Few‐sample multi‐objective optimisation of a double‐sided tubular machine with hybrid segmented permanent magnet
Abstract Double‐sided tubular machine (DSTM) is very suitable for wave energy conversion but easily suffers from high thrust ripple. In order to get the minimum cogging force with the maximum thrust force, a new DSTM with hybrid segmented permanent magnet array is proposed and optimised by a novel i...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-09-01
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| Series: | IET Electric Power Applications |
| Online Access: | https://doi.org/10.1049/elp2.12202 |
| _version_ | 1828183814499729408 |
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| author | Liang Guo Mian Weng Michael Galea Xiaowen Wu Peng Zhang Wenqi Lu |
| author_facet | Liang Guo Mian Weng Michael Galea Xiaowen Wu Peng Zhang Wenqi Lu |
| author_sort | Liang Guo |
| collection | DOAJ |
| description | Abstract Double‐sided tubular machine (DSTM) is very suitable for wave energy conversion but easily suffers from high thrust ripple. In order to get the minimum cogging force with the maximum thrust force, a new DSTM with hybrid segmented permanent magnet array is proposed and optimised by a novel iterative few‐sample multi‐objective optimisation method. The novel optimisation method is based on an iterative Taguchi method framework to obtain optimal design with only few samples. To solve the low precision problem of the iterative Taguchi method, a surrogate‐model based multi‐objective optimisation algorithm that uses a general regression neural network, a speed‐constrained multi‐objective particle swarm optimisation and an exponentially weighted moving average are embedded into this framework. The optimisation result is compared with other alternative topologies and methods, and a prototype is manufactured for testing experiment. |
| first_indexed | 2024-04-12T06:37:20Z |
| format | Article |
| id | doaj.art-d3296f2ac6b348ae8a4c97e36ae2c3f6 |
| institution | Directory Open Access Journal |
| issn | 1751-8660 1751-8679 |
| language | English |
| last_indexed | 2024-04-12T06:37:20Z |
| publishDate | 2022-09-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Electric Power Applications |
| spelling | doaj.art-d3296f2ac6b348ae8a4c97e36ae2c3f62022-12-22T03:43:49ZengWileyIET Electric Power Applications1751-86601751-86792022-09-0116995396510.1049/elp2.12202Few‐sample multi‐objective optimisation of a double‐sided tubular machine with hybrid segmented permanent magnetLiang Guo0Mian Weng1Michael Galea2Xiaowen Wu3Peng Zhang4Wenqi Lu5Faculty of Mechanical Engineering and Automation Zhejiang Sci‐Tech University Hangzhou ChinaFaculty of Mechanical Engineering and Automation Zhejiang Sci‐Tech University Hangzhou ChinaDepartment of Industrial Electrical Power Conversion University of Malta Msida MaltaZhejiang Fangyuan Test Group CO., LTD Hangzhou ChinaZhejiang Fangyuan Test Group CO., LTD Hangzhou ChinaFaculty of Mechanical Engineering and Automation Zhejiang Sci‐Tech University Hangzhou ChinaAbstract Double‐sided tubular machine (DSTM) is very suitable for wave energy conversion but easily suffers from high thrust ripple. In order to get the minimum cogging force with the maximum thrust force, a new DSTM with hybrid segmented permanent magnet array is proposed and optimised by a novel iterative few‐sample multi‐objective optimisation method. The novel optimisation method is based on an iterative Taguchi method framework to obtain optimal design with only few samples. To solve the low precision problem of the iterative Taguchi method, a surrogate‐model based multi‐objective optimisation algorithm that uses a general regression neural network, a speed‐constrained multi‐objective particle swarm optimisation and an exponentially weighted moving average are embedded into this framework. The optimisation result is compared with other alternative topologies and methods, and a prototype is manufactured for testing experiment.https://doi.org/10.1049/elp2.12202 |
| spellingShingle | Liang Guo Mian Weng Michael Galea Xiaowen Wu Peng Zhang Wenqi Lu Few‐sample multi‐objective optimisation of a double‐sided tubular machine with hybrid segmented permanent magnet IET Electric Power Applications |
| title | Few‐sample multi‐objective optimisation of a double‐sided tubular machine with hybrid segmented permanent magnet |
| title_full | Few‐sample multi‐objective optimisation of a double‐sided tubular machine with hybrid segmented permanent magnet |
| title_fullStr | Few‐sample multi‐objective optimisation of a double‐sided tubular machine with hybrid segmented permanent magnet |
| title_full_unstemmed | Few‐sample multi‐objective optimisation of a double‐sided tubular machine with hybrid segmented permanent magnet |
| title_short | Few‐sample multi‐objective optimisation of a double‐sided tubular machine with hybrid segmented permanent magnet |
| title_sort | few sample multi objective optimisation of a double sided tubular machine with hybrid segmented permanent magnet |
| url | https://doi.org/10.1049/elp2.12202 |
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