Axial position estimation of conical shaped motors for aerospace traction applications

Roggia, S., Cupertino, Francesco, Gerada, C. and Galea, Michael (2017) Axial position estimation of conical shaped motors for aerospace traction applications. IEEE Transactions on Industry Applications, 53 (6). pp. 5405-5414. ISSN 1939-9367

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Abstract

This paper is concerned with the use of conical induction machines. Such machines are extremely valuable when apart from the rotational torque output, an axial translation of the rotor is also required. The inherent attraction between the stator and rotor of any machine, combined with the geometry of a conical machine will provide the required axial movement. However, when applied to aerospace applications, where reliability is very important, then full monitoring of the axial position is required. In this paper, an innovative approach aimed at monitoring and controlling the axial translation of a conical induction machine is proposed and investigated. In order to increase the system reliability and also decrease component count, as demanded by the application, the methodology is a sensor-less technique, based on an innovative variant of the high-frequency injection approach. In this paper, the technique has been fully investigated and experimentally validated on a purposely-built, instrumented test-rig.

Item Type: Article
RIS ID: https://nottingham-repository.worktribe.com/output/867639
Additional Information: © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Keywords: conical motor; sliding rotor; high voltage signal injection; in-wheel actuator
Schools/Departments: University of Nottingham, UK > Faculty of Engineering > Department of Electrical and Electronic Engineering
Identification Number: https://doi.org/10.1109/TIA.2017.2717911
Depositing User: Burns, Rebecca
Date Deposited: 14 Jul 2017 11:08
Last Modified: 04 May 2020 18:51
URI: https://eprints.nottingham.ac.uk/id/eprint/44155

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