Abstract
Optimizing the design of electric machines is a vital step in ensuring the economical use of active materials. The three-dimensional flux paths in axial flux PM (AFPM) machines necessitate the use of computationally expensive 3D electromagnetic analysis. Furthermore, a large number of design evaluations is required to find the optimum, causing the total computation time to be excessively long. In view of this, a two-level surrogate assisted algorithm capable of handling such expensive optimization problems is introduced, which substantially reduces the number of FEA evaluations. The proposed algorithm is employed to optimally design an AFPM machine within a specified envelope, identifying the limits of cost and efficiency. Optimized designs with different rotor polarities are systematically compared in order to form the basis for a set of generalized design rules.
Original language | English |
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Title of host publication | 2018 IEEE Energy Conversion Congress and Exposition, ECCE 2018 |
Pages | 3272-3277 |
Number of pages | 6 |
ISBN (Electronic) | 9781479973118 |
DOIs | |
State | Published - Dec 3 2018 |
Event | 10th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2018 - Portland, United States Duration: Sep 23 2018 → Sep 27 2018 |
Publication series
Name | 2018 IEEE Energy Conversion Congress and Exposition, ECCE 2018 |
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Conference
Conference | 10th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2018 |
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Country/Territory | United States |
City | Portland |
Period | 9/23/18 → 9/27/18 |
Bibliographical note
Publisher Copyright:© 2018 IEEE.
Keywords
- Axial flux permanent magnet
- Multi-objective
- Number of poles
- Optimization
- SPM
- Surrogate assisted
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Renewable Energy, Sustainability and the Environment
- Control and Optimization
- Computer Networks and Communications
- Hardware and Architecture
- Information Systems and Management