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Measuring systems for active steering of railway vehicles

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thesis
posted on 2010-10-21, 15:03 authored by Hong Li
This thesis studies measuring systems for active steering of railway vehicles. The aim of the study is to develop state estimation techniques to provide high integrity feedback variables for the active steering of railway vehicles. Practicality and provision of high-integrity data are two important aspects of the work. To avoid the use of expensive sensors and complex instrumentation, practical techniques for estimating vehicle variables are developed where only economical measurements are used and they can be easily implemented. The conventional solid-axle wheelset and wheelset with independently-rotating wheels are studied and their mathematical models are developed. The fundamental stability problem of these two models is analysed from a control engineering viewpoint for studies of actively-controlled wheelsets. The Kalman filters are then developed for these models to estimate all state variables, particularly variables of the wheelset relative to the track such as lateral displacement and yaw angle which are needed for active control. A number of sensing options are also identified, analysed for performance and assessed in a comparative sense. Fault detection and isolation schemes are then studied for the estimation techniques developed. Finally, some applications are considered. The techniques and analysis methods developed for the single wheel pair are extended and applied to a MKII coach and a two-axle railway vehicle. The estimation of cant deficiency for tilting trains is explored, and also the possibility of state estimation for a real profiled wheel.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Publisher

© Hong Li

Publication date

2001

Notes

A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy of Loughborough University.

EThOS Persistent ID

uk.bl.ethos.247888

Language

  • en

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    Mechanical, Electrical and Manufacturing Engineering Theses

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