Fast Shielding Optimization of an Inductive Power Transfer System for Electric Vehicles
The shielding design is one of the most difficult phases in developing an inductive power transfer system (IPT) for electric vehicles. In this aspect, the combination of metamodeling with a multiobjective optimization algorithm provides an efficient approach. Here, Polynomial Chaos Expansions (PCE)...
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9857909/ |
| _version_ | 1811268903316226048 |
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| author | Yao Pei Lionel Pichon Yann Le Bihan Mohamed Bensetti Philippe Dessante |
| author_facet | Yao Pei Lionel Pichon Yann Le Bihan Mohamed Bensetti Philippe Dessante |
| author_sort | Yao Pei |
| collection | DOAJ |
| description | The shielding design is one of the most difficult phases in developing an inductive power transfer system (IPT) for electric vehicles. In this aspect, the combination of metamodeling with a multiobjective optimization algorithm provides an efficient approach. Here, Polynomial Chaos Expansions (PCE) and Multigene Genetic Programming Algorithm (MGPA) methods are used and compared to describe the mutual inductance of the IPT system in the function of the design variables on the shielding. These metamodels are obtained based on a number of 3D Finite Element Method (FEM) computations. Then, a multiobjective optimization algorithm coupled with the PCE metamodeling technique is applied to determine the optimal design variables for a practical shielding design when considering the magnetic coupling as well as the cost of the shielding as objective functions. Such a multiobjective optimization algorithm based on a particle swarm algorithm coupled with a metamodel on PCE method is proposed, leading to improve around 104 % of the mutual inductance <inline-formula> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> and save 14 % of the cost <inline-formula> <tex-math notation="LaTeX">$C$ </tex-math></inline-formula> for the shielding compared to the initial design. |
| first_indexed | 2024-04-12T21:32:20Z |
| format | Article |
| id | doaj.art-4fa6915607144d2e88fcfbcc6c5476cb |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-12T21:32:20Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-4fa6915607144d2e88fcfbcc6c5476cb2022-12-22T03:16:01ZengIEEEIEEE Access2169-35362022-01-0110912279123410.1109/ACCESS.2022.31989539857909Fast Shielding Optimization of an Inductive Power Transfer System for Electric VehiclesYao Pei0https://orcid.org/0000-0003-0099-4001Lionel Pichon1https://orcid.org/0000-0002-3402-5498Yann Le Bihan2Mohamed Bensetti3Philippe Dessante4https://orcid.org/0000-0002-4254-5987Laboratoire de Génie Electrique et Electronique de Paris, CentraleSupélec, CNRS, Université Paris-Saclay, Gif-sur-Yvette, FranceLaboratoire de Génie Electrique et Electronique de Paris, CentraleSupélec, CNRS, Université Paris-Saclay, Gif-sur-Yvette, FranceLaboratoire de Génie Electrique et Electronique de Paris, CentraleSupélec, CNRS, Université Paris-Saclay, Gif-sur-Yvette, FranceLaboratoire de Génie Electrique et Electronique de Paris, CentraleSupélec, CNRS, Université Paris-Saclay, Gif-sur-Yvette, FranceLaboratoire de Génie Electrique et Electronique de Paris, CentraleSupélec, CNRS, Université Paris-Saclay, Gif-sur-Yvette, FranceThe shielding design is one of the most difficult phases in developing an inductive power transfer system (IPT) for electric vehicles. In this aspect, the combination of metamodeling with a multiobjective optimization algorithm provides an efficient approach. Here, Polynomial Chaos Expansions (PCE) and Multigene Genetic Programming Algorithm (MGPA) methods are used and compared to describe the mutual inductance of the IPT system in the function of the design variables on the shielding. These metamodels are obtained based on a number of 3D Finite Element Method (FEM) computations. Then, a multiobjective optimization algorithm coupled with the PCE metamodeling technique is applied to determine the optimal design variables for a practical shielding design when considering the magnetic coupling as well as the cost of the shielding as objective functions. Such a multiobjective optimization algorithm based on a particle swarm algorithm coupled with a metamodel on PCE method is proposed, leading to improve around 104 % of the mutual inductance <inline-formula> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> and save 14 % of the cost <inline-formula> <tex-math notation="LaTeX">$C$ </tex-math></inline-formula> for the shielding compared to the initial design.https://ieeexplore.ieee.org/document/9857909/Shielding designpolynomial chaos expansionmultigene genetic programming algorithmparticle swarm algorithminductive power transfer system |
| spellingShingle | Yao Pei Lionel Pichon Yann Le Bihan Mohamed Bensetti Philippe Dessante Fast Shielding Optimization of an Inductive Power Transfer System for Electric Vehicles IEEE Access Shielding design polynomial chaos expansion multigene genetic programming algorithm particle swarm algorithm inductive power transfer system |
| title | Fast Shielding Optimization of an Inductive Power Transfer System for Electric Vehicles |
| title_full | Fast Shielding Optimization of an Inductive Power Transfer System for Electric Vehicles |
| title_fullStr | Fast Shielding Optimization of an Inductive Power Transfer System for Electric Vehicles |
| title_full_unstemmed | Fast Shielding Optimization of an Inductive Power Transfer System for Electric Vehicles |
| title_short | Fast Shielding Optimization of an Inductive Power Transfer System for Electric Vehicles |
| title_sort | fast shielding optimization of an inductive power transfer system for electric vehicles |
| topic | Shielding design polynomial chaos expansion multigene genetic programming algorithm particle swarm algorithm inductive power transfer system |
| url | https://ieeexplore.ieee.org/document/9857909/ |
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