Analysis of inductive power transfer systems by metamodeling techniques
This paper presents some metamodeling techniques to analyze the variability of the performances of an inductive power transfer (IPT) system, considering the sources of uncertainty (misalignment between the coils, the variation in air gap, and the rotation on the receiver). For IPT systems, one of th...
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| Format: | Article |
| Language: | English |
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Académie des sciences
2024-08-01
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| Series: | Comptes Rendus. Physique |
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| Online Access: | https://comptes-rendus.academie-sciences.fr/physique/articles/10.5802/crphys.188/ |
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| author | Pei, Yao Pichon, Lionel Bensetti, Mohamed Le Bihan, Yann |
| author_facet | Pei, Yao Pichon, Lionel Bensetti, Mohamed Le Bihan, Yann |
| author_sort | Pei, Yao |
| collection | DOAJ |
| description | This paper presents some metamodeling techniques to analyze the variability of the performances of an inductive power transfer (IPT) system, considering the sources of uncertainty (misalignment between the coils, the variation in air gap, and the rotation on the receiver). For IPT systems, one of the key issues is transmission efficiency, which is greatly influenced by many sources of uncertainty. So, it is meaningful to find a metamodeling technique to quickly evaluate the system’s performances. According to the comparison of Support Vector Regression, Multigene Genetic Programming Algorithm, and sparse Polynomial Chaos Expansions (PCE), sparse PCE is recommended for the analysis due to the tradeoff between the computational time and the accuracy of the metamodel. |
| format | Article |
| id | doaj-art-21642766a3ee419993539cc1b9b529f0 |
| institution | Kabale University |
| issn | 1878-1535 |
| language | English |
| publishDate | 2024-08-01 |
| publisher | Académie des sciences |
| record_format | Article |
| series | Comptes Rendus. Physique |
| spelling | doaj-art-21642766a3ee419993539cc1b9b529f02025-02-07T13:53:29ZengAcadémie des sciencesComptes Rendus. Physique1878-15352024-08-0125S112513910.5802/crphys.18810.5802/crphys.188Analysis of inductive power transfer systems by metamodeling techniquesPei, Yao0https://orcid.org/0000-0003-0099-4001Pichon, Lionel1https://orcid.org/0000-0002-3402-5498Bensetti, Mohamed2https://orcid.org/0000-0002-4755-5113Le Bihan, Yann3https://orcid.org/0000-0001-5563-9192Sorbonne Université, CNRS, Laboratoire de Génie Electrique et Electronique de Paris, 75252, Paris, France; Université Paris-Saclay, CentraleSupélec, CNRS, Laboratoire de Génie Electrique et Electronique de Paris, 91192, Gif-sur-Yvette, FranceSorbonne Université, CNRS, Laboratoire de Génie Electrique et Electronique de Paris, 75252, Paris, France; Université Paris-Saclay, CentraleSupélec, CNRS, Laboratoire de Génie Electrique et Electronique de Paris, 91192, Gif-sur-Yvette, FranceSorbonne Université, CNRS, Laboratoire de Génie Electrique et Electronique de Paris, 75252, Paris, France; Université Paris-Saclay, CentraleSupélec, CNRS, Laboratoire de Génie Electrique et Electronique de Paris, 91192, Gif-sur-Yvette, FranceSorbonne Université, CNRS, Laboratoire de Génie Electrique et Electronique de Paris, 75252, Paris, France; Université Paris-Saclay, CentraleSupélec, CNRS, Laboratoire de Génie Electrique et Electronique de Paris, 91192, Gif-sur-Yvette, FranceThis paper presents some metamodeling techniques to analyze the variability of the performances of an inductive power transfer (IPT) system, considering the sources of uncertainty (misalignment between the coils, the variation in air gap, and the rotation on the receiver). For IPT systems, one of the key issues is transmission efficiency, which is greatly influenced by many sources of uncertainty. So, it is meaningful to find a metamodeling technique to quickly evaluate the system’s performances. According to the comparison of Support Vector Regression, Multigene Genetic Programming Algorithm, and sparse Polynomial Chaos Expansions (PCE), sparse PCE is recommended for the analysis due to the tradeoff between the computational time and the accuracy of the metamodel.https://comptes-rendus.academie-sciences.fr/physique/articles/10.5802/crphys.188/Wireless power transferMetamodelsPolynomial chaos expansionsSupport vector regressionMultigene genetic programming algorithm |
| spellingShingle | Pei, Yao Pichon, Lionel Bensetti, Mohamed Le Bihan, Yann Analysis of inductive power transfer systems by metamodeling techniques Comptes Rendus. Physique Wireless power transfer Metamodels Polynomial chaos expansions Support vector regression Multigene genetic programming algorithm |
| title | Analysis of inductive power transfer systems by metamodeling techniques |
| title_full | Analysis of inductive power transfer systems by metamodeling techniques |
| title_fullStr | Analysis of inductive power transfer systems by metamodeling techniques |
| title_full_unstemmed | Analysis of inductive power transfer systems by metamodeling techniques |
| title_short | Analysis of inductive power transfer systems by metamodeling techniques |
| title_sort | analysis of inductive power transfer systems by metamodeling techniques |
| topic | Wireless power transfer Metamodels Polynomial chaos expansions Support vector regression Multigene genetic programming algorithm |
| url | https://comptes-rendus.academie-sciences.fr/physique/articles/10.5802/crphys.188/ |
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