Abstract
A new modeling framework and optimization approach is proposed for co-optimization of both switched reluctance machine (SRM) design and control across the entire torque-speed range. Custom modeling codes use static finite element analysis (FEA) results to determine optimal current profiles and conventional control conditions for discrete speeds, torques, and torque ripple levels. A machine design optimization method is proposed that leverages outputs from control optimization and determines quality metrics for each design based on the efficiency and torque ripple across the operation envelope. Simulations are validated through empirical testing across the entire torque-speed operation range as comparisons of transient FEA, custom models, and tests are presented.
Original language | English |
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Title of host publication | 2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9798350398991 |
DOIs | |
State | Published - 2023 |
Event | 2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023 - San Francisco, United States Duration: May 15 2023 → May 18 2023 |
Publication series
Name | 2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023 |
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Conference
Conference | 2023 IEEE International Electric Machines and Drives Conference, IEMDC 2023 |
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Country/Territory | United States |
City | San Francisco |
Period | 05/15/23 → 05/18/23 |
Funding
This manuscript has been authored by Oak Ridge National Laboratory, operated by UT-Battelle, LLC, under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).
Keywords
- Switched reluctance machine
- machine design and control optimization