Development of Urban Electric Bus Drivetrain

The development of the drivetrain for a new series of urban electric buses is presented in the paper. The traction and design properties of several drive variants are compared. The efficiency of the drive was tested using simulation calculations of the vehicle rides based on data from real bus lines in Prague. The results of the design work and simulation calculations are presented in the paper

Review on model-based methods for on-board condition monitoring in railway vehicle dynamics:

This article performs an extensive review on condition monitoring techniques for rail vehicle dynamics. In particular, the review focuses on applications of model-based approaches for on-board condition monitoring systems. The article covers condition monitoring schemes, fault detection strategies as well as theoretical aspects of different techniques. Case studies and experimental applications are also summarized. All the mentioned issues are discussed with the goal of providing a detailed overview on condition monitoring in railway vehicle dynamics

Low adhesion detection and identification in a railway vehicle system using traction motor behaviour

It is important to monitor the wheel-rail friction coefficient in railway vehicles to improve their traction and braking performance as well as to reduce the number of incidents caused by low friction. Model based fault detection and identification (FDI) methods, especially state observers have been commonly used in previous research to monitor the wheel-rail friction. However, the previous methods cannot provide an accurate value of the friction coefficient and few of them have been validated using experiments. A Kalman filter based estimator is proposed in this research project. The developed estimator uses signals from the traction motor and provides a new and more efficient approach to monitoring the condition of the wheel-rail contact condition. A 1/5 scaled test rig has been built to evaluate the developed method. This rig comprises 2 axle-hung induction motors driving both the wheelsets of the bogie through 2 pairs of spur gears. 2 DC generators are used to provide traction load to the rollers through timing pulleys. The motors are independently controlled by 2 inverters. Motor parameters such as voltage, current and speed are measured by the inverters. The speed of the wheel and roller and the output of the DC generator are measured by incremental encoders and Hall-effect current clamps. A LabVIEW code has been designed to process all the collected data and send control commands to the inverters. The communication between the PC and the inverters are realized using the Profibus (Process Field Bus) and the OPC (Object Linking and Embedding (OLE) for Process Control) protocol. 3 different estimators were first developed using computer simulations. Kalman filter and its two nonlinear developments: extended Kalman filter (EKF) and unscented Kalman filter (UKF) have been used in these 3 methods. The results show that the UKF based estimator can provide the best performance in this case. The requirement for measuring the roller speed and the traction load are also studied using the UKF. The results show that it is essential to measure the roller speed but the absence of the traction load measurement does not have significant impact on the estimation accuracy. A re-adhesion control algorithm, which reduces excessive creepage between the wheel and rail, is developed based on the UKF estimator. Accurate monitoring of the friction coefficient helps the traction motor work at its optimum point. As the largest creep force is generated, the braking and accelerating time and distance can be reduced to their minimum values. This controller can also avoid excessive creepage and hence potentially reduce the wear of the wheel and rail. The UKF based estimator development has been evaluated by experiments conducted on the roller rig. Three different friction conditions were tested: base condition without contamination, water contamination and oil contamination. The traction load was varied to cover a large range of creepage. The importance of measuring the roller speed and the traction load was also studied. The UKF based estimator was shown to provide reliable estimation in most of the tested conditions. The experiments also confirm that it is not necessary to measure the traction load and give good agreement with the simulation results. With both the simulation and experiment work, the UKF based estimator has shown its capability of monitoring the wheel-rail friction coefficient

Summary of the Modern Wheel Slip Controller Principles

Railway traction vehicles need to transfer high tractive effort from wheels to rails. The task is complicated because the maximum transferable force continuously changes during the train run, and the change can lead to the high wheels slip velocity or slippage. The effects are undesirable and must be prevented if it is possible or at least limited by slip controllers. There have been several slip controllers developed based on different principles with different degree of complexity and efficiency. The paper summarises principles of the slip control methods and brings their overview with the simulation of their behaviour

EXTENDED KALMAN FILTER DESIGN FOR RAILWAY TRACTION MOTOR

Monitoring the adhesion force between a railway wheel and a rail surface is very essential in maintaining the high acceleration and braking performance of railway vehicles. Due to the difficulties encountered in direct measurement of friction coefficient, creepage and adhesion force, state observers are used as indirect estimation methods. This paper proposes an effective estimation method, which exploits railway traction motor behaviour to give an assistance for realizing wheel slip and adhesion control in order to be used in railway applications. This method plays an active role in optimizing the use of the existing adhesion and reducing wheel wear by decreasing high creep values. With this method, adhesion force can be indirectly estimated by measuring stator currents, and angular speed of the AC traction motor and using dynamic relationships based on the extended Kalman filter (EKF) simulation model. The re-adhesion controller can be designed to regulate the motor torque command according to the maximum available adhesion depending on the estimated results. To test the proposed method, simulations were performed under different friction coefficients.   

PSO Based EKF Wheel-rail Adhesion Estimation

An ideal traction and braking system not only ensures ride comfort and transportation safety but also attracts significant cost benefits through reduction of damaging processes in wheel-rail and optimum on-time operation. In order to overcome the problem of the wheel slip/slide at the wheel-rail contact surface, detection of adhesion and its changes has high importance and scientifically challenging, because adhesion is influenced by different factors. However, critical information this detection provides is applicable not only in the control of trains to avoid undesirable wear of the wheels/track but also the safety compromise of rail operations. The adhesion level between the wheel and rail cannot be measured directly but the friction on the rail surface can be measured using measurement techniques. Estimation of wheel-rail adhesion conditions during railway operations can characterize the braking and traction control system. This paper presents the particle swarm optimization (PSO) based Extended Kalman Filter (EKF) to estimate adhesion force. The main limitation in applying EKF to estimate states and parameters is that its optimality is critically dependent on the proper choice of the state and measurement noise covariance matrices. In order to overcome the mentioned difficulty, a new approach based on the use of the tuned EKF is proposed to estimate induction motor (as a main part of the train moving system) parameters. This approach consists of two steps: In the first step the covariance matrices are optimized by PSO and then, their values will be introduced in the estimation loop.

Multiple model based real time estimation of wheel-rail contact conditions

The issue of low adhesion between the wheel and the rail has been a problem for thedesign and operation of the railway vehicles. The level of adhesion can be influenced bymany different factors, such as contamination, climate, and vegetation, and it isextremely difficult to predict with certainty. Changes in the adhesion conditions can berapid and short-lived, and values can differ from position to position along a route,depending on the type and degree of contamination. All these factors present asignificant scientific challenge to effectively design a suitable technique to tackle thisproblem. This thesis presents the development of a unique, vehicle based technique forthe real-time estimation of the contact conditions using multiple models to representvariations in the adhesion level and different contact conditions. The proposed solutionexploits the fact that the dynamic behaviour of a railway vehicle is strongly affected bythe nonlinearities and the variations in creep characteristics. The purpose of the proposedscheme is to interpret these variations in the dynamic response of the wheelset,developing useful contact condition information. The proposed system involves the useof a number of carefully selected mathematical models (or estimators) of a rail vehicle tomimic train dynamic behaviours in response to different track conditions. Each of theestimators is tuned to match one particular track condition to give the best results at thespecific design point. Increased estimation errors are expected if the contact condition isnot at or near the chosen operating point. The level of matches/mismatches is reflected inthe estimation errors (or residuals) of the models concerned when compared with the realvehicle (through the measurement output of vehicle mounted inertial sensors). Theoutput residuals from all the models are then assessed using an artificial intelligencedecision-making approach to determine which of the models provides a best match to thepresent operating condition and, thus, provide real-time information about trackconditions

Investigation of Novel Displacement-Controlled Hydraulic Architectures for Railway Construction and Maintenance Machines

This dissertation aims at showing how to transform hydraulic systems of railway multi-actuator machinery characterized by inefficient state-of-the-art systems into the 21st Century. Designing machines that are highly efficient, productive, reliable, and cost affordable represents the target of this research. In this regard, migrating from valve-controlled architectures to displacement-controlled layouts is the proper answer. Displacement-controlled systems remove the losses generated by flow throttling typical of conventional circuits, allow an easy implementation of energy recovery (e.g. during regenerative braking), and create the possibility for the use of hybrid systems capable of maximizing the downsizing of the combustion engine. One portion of the dissertation focuses on efficient propulsion systems suitable for railway construction and maintenance machines. Two non-hybrid architectures are first proposed, i.e. a novel layout grounded on two independent hydrostatic transmissions (HSTs) and two secondary controlled hydraulic motors (SCHMs) connected in parallel. Three suitable control strategies are developed according to the specific requirements for railway machines and dedicated controllers are implemented. Detailed analyses are conducted via high-fidelity virtual simulations involving accurate modeling of the rail/wheel interface. The performance of the propulsion systems is proven by acceptable velocity tracking, accurate stopping position, achieving regenerative braking, and the expected behavior of the slip coefficients on both axles. Energy efficiency is the main emphasis during representative working cycles, which shows that the independent HSTs are more efficient. They consume 6.6% less energy than the SCHMs working with variable-pressure and 12.8% less energy than the SCHMs controlled with constant-pressure. Additionally, two alternative hybrid propulsion systems are proposed and investigated. These architectures enable a 35% reduction of the baseline machine’s rated engine power without modifying the working hydraulics. Concerning the working hydraulics, the focus is to extend displacement-controlled technology to specific functions on railway construction and maintenance machines. Two specific examples of complete hydraulic circuits for the next generation tamper-liners are proposed. In particular, an innovative approach used to drive displacement-controlled dual function squeeze actuators is presented, implemented, and experimentally validated. This approach combines two functions into a unique actuator, namely squeezing the ballast and vibrating the tamping tools of the work-heads. This results in many advantages, such as variable amplitude and variable frequency of the tamping tools’ vibration, improved reliability of the tamping process, and energy efficient actuation. A motion of the squeeze actuator characterized by a vibration up to 45 Hz, i.e. the frequency used in state-of-the-art systems, is experimentally confirmed. In conclusion, this dissertation demonstrates that displacement-controlled actuation represents the correct solution for next-generation railway construction and maintenance machines