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University of Sindh Journal of Information and Communication Technology (USJICT)

Volume 1, Issue 1, October 2017


ISSN: 2521-5582

Website: Published by University of Sindh, Jamshoro.



Observer Based Slip Measurement Technique of DC Motor Mounted on Railway Wheel-set


Shahzor Memon1, Riaz Uddin2 , Imtiaz Hussain Kalwar3 , Kamran Kazi4

1Department of Electronic Engineering, Hamdard University Karachi, Pakistan

([email protected])

2Department of Electrical Engineering, NED University of Engineering and Technology, Karachi-75270, Pakistan ([email protected])

3Department of Electrical Engineering, DHA Suffa University Karachi Pakistan

([email protected])

4Department of Electronic Engineering, Mehran University of Engineering and Technology, Jamshoro Pakistan

([email protected])



Abstract: The paper proposes the technique of detection and estimation of slip by using parameters of motor such as torque and current for a locomotive system. The motor is used for controlling wheel-set motion mounted on each axle of the rail. As the track condition changes (due to decrease in adhesion/friction), the parameter of motor considerably varies resulting slip occurrence. By utilizing inertial mounted sensors (such as tachometer) in order to measure the velocity of the train, slip can be detected. Furthermore, the estimation of motor parameters is carried out using Kalman filter, which minimizes the usage of additional sensors. In this regard, the proposed method offers a cost effective, accurate and robust solution for the slip issue in order to avoid accidents in locomotive systems. The technique is validated using simulation results in this paper.



Keywords: Locomotive, Slip, Detection, Estimation, Kalman Filter, Rail.



                                                                                                                                                     I.          Introduction

Low adhesion (friction) problem has been spotted a vital parameter to be considered from the beginning of railway transportation for the designing and operation of railway vehicles [3]. The weather effect especially autumn drastically disturbs the adhesion level in which decomposed leaves are crushed by the wheels of the train. In this condition, applying a higher force on the track by the wheel cause wheels-slip during traction and it is subjected to slide while braking, which may be responsible as the damage of track and wheels itself. Various techniques are adopted around the world to overcome this issue, the few of them used (temporarily)are as: (i) vegetation, (ii) sandites (iii) water jetting management [2]. Hence from these methods, the designers still could not get the comprehensive results in order to reduce the adhesion because of the highly non-linearity of adhesion variations most of the time. Therefore, it is difficult to monitor and calculate it exactly and it may certainly desire some level of technical expertise to introduce a solid and appropriate technique to deal with this problem.

In this paper, a wheel-set model is under observation and assessment is made on the basis of comparison between its dynamics under stable condition and slip condition. The information of slip can be acquired from motor parameters such as torque/current connected with each axel of rail as shown in Figure 1. In addition, Kalman filter is used in order to get the accurate estimation of torque/current. Once torque/current is estimated we can ultimately measure that how much slip is occurred during traction.

The remaining paper such as section II comprises of rail wheel-set. Section III presents the modeling of system dynamics. Section IV states the details of estimation of slip using Kalman filter. Section V shows the simulation results. Finally, section VI concludes the proposed method.



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Copyright (c) 2017 Shahzor Memon

ISSN-E: 2523-1235, ISSN-P: 2521-5582

 Copyright © University of Sindh, Jamshoro. 2017 All Rights Reserved.  
Printing and Publication by: Sindh University Press. 

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University of Sindh, Jamshoro, Sindh, Pakistan. 76080