Optimal drive cycle current supply of a wound field automotive electrical machine using surrogate models
Surrogate models have become a widely used solution for reducing computation times along design processes. In this work, a Gaussian Process surrogate model is built and used to predict the performance and losses of a wound field electrical machine in a fast manner. This approach is relevant, especia...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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EDP Sciences
2024-01-01
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| Series: | Science and Technology for Energy Transition |
| Subjects: | |
| Online Access: | https://www.stet-review.org/articles/stet/full_html/2024/01/stet20230174/stet20230174.html |
| _version_ | 1797343553366523904 |
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| author | Mazloum Rebecca Hlioui Sami Laurent Luc Belhadi M’Hamed Mermaz-Rollet Guillaume Gabsi Mohamed |
| author_facet | Mazloum Rebecca Hlioui Sami Laurent Luc Belhadi M’Hamed Mermaz-Rollet Guillaume Gabsi Mohamed |
| author_sort | Mazloum Rebecca |
| collection | DOAJ |
| description | Surrogate models have become a widely used solution for reducing computation times along design processes. In this work, a Gaussian Process surrogate model is built and used to predict the performance and losses of a wound field electrical machine in a fast manner. This approach is relevant, especially for drive cycle calculations that rapidly generate rising computation costs if they are computed using physical models, especially finite elements analysis. We present in detail the established method and a comparison of the obtained results with finite elements results. In addition, a detailed analysis of the optimized current supply is presented, and the advantages of variable excitation current are highlighted. |
| first_indexed | 2024-03-08T10:49:21Z |
| format | Article |
| id | doaj.art-857258e86d2d41c3ba928139ff4bc45f |
| institution | Directory Open Access Journal |
| issn | 2804-7699 |
| language | English |
| last_indexed | 2024-03-08T10:49:21Z |
| publishDate | 2024-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | Science and Technology for Energy Transition |
| spelling | doaj.art-857258e86d2d41c3ba928139ff4bc45f2024-01-26T16:50:25ZengEDP SciencesScience and Technology for Energy Transition2804-76992024-01-0179210.2516/stet/2023041stet20230174Optimal drive cycle current supply of a wound field automotive electrical machine using surrogate modelsMazloum Rebecca0Hlioui Sami1Laurent Luc2https://orcid.org/0000-0002-8935-5929Belhadi M’Hamed3Mermaz-Rollet Guillaume4Gabsi Mohamed5SATIE Laboratory, Stellantis and Paris Saclay UniversitySATIE Laboratory, CY Cergy Paris UniversityLMSSC, Cnam, HESAM UniversityStellantisStellantisSATIE, Paris Saclay UniversitySurrogate models have become a widely used solution for reducing computation times along design processes. In this work, a Gaussian Process surrogate model is built and used to predict the performance and losses of a wound field electrical machine in a fast manner. This approach is relevant, especially for drive cycle calculations that rapidly generate rising computation costs if they are computed using physical models, especially finite elements analysis. We present in detail the established method and a comparison of the obtained results with finite elements results. In addition, a detailed analysis of the optimized current supply is presented, and the advantages of variable excitation current are highlighted.https://www.stet-review.org/articles/stet/full_html/2024/01/stet20230174/stet20230174.htmldrive cycleelectrical machineexcitation currentgaussian processmetamodeling |
| spellingShingle | Mazloum Rebecca Hlioui Sami Laurent Luc Belhadi M’Hamed Mermaz-Rollet Guillaume Gabsi Mohamed Optimal drive cycle current supply of a wound field automotive electrical machine using surrogate models Science and Technology for Energy Transition drive cycle electrical machine excitation current gaussian process metamodeling |
| title | Optimal drive cycle current supply of a wound field automotive electrical machine using surrogate models |
| title_full | Optimal drive cycle current supply of a wound field automotive electrical machine using surrogate models |
| title_fullStr | Optimal drive cycle current supply of a wound field automotive electrical machine using surrogate models |
| title_full_unstemmed | Optimal drive cycle current supply of a wound field automotive electrical machine using surrogate models |
| title_short | Optimal drive cycle current supply of a wound field automotive electrical machine using surrogate models |
| title_sort | optimal drive cycle current supply of a wound field automotive electrical machine using surrogate models |
| topic | drive cycle electrical machine excitation current gaussian process metamodeling |
| url | https://www.stet-review.org/articles/stet/full_html/2024/01/stet20230174/stet20230174.html |
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