Advances in Dynamics of Vehicles on Roads and Tracks II

Inhaltsverzeichnis

1. Frontmatter

2. Rail: Active suspensions, Control and Monitoring

   1. Frontmatter

   2. Multi-degree of Freedom Dynamic Vibration Absorber of the Carbody of High-Speed Trains

      Yu Sun, Jinsong Zhou, Dao Gong, Taiwen You, Qiushi Wang

      Abstract

      A multi-degree of freedom dynamic vibration absorber (MDOF DVA) to suppress the vibration of the carbody of high-speed trains is proposed. The MDOF DVA is installed under the carbody, the natural vibration frequency of which are designed as a dynamic vibration absorber for lateral motion, bouncing, rolling, pitching, and yawing of the carbody. A high-speed train dynamics model including an under-carbody MDOF DVA is established. Based on the virtual excitation method, the vibration control effect on each DOF of the MDOF DVA on the carbody is analyzed. Results show that the MDOF DVA can absorb the vibration of the carbody in multiple degrees of freedom.

   3. Active Modal Control of an Innovative Two-Axle Vehicle with Composite Frame Running Gear

      Rocco Libero Giossi, Anton Shipsha, Rickard Persson, Per Wennhage, Sebastian Stichel

      Abstract

      Within the Shift2Rail projects Pivot2 and NEXTGEAR, an innovative Metro vehicle with single axle running gear and only one suspension step is proposed. A composite material running gear frame is developed to be used both as structural and as suspension element. The design with only one suspension step can significantly degrade the passengers ride comfort. Thus, active modal control is implemented both in lateral and vertical direction to increase the performance of the system. The running gear frame is modelled in Abaqus® as well as the carbody. Structural modes of both elements are implemented in SIMPACK®. A hydraulic actuator model is developed in Simscape®, where two pressure-controlled valves are used to control the pressure inside the chambers of a double acting hydraulic cylinder. A co-simulation environment is then established between SIMPACK® and Simulink®. The vehicle is running with speeds between 10 and 120 km/h. Active modal control makes it possible to maintain ride comfort levels of conventional bogie vehicles with this innovative single axle and single suspension step running gear, promising substantial weight savings of about 400 kg/m. The single axle running gear solution with active comfort control developed here can be an attractive alternative to bogies, providing reduced Life Cycle Costs.

   4. A Research Facility for the Next Generation Train Running Gear in True Scale

      Andreas Heckmann, Daniel Lüdicke, Alexander Keck, Björn Goetjes

      Abstract

      The running gears of DLR’s long-term project Next Generation Train utilize independently rotating wheels with mechatronic track guidance, direct drives close to the wheels and are optimized for low weight. On the basis of encouraging research results so far, DLR decided to design and build a true scale prototype of the NGT running gear and use it as a research facility. It is the intention to improve, validate and demonstrate the mechanical and mechatronic design, sensor and actuator lay-out step by step and finally approach the Technology Readiness Level 6. By the end of 2022, this prototype will be put into operation considering low speed scenarios up to max. 5 m/s at an in-house integration test rig. This is the current task, which is reported on in the paper. However, this work is supposed to prepare advanced performance experiments up to 350 km/h on external roller rigs and at railway test tracks later on.

   5. Implementation of Steering Control of Full Scale Railway Vehicle Assembling Independently Rotating Wheels with Negative Tread Conicity

      Yu Wang, Shihpin Lin, Ronak Prateek, Yoshihiro Suda

      Abstract

      Utilization of independently rotating wheel attains benefits in low floor transit, while sacrifices the steering performance because of the deficiency of longitudinal creep forces. As a promising structure for improving steering performance of vehicle, independently rotating wheel with negative tread conicity was proposed previously, but the research on such structure still stays at the stage of simulation and scale model, while full scale vehicle experiment has not been implemented so far. To this end, the experimental validation of vehicle assembling independently rotating wheels with negative tread conicity is firstly implemented in present research. The vehicle system compatible with full scale rail is constructed and the stand of better curving performance is supported by experiment results. Moreover, as the traction is necessary for the practical operation of vehicle, the utilization of traction motors for further improving the curving performance of vehicle is naturally proposed in this research. The active steering control is attempted, and the results indicate that the further improvement of curving performance is achieved by means of proposed control scheme.

   6. Improvement of High-Speed Vehicle Vertical Ride Comfort with Semi-active Primary Suspension

      Bin Fu, Binbin Liu, Egidio Di Gialleonardo, Stefano Alfi, Stefano Bruni

      Abstract

      With the trend of car-body light-weighting, car-body structural vibration is imposing a new challenge to the vertical ride comfort which, however, is difficult to be improved by passive suspension components. Semi-active primary suspension (SAPS) is studied in this work to improve the vertical ride comfort with special attention on the suppression of car-body first bending mode. At first, a coupling effect between car-body bending mode and bogie pitch and longitudinal vibrations is analyzed. Then a simplified vehicle model is established to represent the vehicle dynamic behavior, showing a good agreement with a detailed multibody vehicle model in SIMPACK, integrated with the finite element model of the car-body. Skyhook controller is applied in the SAPS, capable of mitigating vibration from the car-body bending mode. LQG controller is also developed, showing further reduced vibration not only related to the first bending mode but also in a lower frequency range associated with vibrations due to rigid modes.

   7. Railway Bogie Diagnostics Using Machine Learning and Bayesian Net Reasoning Approaches

      Bernhard Girstmair, Thomas Moshammer

      Abstract

      Railway bogies are generally maintained preventively within certain time periods. Vehicles run for a long time (up to thirty years) so that about one-third of lifecycle costs are caused by maintenance. Condition-based predictive maintenance strategies offer economic improvements of up to 15 percent and an increased availability of up to 100 percent. By implementing a sensor based diagnostic system using artificial intelligence techniques and business analytics, maintenance can be optimized.

      This paper presents a concept for the detection of faulty mechanical components, such as dampers and springs, of railway bogies. On the one hand, the work deals with the analysis of time series data by evaluating power spectral density and transfer functions. On the other hand, it shows results of the training of machine learning models based on features. Various multi body simulations have been done to develop a physical understanding of the effects of the individual fault modes. Beside this, the available data set for the analysis also includes real measured data from test rides with faulty components.

      The developed algorithms have been deployed on a Siemens commuter train. In addition to validation results, this work also shows an example of the successful detection of real failures in operational mode.

   8. Condition Monitoring and Evaluation of Railway Vehicles Using New Index Values Consisting of Wheel Load and Lateral Force

      Sora Sakanishi, Shihpin Lin, Yu Wang, Yoshihiro Suda

      Abstract

      The on-line condition monitoring system can monitor the condition of the train by measuring the wheel load and lateral force of the train passing through the measurement point over a long period of time. With this system, the derailment coefficient and wheel load balance of the sharp curve section have already been monitored. On sharp curves section, it is very important to evaluate the steering performance of the bogie and the lubrication conditions at the contact point between the wheels and rails. In addition, many types of bogie are running on the same section. It is efficient to evaluate the steering performance of the bogie and the lubrication conditions at the contact point between the wheels and rails from the ground side. In this study, new indicators consisting of wheel load and lateral force were introduced and evaluated to add train steering performance to monitoring system.

   9. Validation of a Driverless Railway Vehicle Control Unit Algorithms Through Real-Time Vehicle Simulation

      Michele Vignati, Nicola Debattisti, Maria Laura Bacci, Davide Tarsitano

      Abstract

      The use of Electronic Control Unit (ECU) in vehicle requires them to be widely tested before the first physical prototype is developed. This is even more important when the vehicle is unmanned because most critical tasks are demanded to the control unit without a human supervision. This paper presents a Hardware-in-the-loop (HiL) test bench used to validate the control algorithm of the Vehicle Control Unit (VCU) of a Driverless Railway Vehicle (DLRV). The VCU has the duty to control the traction motor and the pneumatic braking systems but has also to control the hybrid powertrain and its configuration. The test bench is then built in Simulink Real Time environment where the vehicle model is implemented. The model communicates with the VCU through CAN BUS communication as it will operate on the real vehicle.

   10. Traction Control Algorithms Versus Dynamic Performance in Light Rail Vehicle Design Architectures

       Esteban Bernal, Maksym Spiryagin, Ingemar Persson, Sanjar Ahmad, Qing Wu, Colin Cole

       Abstract

       Light rail vehicles (LRV) are becoming more attractive for urban centres as a sustainable mass transportation solution. The tight curves and short transitions that characterise urban LRV networks lead to high wear and undesirable vehicle dynamics that can be avoided with active suspensions or traction control algorithms. This paper presents a comparison on the dynamic performance and curve negotiation of LRV with solid wheelsets and independently rotating wheels (IRW) with different traction control systems. Two multibody simulations were conducted to compare slip, angle of attack (AoA) and other vehicle dynamics parameters. The traction control was set to operate at the maximum traction conditions with a slip set point. The wheel-rail contact model included the effects of slip-dependent friction variations. It was found that the LRV with IRW reduced the lateral wheel-rail contact forces, traction coefficients and wheel torque when negotiating a curve, while maintaining the AoA performance. The results indicate that with an appropriate traction control algorithm, a LRV with IRW can be more track friendly than a solid wheelsets LRV when negotiating a curve in maximum traction conditions.

   11. Data-Driven Robust Control for Railway Driven Independently Rotating Wheelsets Using Deep Deterministic Policy Gradient

       Juyao Wei, Zhenggang Lu, Zhe Yang, Yang He, Xiaochao Wang

       Abstract

       This paper presents a data-driven robust controller for the active steering of driven independently rotating wheels (DIRW). Associated with a two-axle DIRW vehicle, a reinforcement learning controller called Deep Deterministic Policy Gradient (DDPG) is applied to improve the guidance and curve-negotiation behaviour of the DIRW system. We implement deep neural networks in DDPG to learn complex vehicle behaviours by training with data generated dynamically from non-linear simulation models. The controller can achieve adaptive optimization through online training episodes. The DDPG controller’s effectiveness is verified by the co-simulation method: the DIRW railway vehicle’s dynamics model is established in SIMPACK, and the data-driven controller is trained and deployed in MATLAB. The simulation results show that for the DIRW system, the proposed control approach can improve the IRW’s running performance and can significantly reduce the wheel-rail wear in both straight and curved tracks.

   12. Demonstration of a Digital Twin Framework for Model-Based Operational Condition Monitoring of Crossing Panels

       Marko D. G. Milošević, Björn A. Pålsson, Arne Nissen, Jens C. O. Nielsen, Håkan Johansson

       Abstract

       The wheel transition area in railway crossings is subjected to impact loads that cause an accumulation of structural degradation in crossing panels over time. This degradation leads to high maintenance costs and possibly traffic disturbances. There is therefore a demand from infrastructure managers to monitor the condition and predict maintenance needs for these assets without the need for regular on-site inspections. One solution for operational condition monitoring is to observe the structural response of the crossing under traffic loading via embedded accelerometers. From these measurements, relative changes in track dynamics over time can be observed. To derive a condition or predict maintenance needs, however, these measured accelerations need to be related to the status of the asset. A framework for this where measurement data, simulation models and maintenance history are combined to build an online model that can assess the status and predict future maintenance needs for a material asset is often called a Digital Twin. This paper will present a Digital Twin framework that uses measured accelerations, climate data, scanned running surface geometry and a multi-body simulation (MBS) model to estimate the status and degradation rate of crossing panels. Method developments for this framework are demonstrated for two in situ crossings.

   13. Adhesion-Based Maximum-Seeking Brake Control for Railway Vehicles

       Christoph Schwarz, Tobias Posielek, Björn Goetjes

       Abstract

       The emerging integration of mechatronic systems in modern railway vehicles enables significant improvements with respect to safety, comfort, and wear reduction. To fully exploit the potential of mechatronic systems, the German Aerospace Center (DLR) complements its validated estimation and control concepts in the field of lateral vehicle dynamics with approaches for longitudinal dynamics. The present work introduces an adhesion-based maximum-seeking brake control that offers a benefit in contrast to slip-based approaches especially in safety critical scenarios.

   14. Experimental Study of Magnetic Levitation Vehicle System Based on Flexible Levitation Control Strategy

       Qin Li, Gang Shen

       Abstract

       Coupling vibration between maglev vehicle and track can easily occur when maglev train levitate on a light or low stiffness track beam. To overcome this, track beam nowadays always got big mass and stiffness which directly result in massive increasing of construction cost of maglev line. It would be a much more economical way to solve this vibration problem by improving levitation control strategy. In this paper flexible levitation control strategy and traditional rigid levitation control strategy are tested on a small scale magnet-track beam coupling test rig. For magnetic levitation system, because of the strong nonlinear characteristic, test rig study is more accuracy than computer simulation. The test rig is designed based on similarity theory and have one magnet and one simply supported track beam. Results show that comparing with rigid levitation control strategy, flexible levitation controller can make the system more stable. Coupling vibration can be actively decreased under flexible control strategy.

   15. Polygonal Wheel Detection of Railway Vehicles Based on VMD-FastICA and Inertial Principle

       Bo Xie, Shiqian Chen, Kaiyun Wang, Yunfan Yang, Wanming Zhai

       Abstract

       Wheel polygonalisation, as a common phenomenon in railway vehicles, will worsen the dynamic effect of wheel-rail and affect running safety. Detection of the polygonal wear is essential for railway vehicle maintenance and running safety. Therefore, a novel polygonal wear detection method based on vehicle vibration measurements is proposed in this paper. Firstly, the axle box vertical acceleration signal is decomposed into multiple intrinsic mode functions (IMFs) by the variational mode decomposition (VMD) algorithm. Then, the observed vibration signal composed of multiple IMFs is analyzed by the independent component analysis (ICA) algorithm, and the independent component related to polygonal wear is selected according to their correlation coefficients. Finally, the optimal independent component is used to calculate the order and amplitude of the polygonal wear by the inertia principle. To verify the effectiveness of the proposed method, the simulation signal and axle box acceleration signal of measured data are implemented. Experimental results demonstrate that the proposed method can effectively estimate the order and amplitude of the polygonal wear.