Analysis of inductive power transfer systems by metamodeling techniques

Yao Pei; Lionel Pichon; Mohamed Bensetti; Yann Le Bihan

doi:10.5802/crphys.188

Article de recherche

Analysis of inductive power transfer systems by metamodeling techniques
[Analyse de systèmes de transfert de puissance inductifs par des techniques de métamodélisation]

Yao Pei ^1,² ; Lionel Pichon ^1,² ; Mohamed Bensetti ^1,² ; Yann Le Bihan ^1,²

¹ Université Paris-Saclay, CentraleSupélec, CNRS, Laboratoire de Génie Electrique et Electronique de Paris, 91192, Gif-sur-Yvette, France
² Sorbonne Université, CNRS, Laboratoire de Génie Electrique et Electronique de Paris, 75252, Paris, France

Comptes Rendus. Physique, Online first (2024), pp. 1-15.

Résumé
Abstract

Ce papier présente différentes techniques de métamodélisation afin d’analyser la variabilité des performances d’un système de transfert de puissance par induction (IPT), en tenant compte des sources d’incertitude (décentrage des bobines, la variation de l’entrefer et la rotation du récepteur). Pour les systèmes IPT, l’une des questions clés est l’efficacité de la transmission, qui est fortement influencée par les nombreuses sources d’incertitude. Il est donc important de déterminer une technique de métamodélisation susceptible d’évaluer rapidement les performances du système. Trois techniques de métamodélisation sont comparées : la régression à vecteurs de support, l’algorithme de programmation génétique multigénique et les développements du chaos polynomial (PCE), il ressort que la technique PCE est recommandée pour une telle analyse en raison du compromis entre le temps de calcul et la précision du métamodèle.

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.

Reçu le : 2023-07-18
Révisé le : 2024-02-19
Accepté le : 2024-05-15
Première publication : 2024-08-22

DOI : 10.5802/crphys.188

Keywords: Wireless power transfer, Metamodels, Polynomial chaos expansions, Support vector regression, Multigene genetic programming algorithm
Mot clés : Transfert d’énergie sans contact, Métamodèles, Développements du chaos polynomial, Régression à vecteurs de support, L’algorithme de programmation génétique multigénique

Affiliations des auteurs :

Yao Pei ^{1, 2} ; Lionel Pichon ^{1, 2} ; Mohamed Bensetti ^{1, 2} ; Yann Le Bihan ^{1, 2}

¹ Université Paris-Saclay, CentraleSupélec, CNRS, Laboratoire de Génie Electrique et Electronique de Paris, 91192, Gif-sur-Yvette, France
² Sorbonne Université, CNRS, Laboratoire de Génie Electrique et Electronique de Paris, 75252, Paris, France

Licence :

CC-BY 4.0

Droits d'auteur : Les auteurs conservent leurs droits

@article{CRPHYS_2024__25_S1_A13_0,
     author = {Yao Pei and Lionel Pichon and Mohamed Bensetti and Yann Le Bihan},
     title = {Analysis of inductive power transfer systems by metamodeling techniques},
     journal = {Comptes Rendus. Physique},
     publisher = {Acad\'emie des sciences, Paris},
     year = {2024},
     doi = {10.5802/crphys.188},
     language = {en},
     note = {Online first},
}

TY  - JOUR
AU  - Yao Pei
AU  - Lionel Pichon
AU  - Mohamed Bensetti
AU  - Yann Le Bihan
TI  - Analysis of inductive power transfer systems by metamodeling techniques
JO  - Comptes Rendus. Physique
PY  - 2024
PB  - Académie des sciences, Paris
N1  - Online first
DO  - 10.5802/crphys.188
LA  - en
ID  - CRPHYS_2024__25_S1_A13_0
ER  -

%0 Journal Article
%A Yao Pei
%A Lionel Pichon
%A Mohamed Bensetti
%A Yann Le Bihan
%T Analysis of inductive power transfer systems by metamodeling techniques
%J Comptes Rendus. Physique
%D 2024
%I Académie des sciences, Paris
%Z Online first
%R 10.5802/crphys.188
%G en
%F CRPHYS_2024__25_S1_A13_0

Yao Pei; Lionel Pichon; Mohamed Bensetti; Yann Le Bihan. Analysis of inductive power transfer systems by metamodeling techniques. Comptes Rendus. Physique, Online first (2024), pp. 1-15. doi : 10.5802/crphys.188.

Bibliographie
Cité par

[1] M. Eshani et al. Modern electric, hybrid electric and fuel cell vehicles, Fundamentals, Theory, and Design, CRC Press, Boca Raton, FL, 2005

[2] M. Yilmaz; P. T. Krein Review of battery charger topologies, charging power levels, and infrastructure for plug-in electric and hybrid vehicles, IEEE Trans. Power Electron., Volume 28 (2013) no. 5, pp. 2151-2169

[3] C. T. Rim; C. Mi Wireless Power Transfer for Electric Vehicles and Mobile Devices | IEEE eBooks | IEEE Xplore (Accessed: July 10, 2024. [Online]. Available: https://ieeexplore.ieee.org/book/7953908)

[4] T. M. Fisher et al. Electric vehicle wireless charging technology: a state-of-the-art review of magnetic coupling systems, Wireless Power Transf., Volume 1 (2014) no. 2, pp. 87-96

[5] J1772_202401 : SAE Electric Vehicle and Plug-in Hybrid Electric Vehicle, Conductive Charge Coupler - SAE International (Accessed: July 10, 2024. [Online]. Available: https://www.sae.org/standards/content/j1772_202401/)

[6] Charger Types and Speeds | US Department of Transportation (Accessed: July 10, 2024. [Online]. Available: https://www.transportation.gov/rural/ev/toolkit/ev-basics/charging-speeds)

[7] Z. J. Lee; J. Z. Pang; S. H. Low Pricing EV charging service with demand charge, Electr. Power Syst. Res., Volume 189 (2020), 106694

[8] A. Mahesh; B. Chokkalingam; L. Mihet-Popa Inductive wireless power transfer charging for electric vehicles—a review, IEEE Access, Volume 9 (2021), pp. 137667-137713 https://10.1109/ACCESS.2021.3116678

[9] C. Panchal; S. Stegen; J. Lu Review of static and dynamic wireless electric vehicle charging system, Eng. Sci. Technol. Int. J., Volume 21 (2018) no. 5, pp. 922-937 https://10.1016/j.jestch.2018.06.015

[10] Electric Vehicles - Worldwide – Statista Market Forecast (Statista. Accessed: July 10, 2024. [Online]. Available: https://www.statista.com/outlook/mmo/electric-vehicles/worldwide)

[11] M. Larbi et al. Variability impact of many design parameters: the case of a realistic electronic link, IEEE Trans. Electromagn. Compat., Volume 60 (2018) no. 1, pp. 34-41

[12] S. De Ridder et al. A generative modeling framework for statistical link analysis based on sparse data, IEEE Trans. Compon. Packag. Manuf. Technol., Volume 8 (2018) no. 1, pp. 21-31 | DOI

[13] V. Cirimele et al. Uncertainty quantification for SAE J2954 compliant static wireless charge components, IEEE Access, Volume 8 (2020), pp. 171489-171501 | DOI

[14] R. Trinchero et al. Machine learning and uncertainty quantification for surrogate models of integrated devices with a large number of parameters, IEEE Access, Volume 7 (2019), pp. 4056-4066 | DOI

[15] R. Trinchero et al. Machine learning for the performance assessment of high-speed links, IEEE Trans. Electromagn. Compat., Volume 60 (2018) no. 6, pp. 1627-1634

[16] B. Sudret Global sensitivity analysis using polynomial chaos expansions, Rel. Eng. Syst. Saf., Volume 93 (2008) no. 7, pp. 964-979

[17] I. M. Sobol Sensitivity estimates for nonlinear mathematical models, Math. Model. Comput. Exp., Volume 1 (1990) no. 4, pp. 407-414

[18] M. Moustapha et al. UQLab user manual – Support vector machines for regression, Report UQLab-V2.0-111, Chair of Risk, Safety and Uncertainty Quantification, ETH Zurich, Switzerland, 2022

[19] D. P. Searson GPTIPS 2: an open-source software platform for symbolic data mining, Handbook of Genetic Programming Applications (A. H. Gandomi; A. H. Alavi; C. Ryan, eds.), Springer International Publishing, Cham, 2015, pp. 551-573 | DOI

[20] G. Blatman; B. Sudret Adaptive sparse polynomial chaos expansion based on least angle regression, J. Comput. Phys., Volume 230 (2011) no. 6, pp. 2345-2367 | DOI

[21] J. A. K. Suykens et al. Least Squares Support Vector Machines, World Scientific, Singapore, 2002

[22] G. D. Capua et al. Mutual inductance behavioral modeling for wireless power transfer system coils, IEEE Trans. Ind. Electron., Volume 68 (2021) no. 3, pp. 2196-2206 | DOI

[23] A. Delgado et al. Self and mutual inductance behavioral modeling of square-shaped IPT coils with air gap and ferrite core plates, IEEE Access, Volume 10 (2022), pp. 7476-7488 | DOI

[24] G. Di Capua et al. Analysis of dynamic wireless power transfer systems based on behavioral modeling of mutual inductance, Sustainability, Volume 13 (2021) no. 5, 2556 | DOI

[25] Y. Pei et al. Comparison of coupling coils for static inductive power-transfer systems taking into account sources of uncertainty, Sustainability, Volume 13 (2021) no. 11, 6324

[26] Y. Pei et al. Fast shielding optimization of an inductive power transfer system for electric vehicles, IEEE Access, Volume 10 (2022), pp. 91227-91234 | DOI

[27] A. Triviõ-Cabrera; J. M. González-González et al. Wireless Power Transfer for Electric Vehicles: Foundations and Design Approach (Accessed: July 10, 2024. [Online]. Available: https://link.springer.com/book/10.1007/978-3-030-26706-3)

[28] Vehicle Initiative Consortium for Transport Operation and Road Inductive Applications Victoria Project, April 25, 2017. http://greentechlatvia.eu/wp-content/uploads/bsk-pdf-manager/1-8_Project_Victoria_(Bludszuweit)_8.pdf (accessed September 19, 2022)

[29] V. Cirimele; M. Diana; F. Freschi; M. Mitolo Inductive power transfer for automotive applications: state-of-the-art and future trends, IEEE Trans. Indus. Appl., Volume 54 (2018) no. 5, pp. 4069-4079 | DOI

[30] G. A. Covic; J. T. Boys Modern trends in inductive power transfer for transportation applications, IEEE J. Emerging Sel. Top.n Power Electron., Volume 1 (2013) no. 1, pp. 28-41 | DOI

[31] M. Ibrahim Wireless Inductive Charging for Electrical Vehicules: Electromagnetic Modelling and Interoperability Analysis, Phd thesis (2014) (Université Paris Sud – Paris XI. Accessed February 11, 2024. [Online]. Available: https://tel.archives-ouvertes.fr/tel-01127163)

[32] P. S. R. Nayak; D. Kishan Design and analysis of SS resonant IPT system with computed mutual inductance through FEM model, 2018 International Conference on Power, Instrumentation, Control and Computing (PICC), Thrissur, India, January, 2018, pp. 1-5 | DOI

[33] K. Kadem et al. Optimal coupler topology for dynamic wireless power transfer for electric vehicle, Energies, Volume 14 (2021) no. 13, 3983 | DOI

[34] K. Kadem Modélisation et optimisation d’un coupleur magnétique pour la recharge par induction dynamique des véhicules électriques, Theses, Centralesupelec (2020) (Accessed August 29, 2022. [Online]. Available: https://hal.archives-ouvertes.fr/tel-03253967)

[35] R. Bosshard; J. Mühlethaler; J. W. Kolar; I. Stevanović Optimized magnetic design for inductive power transfer coils, 2013 Twenty-Eighth Annual IEEE Applied Power Electronics Conference and Exposition (APEC), Long Beach, CA, USA, March, 2013, pp. 1812-1819 | DOI

[36] R. Bosshard; J. W. Kolar; J. Mühlethaler; I. Stevanović; B. Wunsch; F. Canales Modeling and $η$ - $α$ -pareto optimization of inductive power transfer coils for electric vehicles, IEEE J. Emerging Sel. Top. Power Electron., Volume 3 (2015) no. 1, pp. 50-64 | DOI

[37] R. W. Erickson; D. Maksimović Inductor design, Fundamentals of Power Electronics (R. W. Erickson; D. Maksimović, eds.), Springer US, Boston, MA, 2001, pp. 539-564 | DOI

[38] J2954 : wireless power transfer for light-duty plug-in/electric vehicles and alignment methodology - SAE International (Accessed: July 10, 2024. [Online]. https://www.sae.org/standards/content/j2954_202010/)

[39] Software for Simulating Static and Low-Frequency Electromagnetics (COMSOL. Accessed: July 10, 2024. https://www.comsol.com/acdc-module)

[40] V. N. Vapnik The Nature of Statistical Learning Theory, Springer, New York, NY, 2000 (Accessed: July 10, 2024. [Online]. Available: https://link-springer-com.ezproxy.universite-paris-saclay.fr/book/10.1007/978-1-4757-3264-1)

[41] S. Marelli; B. Sudret UQLab: a framework for uncertainty quantification in Matlab, Proceedings of the 2nd International Conference on Vulnerability, Risk Analysis and Management (ICVRAM2014), Liverpool, United Kingdom, 2014, pp. 2554-2563

[42] M. Mitchell An Introduction to Genetic Algorithms, The MIT Press, Cambridge, MA, 1998 (Accessed: July 10, 2024. [Online]. Available: https://mitpress.mit.edu/books/introduction-genetic-algorithms)

[43] G. F. Smits; M. Kotanchek Pareto-front exploitation in symbolic regression, Genetic Programming Theory and Practice II (U.-M. O’Reilly; T. Yu; R. Riolo; B. Worzel, eds.), Springer US, Boston, MA, 2005, pp. 283-299 | DOI

[44] S. Marelli; N. Luthen; B. Sudret UQLab user manual – Polynomial chaos expansions, Report UQLab-V2.0-104, Chair of Risk, Safety and Uncertainty Quantification, ETH Zurich, Switzerland, 2022

[45] C. Lataniotis et al. UQLab user manual – The Input module, Report UQLab-V2.0-102, Chair of Risk, Safety and Uncertainty Quantification, ETH Zurich, Switzerland, 2022

Cité par Sources :

Commentaires - Politique