Active wheelset steering can improve the curving performance of railway vehicles and thus reduce wear. Several control strategies have been proposed to achieve a perfect steering condition which may require feedback signals that are difficult to measure. This study proposes a control strategy for an active wheelset steering system via wheelset angular velocity measurements aimed to minimise longitudinal creepages in curves. The desired wheelset angular velocity is derived from the relation of longitudinal creepages and the wheelset movement in curves. Co-simulations with a conventional railway vehicle with two two-axle bogies are carried out for 24 cases. First, the strategy based on actual wheel-rail geometry is used to evaluate the effectiveness of the proposed control strategy; in the second step, a simplified strategy is tested using the approximated equivalent rolling radius approach. Curving performance indicators, including wheelset movements and wheel-rail wear number, are used to evaluate the performance of the control system. The results indicate the effectiveness of the proposed control strategies. Challenges and practical considerations are also discussed.

A mechatronic two-axle rail vehicle with only one suspension step is introduced in the Shift2Rail project Pivot2. This vehicle design reduces the vehicle weight in comparison to standard bogie vehicles. However, having only one suspension step drastically decreases passenger comfort. Thus, hydraulic actuators are introduced instead of passive dampers and active modal sky-hook control is applied. Due to the strong interaction between the running gear frame and the carbody, a blended modal solution is applied where a percentage of the acceleration of the frame is used in the feedback loop in addition to the acceleration of the carbody. To assess the performance of the controllers, simulations are carried out with the vehicle running at constant speeds from 10 km/h to 120 km/h on tangent track with high level of track irregularities. First, multiplicative dimensional reduction method (M-DRM) sensitivity analysis is applied to determine the importance of the control variables and subsequently a genetic algorithm (GA) optimization is performed to identify the control gains for each speed. The blended control proposed here can improve passenger comfort with respect to a standard modal control while maintaining similar energy and force usage.

Negotiation of turnouts imposes challenges for an active wheelset steering system due to lack of smooth transition curves and existence of rail discontinuities. These affect the performance of both the vehicle and control system in turnouts, which is investigated in this paper. The simulation is carried out with a conventional railway vehicle with two two-axle bogies passing through a crossover onto a parallel track. The Swedish 60E1-R760-1:5 turnout is used in this study. The results reveal that an active wheelset steering system can decrease the wheel-rail wear index. However, peaks in wear number take place in the switch toe and the crossing nose and they are considerably higher than other regions. A control scheme with preview is proposed by considering wheelset lateral positions on discontinuous rail profiles to avoid flange contact. The proposed control system with preview results in a further reduction of the maximum wear number by 66%.

With the support of EU’s key funding program Horizon Europe, the Europe’s Rail Joint Undertaking (EU-Rail) aims to deliver faster deployment of innovations in the railway design. The EU-Rail FutuRe project aims at tackling the increasing Total Cost of Ownership (TCO) of European interoperable regional lines by means of providing new innovative solutions to make these lines cost-effective and attractive. Setting the right level of requirements and specification for the regional rail rolling stock plays therefore an important role in meeting the FutuRe objectives. The detailed objectives are to define a vehicle concept for up to 100 passengers or corresponding freight with significant vehicle weight savings compared to existing rolling stock. The key systems for the research are the mechanical arrangement to avoid unnecessary weight and reduce maintenance costs on vehicle and track, the propulsion system which must be emission free despite that these lines often are non-electrified and the control system which may be combined with train protection system and offer autonomous running.

In the Shift2Rail project Pivot2 an innovative two-axle single suspension step metro vehicle is proposed. The single suspension step requires active suspensions to improve passenger ride comfort both in vertical and lateral direction. Two control approaches are developed, modal and blended control. Despite the good achievements with regard to comfort improvement, the robustness and performance of the developed controllers in relation to wheel degradation due to wear is unknown. Two different track types and three rail inclinations are used to generate worn wheel profiles with the KTH wear method creating a 75 wheel-rail combination set. For each combination, the comfort is evaluated with the vehicle travelling at constant speed from 50 km/h to 120 km/h with 5 km/h interval, producing a set of 1125 ride comfort evaluation points. Results show that both controllers are robust and that good ride comfort of the innovative vehicle can be maintained according to the EN12299 standard also in case of wheel degradation due to wear. Blended control produces enhanced performance with respect to its modal counterpart in vertical direction.

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.

This paper presents the implementation of the dual extended Kalman filter (DEKF) to estimate wheelset equivalent conicity, an accurate understanding of which can facilitate the implementation of an effective model-based estimator. The estimator is developed to identify the wheelset equivalent conicity of high-speed railway vehicles while negotiating a curve. The designed DEKF estimator employs two discrete-time extended Kalman filters combining state and parameter estimators in parallel. This estimator uses easily available measurements from acceleration sensors measuring at axle boxes and a rate gyroscope measuring bogie frame yaw velocity. Two tests, including linearized and actual wheel-rail geometry, are carried out at a speed of 250 km/h with stochastic and deterministic track features using multibody simulations, SIMPACK. The results with acceptable estimation errors for both track conditions indicate adequate performance and reliability of the designed DEKF estimator. They demonstrate the feasibility of utilizing this DEKF method in rail vehicle applications as the knowledge of time-varying parameters is not only important in achieving an effective estimator for vehicle control but also useful for vehicle condition monitoring.

The mechatronic vehicle developed within the Shift2Rail projects Run2Rail, Pivot, NEXTGEAR, and Pivot2 is evaluated with respect to wheel wear. The KTH wear model is used to determine the coefficients of Archard’s wear map to reproduce measured worn wheel profiles of the present vehicle running on Metro Madrid line 10. The same wear model is then used to evaluate the performance of the mechatronic vehicle controlled with two variants of a feedforward controller. The first one uses on-board measurements, while the second one is optimised using firefly optimisation algorithms assuming knowledge of the travelled track. The control strategy based on on-board measurements shows improvements above 60% in terms of lost wheel volume due to wear, compared to the standard bogie vehicle. The optimised controller reaches improvements above 70%. Good coherence is found between improvements predicted with the wear number and the ones achieved in terms of lost wheel volume.

Energy and maintenance costs constitute a large part of the recurring cost for railway operation. The vehicle weight impacts both energy consumption and the need for tamping of the track, while curving performance impacts the curving resistance and the wear on wheels and rails. In the project RUN2Rail and further in NextGear, both parts of the EU-funded initiative Shift2Rail, a single axle running gear with composite frame and active wheelset guidance was proposed for metro vehicles. The present study is comparing a reference vehicle from Metro Madrid with the proposed vehicle in terms of energy consumption and maintenance cost for simulated service on Metro Madrid Line 10 with curvature, gradients, stops and speed profiles considered. The calculated yearly saving for each vehicle become about 50 k€/(year*trainset), split on 20% on energy and 40% on each of wheel and track maintenance.

A Shift2Rail funded research project called RUN2Rail has investigated a range of new technologies for railway rolling stock. The project included a task on the use of active suspensions, and one of the subtasks was to propose a strategy supporting the authorisation by safety authorities for highly innovative mechatronic vehicles to be placed on the market. The incorporation of electronics and control into suspension systems is still at an early stage, so this paper provides a framework for a practical and efficient authorisation strategy, primarily based upon existing European regulations and standards but in general applicable worldwide.