Research on online optimization scheme and deployment of PMSM control parameters based on honey badger algorithm
Abstract Permanent magnet synchronous motor (PMSM) drive systems are receiving increasing attention due to their superior control quality and efficiency. Optimizing the control parameters are key to achieve the high-performance operation of PMSMs. Although heuristic algorithms demonstrate excellent...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-11-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-77225-9 |
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| _version_ | 1846172105156067328 |
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| author | Xiaofeng Zhu Yiming Hu Yinquan Yu Dequan Zeng Jinwen Yang Giuseppe Carbone |
| author_facet | Xiaofeng Zhu Yiming Hu Yinquan Yu Dequan Zeng Jinwen Yang Giuseppe Carbone |
| author_sort | Xiaofeng Zhu |
| collection | DOAJ |
| description | Abstract Permanent magnet synchronous motor (PMSM) drive systems are receiving increasing attention due to their superior control quality and efficiency. Optimizing the control parameters are key to achieve the high-performance operation of PMSMs. Although heuristic algorithms demonstrate excellent optimization outcomes in simulations, there are still challenges in deploying optimization schemes in practical drives. In this study, a real-time online deployable control parameter optimization scheme is proposed. The optimization effect is evaluated through the system step response performance, and a framework for deploying optimization algorithms within the driver is developed. A fault suppression mechanism is also designed to mitigate overshoot and vibration issues caused by suboptimal solutions. The proposed scheme is validated on a rapid prototyping control platform. Experimental results confirm that the scheme exhibits good optimization performances across various operating conditions. The honey badger algorithm employed in this paper shows faster convergence and more stable optimization effects than other optimization algorithms. The optimization effect is improved by 2.2% and its performance in terms of consistency across multiple optimization results has increased by 40%. |
| format | Article |
| id | doaj-art-716399da669d4b7d8379deb7182e17e5 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-716399da669d4b7d8379deb7182e17e52024-11-10T12:18:05ZengNature PortfolioScientific Reports2045-23222024-11-0114111910.1038/s41598-024-77225-9Research on online optimization scheme and deployment of PMSM control parameters based on honey badger algorithmXiaofeng Zhu0Yiming Hu1Yinquan Yu2Dequan Zeng3Jinwen Yang4Giuseppe Carbone5School of Mechatronics and Vehicle Engineering, East China Jiaotong UniversitySchool of Mechatronics and Vehicle Engineering, East China Jiaotong UniversitySchool of Mechatronics and Vehicle Engineering, East China Jiaotong UniversitySchool of Mechatronics and Vehicle Engineering, East China Jiaotong UniversitySchool of Mechatronics and Vehicle Engineering, East China Jiaotong UniversityDepartment of Mechanical, Energy, and Management Engineering, University of CalabriaAbstract Permanent magnet synchronous motor (PMSM) drive systems are receiving increasing attention due to their superior control quality and efficiency. Optimizing the control parameters are key to achieve the high-performance operation of PMSMs. Although heuristic algorithms demonstrate excellent optimization outcomes in simulations, there are still challenges in deploying optimization schemes in practical drives. In this study, a real-time online deployable control parameter optimization scheme is proposed. The optimization effect is evaluated through the system step response performance, and a framework for deploying optimization algorithms within the driver is developed. A fault suppression mechanism is also designed to mitigate overshoot and vibration issues caused by suboptimal solutions. The proposed scheme is validated on a rapid prototyping control platform. Experimental results confirm that the scheme exhibits good optimization performances across various operating conditions. The honey badger algorithm employed in this paper shows faster convergence and more stable optimization effects than other optimization algorithms. The optimization effect is improved by 2.2% and its performance in terms of consistency across multiple optimization results has increased by 40%.https://doi.org/10.1038/s41598-024-77225-9PMSMHoney badger algorithmMetaheuristic algorithmsOnline optimizationControl parameter optimizationControl failure suppression |
| spellingShingle | Xiaofeng Zhu Yiming Hu Yinquan Yu Dequan Zeng Jinwen Yang Giuseppe Carbone Research on online optimization scheme and deployment of PMSM control parameters based on honey badger algorithm Scientific Reports PMSM Honey badger algorithm Metaheuristic algorithms Online optimization Control parameter optimization Control failure suppression |
| title | Research on online optimization scheme and deployment of PMSM control parameters based on honey badger algorithm |
| title_full | Research on online optimization scheme and deployment of PMSM control parameters based on honey badger algorithm |
| title_fullStr | Research on online optimization scheme and deployment of PMSM control parameters based on honey badger algorithm |
| title_full_unstemmed | Research on online optimization scheme and deployment of PMSM control parameters based on honey badger algorithm |
| title_short | Research on online optimization scheme and deployment of PMSM control parameters based on honey badger algorithm |
| title_sort | research on online optimization scheme and deployment of pmsm control parameters based on honey badger algorithm |
| topic | PMSM Honey badger algorithm Metaheuristic algorithms Online optimization Control parameter optimization Control failure suppression |
| url | https://doi.org/10.1038/s41598-024-77225-9 |
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