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...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Comptes rendus. Physique Ročník 25; číslo S1; s. 125 - 139
Hlavní autori: Pei, Yao, Pichon, Lionel, Bensetti, Mohamed, Le Bihan, Yann
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Académie des sciences (Paris) 01.01.2024
Académie des sciences
Predmet:
Engineering Sciences
Metamodels
Multigene genetic programming algorithm
Polynomial chaos expansions
Support vector regression
Wireless power transfer
L
Wireless power transfer Metamodels Polynomial chaos expansions Support vector regression Multigene genetic programming algorithm. Mots-clés. Transfert d'énergie sans contact Métamodèles Développements du chaos polynomial Régression à vecteurs de support L
ISSN:1631-0705, 1878-1535
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí: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.
ISSN:1631-0705
1878-1535
DOI:10.5802/crphys.188