reducing the train consist’s dependence on wheel–rail adhesion and improving performance without needing an additional locomotive. The study analyses the Gothenburg–Borås railway in Sweden, a single-track, mixed-traffic line with limited capacity and slow speeds, where installing linear motors on uphill sections would allow freight trains to match the performance of passenger trains, even under challenging adhesion conditions. Target speed profiles were precomputed using dynamic programming, while a model predictive control algorithm determined the optimal train state and control trajectories. The results show that freight trains can achieve desired speeds but at the cost of increased energy consumption. A system-level cost–benefit analysis reveals a positive impact with a positive benefit-to-cost ratio. Although energy consumption increases, the time savings and reduced CO2 emissions from shifting goods from road to rail demonstrate substantial economic and environmental benefits, improving the efficiency and sustainability of rail freight traffic.

In conventional vehicle design approaches, there is typically little understanding of the consequences of early stage design choices. This may be attributed to the conventional approach’s limitation in capturing complex interactions, further leading to increased design iterations. To overcome this, holistic multidisciplinary models were developed. However, they introduce the burden of complexity and costs because of their intricate nature. Furthermore, it is challenging to gain meaningful insights without a deeper understanding of the model’s nature and structure. Therefore, in this article, an alternative form of model representation was proposed to address these shortcomings. This was achieved by integrating two concepts: network theory and sensitivity analysis. A detailed and robust framework that represents complex multidisciplinary models as network models, reduce their complexity, and navigate insights from them, was provided. This is further demonstrated by a case study of a rail vehicle traction system including a traction motor and an inverter coupled with operational drive cycle. Among the identified 246 factors in the traction system network model, the three most influential inputs were identified for the chosen output factor of interest. Subsequently, the knock-on effects of these inputs were determined. The results indicate a significant reduction in the network graph size compared with the complete network graph of the traction system model. This indicated a significant reduction in the number of factors to consider in the analysis. This demonstrates the capability of the proposed framework to reduce the complexity of the analysis while retaining the ability to analyze intricate interaction effects.

Rail vehicle models have become increasingly complex, posing challenges in extracting insights using traditional model representations as they require numerous iterations to achieve a satisfactory solution. This complexity leads to high computational and time costs and possibly resulting in inefficient vehicle design. To alleviate these limitations, network models are proposed as an alternative representation in this paper. These models enable the analysis of structure, behaviour, and patterns of interactions, facilitating an understanding of knock-on effects across disciplines and subsystems. The terminology, benefits, and capabilities of network theory in early-stage vehicle design are presented in this paper, along with the aspects to consider and methods for developing network models. The applicability of network theory metrics and algorithms is demonstrated using a railway traction system example. Results indicate that the proposed representations can capture complex system knock-on effects across disciplines and subsystems.

In early-stage vehicle design, there is a significant lack of knowledge about the impact of design requirements on the design of subsystems, theresulting knock-on effects between subsystems and the vehicle’s overall performance. This leads to a sub-optimal vehicle design with increaseddesign iterations. To mitigate this lack of knowledge, a cross-scalar design tool consisting of an induction motor model is presented in this paper.The tool calculates the motor’s attributes, namely its volume, mass, and the performance it can deliver to satisfy a given drive cycle’s requirements.This is achieved by breaking down the drive cycle requirements into motor parameters from which the various power losses are derived. Thesekey losses are then utilised to develop the torque/speed curve. Furthermore, it is proposed that the motor’s attributes can be used to design othersubsystems and consequently analyse their interaction effects. For example, the motor’s attributes can be used to design regenerative brakes andconsequently analyse their influence on brake wear, lifetime, and energy savings. Thus, the design tool enables the design of efficient vehicles withminimised design iterations by analysing the influence of design requirements on the subsystem’s design and the consequent interaction effectsamong the subsystems and on the vehicle’s overall performance.