Instantaneous electromagnetic torque waveform calculations for switched reluctance machines exploiting vector analysis
Instantaneous electromagnetic torque waveform calculations for switched reluctance machines exploiting vector analysis
Switched reluctance (SR) machines are magnetically non-linear electromechanical devices and their full and accurate performance prediction—especially of the instantaneous electromagnetic torque waveforms—is not amenable to closed-form analytical solutions. Consequently, the analysis of such machines is usually performed with the aid of computer-based numerical simulations that—even if providing good accuracy—do not offer physical insight into the electromagnetic energy conversion processes taking place inside the machine. For this reason, the SR machine design and analysis are not simple exercises as they require substantial computational resources and extensive prior design expertise. In this article, a methodology for a reasonably accurate prediction of the instantaneous electromagnetic torque waveforms of the SR machines is proposed using a closed-form analytical solution. The suggested approach relies on a simple vector analysis of the flux-linkage map of a non-linear SR machine and as such avoids integration, non-linear curve fitting, or geometrical series summation. The proposed vector-analysis-based methodology offers intuitive physical insight into the electromagnetic energy conversion processes taking place inside the SR machine related to the instantaneous torque generation.
Instantaneous electromagnetic torque, switched reluctance (SR) machines, tractive electromagnets, vector analysis
Stuikys, Aleksas
1c8d9a3b-e9a5-435b-a765-507d1bde5c51
Zaghari, Bahareh
a0537db6-0dce-49a2-8103-0f4599ab5f6a
Sykulski, Jan K.
d6885caf-aaed-4d12-9ef3-46c4c3bbd7fb
1 January 2021
Stuikys, Aleksas
1c8d9a3b-e9a5-435b-a765-507d1bde5c51
Zaghari, Bahareh
a0537db6-0dce-49a2-8103-0f4599ab5f6a
Sykulski, Jan K.
d6885caf-aaed-4d12-9ef3-46c4c3bbd7fb
Stuikys, Aleksas, Zaghari, Bahareh and Sykulski, Jan K.
(2021)
Instantaneous electromagnetic torque waveform calculations for switched reluctance machines exploiting vector analysis.
IEEE Transactions on Magnetics, 57 (1), [9241795].
(doi:10.1109/TMAG.2020.3034565).
Abstract
Switched reluctance (SR) machines are magnetically non-linear electromechanical devices and their full and accurate performance prediction—especially of the instantaneous electromagnetic torque waveforms—is not amenable to closed-form analytical solutions. Consequently, the analysis of such machines is usually performed with the aid of computer-based numerical simulations that—even if providing good accuracy—do not offer physical insight into the electromagnetic energy conversion processes taking place inside the machine. For this reason, the SR machine design and analysis are not simple exercises as they require substantial computational resources and extensive prior design expertise. In this article, a methodology for a reasonably accurate prediction of the instantaneous electromagnetic torque waveforms of the SR machines is proposed using a closed-form analytical solution. The suggested approach relies on a simple vector analysis of the flux-linkage map of a non-linear SR machine and as such avoids integration, non-linear curve fitting, or geometrical series summation. The proposed vector-analysis-based methodology offers intuitive physical insight into the electromagnetic energy conversion processes taking place inside the SR machine related to the instantaneous torque generation.
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Instantaneous Electromagnetic Torque
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e-pub ahead of print date: 28 October 2020
Published date: 1 January 2021
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Funding Information:
ACKNOWLEDGMENT This work was supported in part by the U.K. Engineering and Physical Sciences Research Council (EPSRC) under Grant EP/P010164/1.
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© 1965-2012 IEEE.
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Copyright 2020 Elsevier B.V., All rights reserved.
Keywords:
Instantaneous electromagnetic torque, switched reluctance (SR) machines, tractive electromagnets, vector analysis
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Local EPrints ID: 446950
URI: http://eprints.soton.ac.uk/id/eprint/446950
ISSN: 0018-9464
PURE UUID: 359a3ff4-f3a2-4086-82e9-320c33c5e9f6
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Date deposited: 26 Feb 2021 17:34
Last modified: 21 Sep 2024 01:54
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Author:
Aleksas Stuikys
Author:
Bahareh Zaghari
Author:
Jan K. Sykulski
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