Comparison of Differential Evolution and Nelder–Mead Algorithms for Identification of Line-Start Permanent Magnet Synchronous Motor Parameters
Line-start permanent magnet synchronous motors (LSPMSMs) are of great interest to researchers because of their high energy efficiency, due to the growing interest of manufacturers in energy-efficient units. However, LSPMSMs face some difficulties in starting and synchronization processes. The LSPMSM...
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MDPI AG
2023-06-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/13/13/7586 |
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| author | Aleksey Paramonov Safarbek Oshurbekov Vadim Kazakbaev Vladimir Prakht Vladimir Dmitrievskii Victor Goman |
| author_facet | Aleksey Paramonov Safarbek Oshurbekov Vadim Kazakbaev Vladimir Prakht Vladimir Dmitrievskii Victor Goman |
| author_sort | Aleksey Paramonov |
| collection | DOAJ |
| description | Line-start permanent magnet synchronous motors (LSPMSMs) are of great interest to researchers because of their high energy efficiency, due to the growing interest of manufacturers in energy-efficient units. However, LSPMSMs face some difficulties in starting and synchronization processes. The LSPMSM lumped parameter model is applicable to estimating the successfulness of starting and further synchronization. The parameters of such a model can be determined using computer-aided identification algorithms applied to real motor transient processes’ curves. This problem demands significant computational time. A comparison between two algorithms, differential evolution and Nelder–Mead, is presented in this article. The algorithms were used for 0.55 kW, 1500 rpm LSPMSM parameter identification. Moreover, to increase computational speed, it is proposed to stop and restart the algorithms’ procedures, changing their parameters after a certain number of iterations. A significant advantage of the Nelder–Mead algorithm is shown for the solving of the considered problem. |
| first_indexed | 2024-03-11T01:47:02Z |
| format | Article |
| id | doaj.art-55fd14acaa91409aa05c065da5ec9a8b |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T01:47:02Z |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-55fd14acaa91409aa05c065da5ec9a8b2023-11-18T16:08:32ZengMDPI AGApplied Sciences2076-34172023-06-011313758610.3390/app13137586Comparison of Differential Evolution and Nelder–Mead Algorithms for Identification of Line-Start Permanent Magnet Synchronous Motor ParametersAleksey Paramonov0Safarbek Oshurbekov1Vadim Kazakbaev2Vladimir Prakht3Vladimir Dmitrievskii4Victor Goman5Department of Electrical Engineering, Ural Federal University, 620002 Yekaterinburg, RussiaDepartment of Electrical Engineering, Ural Federal University, 620002 Yekaterinburg, RussiaDepartment of Electrical Engineering, Ural Federal University, 620002 Yekaterinburg, RussiaDepartment of Electrical Engineering, Ural Federal University, 620002 Yekaterinburg, RussiaDepartment of Electrical Engineering, Ural Federal University, 620002 Yekaterinburg, RussiaElectromechanical Engineering Technology Department, Abu Dhabi Polytechnic, Abu Dhabi 111499, United Arab EmiratesLine-start permanent magnet synchronous motors (LSPMSMs) are of great interest to researchers because of their high energy efficiency, due to the growing interest of manufacturers in energy-efficient units. However, LSPMSMs face some difficulties in starting and synchronization processes. The LSPMSM lumped parameter model is applicable to estimating the successfulness of starting and further synchronization. The parameters of such a model can be determined using computer-aided identification algorithms applied to real motor transient processes’ curves. This problem demands significant computational time. A comparison between two algorithms, differential evolution and Nelder–Mead, is presented in this article. The algorithms were used for 0.55 kW, 1500 rpm LSPMSM parameter identification. Moreover, to increase computational speed, it is proposed to stop and restart the algorithms’ procedures, changing their parameters after a certain number of iterations. A significant advantage of the Nelder–Mead algorithm is shown for the solving of the considered problem.https://www.mdpi.com/2076-3417/13/13/7586line-start permanent magnet synchronous motorNelder–Mead algorithmdifferential evolution algorithmelectric motorsenergy efficiency classenergy saving |
| spellingShingle | Aleksey Paramonov Safarbek Oshurbekov Vadim Kazakbaev Vladimir Prakht Vladimir Dmitrievskii Victor Goman Comparison of Differential Evolution and Nelder–Mead Algorithms for Identification of Line-Start Permanent Magnet Synchronous Motor Parameters Applied Sciences line-start permanent magnet synchronous motor Nelder–Mead algorithm differential evolution algorithm electric motors energy efficiency class energy saving |
| title | Comparison of Differential Evolution and Nelder–Mead Algorithms for Identification of Line-Start Permanent Magnet Synchronous Motor Parameters |
| title_full | Comparison of Differential Evolution and Nelder–Mead Algorithms for Identification of Line-Start Permanent Magnet Synchronous Motor Parameters |
| title_fullStr | Comparison of Differential Evolution and Nelder–Mead Algorithms for Identification of Line-Start Permanent Magnet Synchronous Motor Parameters |
| title_full_unstemmed | Comparison of Differential Evolution and Nelder–Mead Algorithms for Identification of Line-Start Permanent Magnet Synchronous Motor Parameters |
| title_short | Comparison of Differential Evolution and Nelder–Mead Algorithms for Identification of Line-Start Permanent Magnet Synchronous Motor Parameters |
| title_sort | comparison of differential evolution and nelder mead algorithms for identification of line start permanent magnet synchronous motor parameters |
| topic | line-start permanent magnet synchronous motor Nelder–Mead algorithm differential evolution algorithm electric motors energy efficiency class energy saving |
| url | https://www.mdpi.com/2076-3417/13/13/7586 |
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