Slip controllers are crucial for railway vehicle operation when a high tractive effort is required. The slip controllers have been developed for decades, and their developments continue. The developed slip controllers are based on many more or less effective principles. One of the perspective slip controllers determines a phase shift between an injected excitation signal to the required torque of the electric drive and the signal representation in a measured wheel angular velocity. The slip controllers that are based on the principle can effectively work with any adhesion conditions. However, the slip controller principle has some drawbacks like high filtration requirements, possible failure due to mechanical shock in the wheel-rail contact and long response time. The paper proposes a novel phase shift detection method for the slip controller based on an unscented Kalman filter that can cope with the known disadvantages of the original slip controller. When the proper output of the UKF is used, the slip controller becomes faster, more reliable and can work when the original slip controller fails. The proposed slip controller was verified on the measured data in an open-loop calculation and the mathematical model in the closed-loop simulation.
Analysis of the Locomotive Wheel Slip Controller Operation During Low Velocity
Locomotives are equipped with slip controllers that improve their adhesion utilization and keep wheels slip velocities at appropriate values. The current slip controllers typically correctly work during the regular train run. However, there are some cases when some slip controllers may fail. The correct operation at low velocities is one of the cases in which the slip controller can fail. The long-time response of the velocity measurement that is caused by incremental encoders with a low number of pulses per revolution is causing the problem in this case. The wheel slippage can occur when the adhesion conditions are adverse, and applied forces are high in this case. This paper describes a novel slip controller based on the unscented Kalman filter that correctly works during the train low velocity operation with any adhesion conditions. The slip controller was designed with taking into account all aspects that influence the controller operation. Therefore, the adhesion, electric drive, the slip controller, and problem background are described in the paper. The slip controller functionality is verified on measured data and a mathematical model that was verified on the measured data.
Evaluation of Phase Shift in Electric Drive by Kalman Filter for Wheel Slip Control
Slip controller is an essential part of the locomotive controller because it enables maximum force transfer and increases the service life of the locomotive parts. The modern slip controllers try to determine actual adhesion parameters and set the required tractive force to avoid slippage occurrence. Many types of the slip controller methods were developed, and one of developed principle try to determine adhesion parameters from phase shift between motor torque and corresponding speed measured on the motor or wheelset. The paper presents a novel evaluation procedure for the phase shift calculation that is based on the Kalman filter that enables directly compare force corresponding with the motor torque and the adhesion force. The method principle is described in the paper, and the method performance is evaluated on the mathematical model.
Locomotive Wheel Slip Controller based on Power Dissipation in Wheel-rail Contact
Railway traction vehicles are equipped by slip controllers to avoid wheels slippage occurrence during the train operation and simultaneously enables to maximise the force transfer from wheels to rails. Many types of slip controllers were developed during the last decades, and their development is not sill finished. The paper proposes a novel slip controller principle that is based on a calculation of power dissipation in a wheel-rail contact area. The presented approach enables better adhesion utilisation than conventional slip controllers based on the adhesion coefficient value estimation. The dissipation power is calculated from the estimated adhesion force and train velocity. The estimation of the adhesion force is made by an extended Kalman filter. The slip controller principle is verified on measured data that were obtained on a freight train hauled by an electric locomotive.
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.
Implementations of UKF and EKF for Wheel Slip Control Purpose to Locomotive Computer
Modern electric locomotives have to transfer high tractive effort between wheels and rails. Therefore, they have to be equipped with slip controllers that enable to achieve required force and keep wheelsets velocity in the acceptable value. The slip controller is a part of the locomotive control algorithm that runs on an axle computer that is typically a digital signal processor with limited computational power. The modern slip controller requires determining an actual value of adhesion that cannot be directly measured during the train runs. Therefore, the adhesion estimation is necessary. Extended Kalman filter or unscented Kalman filter can be used with an advantage because they can cope with some drawbacks of conventional methods. However, they are not typically used because of their high computational requirements. Therefore, the extended Kalman filter and unscented Kalman filter are implemented into a digital signal processor that is typically used in the locomotives as an axle computer to verify the possibility of used slip control methods based on the mentioned estimators in the paper. The verification is made on measured data.
Locomotive Wheel Slip Control Method Based on an Unscented Kalman Filter
Railway traction vehicles transfer forces between wheels and rails through an adhesion coefficient. The adhesion coefficient value can decrease abruptly during the train run. Therefore, the wheels can simply gain high value of the wheels slip velocity. Thus, the vehicles are equipped with slip controllers for this case. During the past decades, many types of slip control strategies were developed, and the new methods are also developed today. Some perspective methods are based on an estimation of the adhesion coefficient or an adhesion force. However, correct operation of these methods is not guaranteed in all cases. Moreover, these methods have some weakness that can decrease their efficiency. Therefore, a novel method based on the adhesion condition estimation is presented in the paper. The adhesion condition is estimated by an unscented Kalman filter. When the method is connected to a controller, it is possible to eliminate the rising wheel slip velocity at its beginning and limit it to the appropriate value. The output of the method is directly used as an input of the controller without any additional calculation as it is used in traditional methods. The input signal does not need any additional filtration, and the method does not require information about the actual train velocity for its proper work. The verification of the method is done with the measured data that were measured on a freight train hauled by an electric locomotive. The paper also presents simulation results of the method with a controller based on the locomotive mathematical model.
Method for Torsional Vibrations Detection of Locomotive Wheelset Based on UKF
Torsional vibrations that occur between masses in mechanical systems are undesirable and should be limited. The torsional vibrations are limited in many industrial applications by a control of a dynamic electric drive. However, the torsional vibrations which occur in locomotives axles are different because the vibrations emergence mainly depends on an adhesion conditions change or external sources that are present on the track. The paper presents a method for the torsional vibrations detection and suppression. The detection method is based on an unscented Kalman filter that is simultaneously used as a part of the slip controller that can limit the torsional vibrations besides wheels slip control that is the primary purpose of the slip controller. The method verification is made on the simulations.
Comparison of Different Kalman Filters Types Performance for a Locomotive Slip Control Purposes
To reach an efficient tangential force transfer between wheels and rails of railway vehicles, it needs to be equiped by slip controllers. The slip controller goal is to limit the force if a significant value of a slip can happen. The big value of the slip can occur if the required force is greater than the maximal transferable force or if an adhesion conditions became worsening. The slip control issue has been solved for several years. Many slip control methods were developed during these years. The slip control issue is still actual because of the tractive effort and train speed increases and because fast and reliable slip controller can eliminate undesirable mechanical effects and wear. Some slip control methods use the adhesion force estimation. A Kalman filter or its some variant can be used for the force estimation. The Kaman filter, an extended Kalman filter and an unscented Kalman filter are described in the paper, and their performances are compared from the slip control point of view.
Comparison of Locomotive Adhesion Force Estimation Methods for a Wheel Slip Control Purpose
Locomotives are equipped with slip controllers to limit a value of a wheel slip velocity and conducive to reach required locomotive tractive effort. The slip control methods are developed for tenths years, and the methods are based on several principles. Progressive methods determine an adhesion-slip characteristic slope. This method requires knowledge of an adhesion coefficient value or an adhesion force value. These quantities cannot be measured directly during the train run. Therefore, these quantities are estimated by some estimation techniques. A Kalman filter or its nonlinear variants as an extended Kalman filter or an unscented Kalman filter can be used as estimators of the quantities. Every filter has different features, and the estimated output is different. The filters performance during adhesion estimation for a locomotive slip control is presented in the paper. The comparison of the filters is made for various filters setting. The comparison is based on measured data as offline simulation in Matlab software.
Dependence of locomotive adhesion force estimation by a Kalman filter on the filter settingsv
A locomotive needs a slip controller to achieve the maximal tractive effort. Many types of methods are used for this purpose. Some methods use a Kalman filter or other type of estimation. These methods can work precisely and reliably. The Kalman filter provides a filtration of an output signal to eliminate the output signals noise when the Kalman filter inputs are noisy, and a filtration level is required. There is a relation between the Kalman filter filtration level and its delay. The Kalman filter delay can reach over 100 milliseconds. The locomotive slip controller has to react in the order of tens of milliseconds to provide an appropriate function. The high level of filtration and low delay are contradictory demands. The key is to find a relation between the Kalman filter delay and filtration through its covariance matrixes. In the paper is investigated the relation between the filtration level and the time delay. The simulations are made in the Matlab software and based on measured data.
Extended Kalman Filter Utilization for a Railway Traction Vehicle Slip Control
Optimization of Electrical and Electronic Equipment (OPTIM) & 2017 Intl Aegean Conference on Electrical Machines and Power Electronics (ACEMP), 2017 International Conference on. IEEE, 2017. p. 869-874. ISBN 978-1-5090-4489-4.
Locomotives reach a high value of tractive effort. The high values of tractive effort can cause problems if an adhesion conditions are poor. A wheel velocity high value that is much greater than the train velocity can occur in this case. The high slip velocity value has to be eliminated because it causes a high wear of wheels and rails and can cause damage to some locomotive mechanical parts. The slip velocity can be decreased by significant reduction of the tractive effort. The result of the tractive effort reduction is the train velocity decreasing and mechanical stress. Slip controllers are used to avoiding this situation. There are many types of slip controllers that were developed in the past. New slip controllers are still developed and improved today. In the paper is presented slip control method that is based on an extended Kalman filter that can rapidly and reliably detect decreasing of the adhesion. The method performance is demonstrated on simulations that are based on measured data.
Locomotive Velocity Estimation for a Slip Control Purpose by an Unscented Kalman Filter
The train velocity is needed to be known for many purposes like the train safety systems or a slip control. The train velocity is typically determined from wheelsets velocity. The wheelset velocity is different with the train velocity due to a slip velocity that is needed for a force transmission between wheels and rails. The train velocity measured by this way is the only estimation of the train velocity. If the train velocity is needed for a slip control, the actual velocity has to be known with the smallest possible delay. For the purpose, a novel method based on the unscented Kalman filter is presented. Nonlinearity between the wheel velocity and the train velocity is analytically derived. The simulation results are based on the measured data.
Train Velocity Estimation Method Based on an Adaptive Filter with Fuzzy Logic
The train velocity is difficult to determine when the velocity is measured only on the driven or braked locomotive wheelsets. In this case, the calculated train velocity is different from the actual train velocity due to slip velocity or skid velocity respectively. The train velocity is needed for a locomotive controller proper work. For this purpose an adaptive filter that is tuned by a fuzzy logic is designed and described in the paper. The filter calculates the train longitudinal velocity based on locomotive wheelset velocity. The fuzzy logic is used for the tuning of the filter according to actual wheelset acceleration and wheelset jerk. The simulation results are based on real measured data on a freight train. The results show that the calculated velocity corresponds to the actual train velocity.
Adhesion Force Detection Method Based on the Kalman Filter for Slip Control Purpose
The slip control is important for an adhesion force transmission between locomotive wheels and rails. The slip control consists of two tasks. The first task is the slip value detection and the second one is the evaluation of a slip value with a subsequent control action. These two tasks can be realized by many types of methods. Several detection methods use an adhesion coefficient or the adhesion force determination. Because of difficulty of the adhesion coefficient measurement during the train run the adhesion coefficient or the adhesion force has to be estimated. In this paper, the adhesion force is estimated by the Kalman filter. The Kalman filter uses the locomotive model and measured locomotive velocity. The Kalman filter is implemented in Matlab and also applied on measured data.
Train Velocity Estimation by Extended Kalman Filter
A train longitudinal velocity is needed for some control devices. The train velocity is typically determined from a locomotive wheelsets velocity. This solution can cause problems when the wheelsets are driven or braked. In these cases, the wheelset velocity is higher or lower than the train longitudinal velocity due to a slip or skid velocity. The problem is typically solved by some type of averaging or filtration of all available wheelsets velocities. These algorithms need to know all wheelsets velocities at the same time. This task can be difficult to fulfil in some types of distributed computer systems due to communication delays between computers. The problem is solved by using an extended Kalman filter that estimates the train velocity from one wheelset velocity in the paper. The filter and its properties are described and designed in the paper. The measured data are used for the filter function check.
For reaching locomotive maximal tractive effort it is needed fully utilize available adhesion conditions on a track. For the purpose are exploited slip controllers. The controllers are based on many types of algorithms and some algorithms has common feature that the algorithms needed to know the locomotive longitudinal velocity. Measuring of the locomotive longitudinal velocity on driven wheels without any additional devices cannot be done. Therefore there are some methods for estimation of the train velocity. The paper proposes an adaptive nonlinear filter that is used for the locomotive longitudinal velocity estimation. The filter is described and simulation results in Matlab software based on measured wheel velocity are presented.
Locomotive Wheel Speed Measurement under Wheel Slip Conditions
Wheel speed of heavy freight train locomotive under non-ideal traction conditions was measured with very high resolution and fine precision. Many authors published papers in this area over past century, but only recent advance in the information technology enabled measurement in such extent and resolution at the same time. Most modern locomotives have the speed sensor coupled with the traction motor. Unlike many other authors doing research in the area of wheel-slip, in the presented case the wheel speed was measured directly on the wheel, not indirectly on the traction motor. This approach made it possible to observe the wheel speed directly, without the requirement to implement motor – wheel model, which can introduce inaccuracies. Thanks to an independent method of train speed determination using a sensitive GPS receiver, wheel slip speeds were identified accurately regardless of synchronous slip phenomenon. Despite the adhesion theory, three types of operation mode were identified: the stable traction with negligible slip without oscillations, the semi-stable traction with evident slip and oscillations, and the prominent wheel slip. As the wheel speed was measured directly on the wheel, much larger oscillations than ever published were revealed. The source of the oscillations is discussed in the paper. A simple MatLab model of rotational masses was constructed and tuned to match the measurements. Eigen values and eigenvectors of the model are discussed, too. The model of rotational masses is completed with adhesion model to perform simulation. The simulation results are presented and compared with the results of measurement.
Railway Traction Vehicle Longitudinal Velocity Estimation by Kalman Filter
Important task of railway traction vehicles is to achieve maximal traction effort at any conditions if required. For this purpose the vehicles have slip controllers. Some types of this controllers need the vehicle longitudinal velocity value as an input. The vehicle longitudinal velocity is difficult to measure directly because the vehicle longitudinal velocity could not be directly determined from wheel velocity. When the wheel is driven its velocity is higher than the vehicle longitudinal velocity because of the slip phenomenon. The paper describes method that provides possibility to estimate the vehicle velocity on base of measured wheel velocity. Estimation of the vehicle longitudinal velocity is enabled by Kalman filtration. The method is verified by MatLab simulation using real measured data.
Locomotive need a slip controller that ensures tractive effort transmission from wheels to rails. For developing a new slip control method or for modification of existing slip control method it is appropriate to have a model of locomotive and test the slip control method on the model before its implementation to the locomotive. For modelling it is not possible use universal locomotive model because every locomotive have different parameters and mechanical construction. Therefore for every locomotive have to be created a new model. In the paper is described a reduced model of two bogie, four wheelsets locomotive that describes significant mechanical and dynamic properties for slip controller design. The model is created and simulated in MATLAB/SIMULINK.
Measuring Device for Measurement of Train Dynamic Motion During Wheel Slip
For a locomotive wheel slip velocity detection and slip control are typically used measurement sensors that are mounted on the locomotive. The sensors are typically intended for another purpose e.g. wheel speed measurement or tractive effort determination. When the slip control is based on indirect methods that needed to measure some specific locomotive behavior that occurs during high slip velocity it is difficult to use the locomotive measurement sensors. The paper presents an additional experimental measurement device that is mounted on locomotive wheelset to measure the wheelset dynamic motions that typically occur when the wheel has large value of slip velocity. The measurement device is equipped with accelerometers. Measured data are filtered to get signal that can be used for locomotive wheel slip velocity detection and control.
Overview of Slip Control Methods used in Locomotives
Modern locomotives are more powerful and reaches higher speeds. With these parameters increasing it is connected a problem with transmission of tractive effort between vehicle wheels and rails. The maximal value of transmitted force depends on value of the wheel slip velocity and its type of control. In the paper is briefly described problem of the force transmission and some used control methods are described. The simulation in Matlab/Simulink of one method is described too.
Basic study of Slip Control Methods for Railway Traction Vehicles
A slip control is important for every railway traction vehicle. Slip control enables to achieve maximum tractive effort that is important when the vehicle accelerates or going up to hill. The slip control is especially important when conditions on rails are bad. In the paper are described some slip control methods its principles and basic features that uses in railway traction vehicles. A simulation results of method that control slip velocity to achieve maximum value of an adhesion coefficient are presented and basic terms that are related with slip control are described too.
Railways traction vehicles tractive effort mainly depends on an adhesion coefficient. A slip velocity is one parameter that significantly affects a value of adhesion coefficient. The low value of the adhesion coefficient is needed for force transmission between wheel and rail and positively affected the adhesion coefficient value. But when the slip velocity has higher value the value of adhesion coefficient is negatively affected and the rail and rails are excessively worn. Therefore the railways traction vehicles have to have fast and accurate slip controller. In the paper are described force transmission mechanism between wheels and rail, slip control methods. Proposal and simulation of new hybrid slip control method is described too.
Application of DC-DC Converters for Increasing of Power Production from Partially Shaded Photovoltaic String
Nowadays, one common way to build the photovoltaic power plant is by connecting photovoltaic panels in series or parallel to form a string. The string is connected to main grid with an inverter. This conception is appropriate for a case when every panel is irradiated with homogeneous solar radiation. If some photovoltaic panels are shadowed or partially shadowed the string output power is dropped. The similar problem can occur if some photovoltaic panels are oriented in different directions in the case the photovoltaic panels are radiated with different solar radiation. The result is similar to a partial shadowing. The problem can be solved by eliminating the non optional conditions. This is possible for application located in open area. The solution can be difficult to implement in urban areas. Photovoltaic panel may be overshadowed by a cloud cover, trees, chimneys, lightning conductors or other parts of buildings in urban areas. The different orientation cans occur if an installation needs to be split in several cardinals or architectural requests. In this case for maximizing power harvest have to be used an inverter with an advance algorithm for searching a Maximum Power Point or to every photovoltaic panel connects to a DC-DC converter that find a photovoltaic panel Maximum Power Point. The converters are called a microconverters or module integrated converters. The paper describes the microconverter that allows increase photovoltaic panel power harvest when the string photovoltaic panels are partially shadowed.
Converter Regulation of Stand-Alone Photovoltaic System at Low Solar Radiation
The paper presents a control and a power supply of a low power stand-alone photovoltaic system converter. In a stand-alone photovoltaic system load is generally supplied from a photovoltaic panel through a DC-DC converter. In simple photovoltaic system without a battery converter controller and other circuits are supplied from the photovoltaic panel. The systems are appropriate for low power application where continual power supply is not required. The systems have problem in low solar radiation because photovoltaic panel is not able to produce enough energy for running a converter. The proposed converter power supply switching on and regulation behaviour at low solar radiation level are described in the paper. The Matlab/Simulink was used for establishing a photovoltaic panel model and DC-DC converter model before the converter implementation. The converter is a boost type converter with a full-bridge. The modelled and experimental results are presented.
Design of isolated DC-DC photovoltaic microconverter.
Many of photovoltaic systems have serial connected photovoltaic panels. This conception is suitable when every panel has homogeneous solar radiation. If some part of the system is shadowed this part is bypassed by bypass diode which is inside of the panel. In this case can be bypassed many times larger area than is shadowed area and power drop can be disproportionate to the area. There can be used microconverters for increasing power in adverse conditions. The microconverter is a low power converter which is usually connected to one photovoltaic panel. This paper proposes boost converter with full-bridge as a type of isolated microconverter.
Low Power Photovoltaic Converter Control and Development
The paper focuses on design and simulation of the low power inverter for photovoltaic application. In the paper it is briefly discussed the DC/DC converter design for the tracking MPP of the solar array and then the design of the control algorithm for the output inverter is discussed. Both possible operation modes - work in “island mode” and operation in the supply grid are considered and a control
algorithms for them were developed and simulated. Attention is also paid to the design of the output filter for the converter
Implementation of DC-DC Converter Power Supply and Control For Photovoltaic
Start up regulation of realized DC-DC converter for photovoltaic panel are presented in this paper. The Converter has no continuous power from main supply or continuous battery power supply, the converter is only supplied by photovoltaic panel. The regulation using three-point weight comparison method find to Maximum Power Point (MPP) is presented too.
Problematics of the High Compatible Semiconductor Power Converters
The effort to use renewable energy sources increase in these days. The processing of the energy obtained from the sun, wind or water gets to the forefront. The energy supplied by these sources has not constant values, but it fluctuates according to the surrounding conditions (intensity of the sun rays, water flow, etc.). Therefore these supplies are added with additional converters. The most used are AC / DC inverters or DC / DC converters. The aim of this project is to create the laboratory test bed that will pursue with energy acquisition from alternative energy sources. The attention will be paid both to the efficiency of the converters and to the control algorithm of the converter.
Simulation and Implementation of Photovoltaic DC-DC Converter
This paper presents simulation and implementation of DC-DC converter. The converter is connected to a photovoltaic panel. The converter is intended for implementation of various Maximum Power Point Trackers (MPPT). There are described converters and used MPPT in this paper too. Input voltage of the converter is tens of volts and maximal input power is 200 W. This power corresponds to power of a photovoltaic panel. The converter was designed to be connected to an inverter. The inverter input voltage must be more than 400 V because it is connected to single-phase grid without using transformer. This voltage is produced by the DC-DC converter.