Design and modelling techniques for performance improvement of synchronous reluctance machines

The design of electric machines constitutes a complex optimization problem subject to target application and performance requirements. State-of-the-art design routines generally start with adaption of a certain geometry followed by an optimization process. An optimization process has its own challen...

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Main Author: Korman, Oguz
Format: Thesis (University of Nottingham only)
Language:English
Published: 2024
Subjects:
Online Access:https://eprints.nottingham.ac.uk/77620/
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author Korman, Oguz
author_facet Korman, Oguz
author_sort Korman, Oguz
building Nottingham Research Data Repository
collection Online Access
description The design of electric machines constitutes a complex optimization problem subject to target application and performance requirements. State-of-the-art design routines generally start with adaption of a certain geometry followed by an optimization process. An optimization process has its own challenges as it shows sensitive behaviour to objectives and constraints. When the optimization problem is an electric machine design, challenge only becomes more sophisticated. Existence of non-linearity due to magnetic materials and performance requirements which more than often contradicts, requires proper handling of the optimization process. This is particularly a problem for more complex machine topologies such as synchronous reluctance (SynRel) and internal permanent magnet (IPM) machines. Besides reaching the optimum geometry, optimality of the selected geometry itself is another uncertainty. This is particularly puzzling especially at the early design stages when a lot of machine parameters are still not selected (such as number of slots and poles). Assessment of the machine parameters along with the geometry then becomes a tangled and time consuming process if a fast analysis tool is missing. This thesis puts these concerns to its center and orbits around them separately. In the beginning, focus is spent on geometric parametrization of the Syn-Rel machine. Once this is achieved, the effecs of the objectives selection during an optimization are investigated. This is later followed by an improved geometric parametrization with the aim of increasing the degrees of freedom. Optimizations are performed to compare existing and newly proposed geometry to contribute towards a more optimal geometry. One of the designs achieved with the optimizations is manufactured and experimentally validated. After that, geometric parametrization is put aside and topology optimization (TO) is used to widen SynRel design space. Since the only parameters with the TO are optimization settings themselves, their effect on the results are deeply examined. Viability of using TO as a design refinement tool is also analyzed by selecting an already optimized design space. In the final part, computational burden of the design processes are addressed through building a highly accurate and fast magnetic equivalent circuit (MEC). The description and principles of this fast analysis technique is presented and it is used to analyze three different machines, namely a SynRel machine, a surface permanent magnet (SPM) machine and a permanent magnet assisted synchronous reluctance machine (PMaSynRel). Through comparisons against finite element analysis (FEA), accuracy of the MEC is proved. As a last remark, an off-the-shelf SynRel machine is tested to obtain its electromagnetic properties and they are used to asses performance of the MEC.
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format Thesis (University of Nottingham only)
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spelling nottingham-776202025-02-28T15:20:18Z https://eprints.nottingham.ac.uk/77620/ Design and modelling techniques for performance improvement of synchronous reluctance machines Korman, Oguz The design of electric machines constitutes a complex optimization problem subject to target application and performance requirements. State-of-the-art design routines generally start with adaption of a certain geometry followed by an optimization process. An optimization process has its own challenges as it shows sensitive behaviour to objectives and constraints. When the optimization problem is an electric machine design, challenge only becomes more sophisticated. Existence of non-linearity due to magnetic materials and performance requirements which more than often contradicts, requires proper handling of the optimization process. This is particularly a problem for more complex machine topologies such as synchronous reluctance (SynRel) and internal permanent magnet (IPM) machines. Besides reaching the optimum geometry, optimality of the selected geometry itself is another uncertainty. This is particularly puzzling especially at the early design stages when a lot of machine parameters are still not selected (such as number of slots and poles). Assessment of the machine parameters along with the geometry then becomes a tangled and time consuming process if a fast analysis tool is missing. This thesis puts these concerns to its center and orbits around them separately. In the beginning, focus is spent on geometric parametrization of the Syn-Rel machine. Once this is achieved, the effecs of the objectives selection during an optimization are investigated. This is later followed by an improved geometric parametrization with the aim of increasing the degrees of freedom. Optimizations are performed to compare existing and newly proposed geometry to contribute towards a more optimal geometry. One of the designs achieved with the optimizations is manufactured and experimentally validated. After that, geometric parametrization is put aside and topology optimization (TO) is used to widen SynRel design space. Since the only parameters with the TO are optimization settings themselves, their effect on the results are deeply examined. Viability of using TO as a design refinement tool is also analyzed by selecting an already optimized design space. In the final part, computational burden of the design processes are addressed through building a highly accurate and fast magnetic equivalent circuit (MEC). The description and principles of this fast analysis technique is presented and it is used to analyze three different machines, namely a SynRel machine, a surface permanent magnet (SPM) machine and a permanent magnet assisted synchronous reluctance machine (PMaSynRel). Through comparisons against finite element analysis (FEA), accuracy of the MEC is proved. As a last remark, an off-the-shelf SynRel machine is tested to obtain its electromagnetic properties and they are used to asses performance of the MEC. 2024-07-18 Thesis (University of Nottingham only) NonPeerReviewed application/pdf en cc_by https://eprints.nottingham.ac.uk/77620/1/Korman_Oguz_20213226_corrections.pdf Korman, Oguz (2024) Design and modelling techniques for performance improvement of synchronous reluctance machines. PhD thesis, University of Nottingham. Electric machine design; Optimization process; Complex machine topologies; Machine parameters; Geometric parametrization; Fast analysis technique; Magnetic equivalent circuit
spellingShingle Electric machine design; Optimization process; Complex machine topologies; Machine parameters; Geometric parametrization; Fast analysis technique; Magnetic equivalent circuit
Korman, Oguz
Design and modelling techniques for performance improvement of synchronous reluctance machines
title Design and modelling techniques for performance improvement of synchronous reluctance machines
title_full Design and modelling techniques for performance improvement of synchronous reluctance machines
title_fullStr Design and modelling techniques for performance improvement of synchronous reluctance machines
title_full_unstemmed Design and modelling techniques for performance improvement of synchronous reluctance machines
title_short Design and modelling techniques for performance improvement of synchronous reluctance machines
title_sort design and modelling techniques for performance improvement of synchronous reluctance machines
topic Electric machine design; Optimization process; Complex machine topologies; Machine parameters; Geometric parametrization; Fast analysis technique; Magnetic equivalent circuit
url https://eprints.nottingham.ac.uk/77620/