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Topology Optimization of Magnetic Actuator based on Reluctance Network Modeling and Adjoint Variable Method

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Title: Topology Optimization of Magnetic Actuator based on Reluctance Network Modeling and Adjoint Variable Method
Authors: Yin, Ming, Naidjate, Mohammed, Bracikowski, Nicolas, Pierquin, Antoine, Trichet, Didier
Contributors: Institut de Recherche en Energie Electrique de Nantes Atlantique UR 4642 (IREENA), Institut Universitaire de Technologie - La Roche-sur-Yon (Nantes Univ - IUT La Roche-sur-Yon), Nantes Université - pôle Sciences et technologie, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes Université - pôle Sciences et technologie, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes Université - Institut Universitaire de Technologie Saint-Nazaire (Nantes Univ - IUT Saint-Nazaire), Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes Université - Ecole Polytechnique de l'Université de Nantes (Nantes Univ - EPUN), Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ), École Polytechnique de Montréal (EPM), Nantes Université (Nantes Univ)
Source: INTERMAG 2023 ; https://hal.science/hal-04317244 ; INTERMAG 2023, May 2023, Sendai, Japan
Publisher Information: CCSD
Publication Year: 2023
Collection: Université de Nantes: HAL-UNIV-NANTES
Subject Terms: Topology optimization, magnetic actuator, reluctance network analysis, adjoint variable method, [SPI]Engineering Sciences [physics]
Subject Geographic: Sendai, Japan
Description: International audience ; Topology Optimization (TO) has great significance in primarily the concept design of a product. In the electrical engineering community, conventional topology optimization is usually based on a spatial discretization that also is used as the mesh for Finite Element Analysis (FEA). In this paper, we proposed to use a local equivalent circuit modeling method-Reluctance Network Analysis (RNA). Afterward, a gradient-based optimization algorithm, line search method, was chosen as the optimizer where the sensitivity information was calculated by Adjoint Variable Method (AVM). Finally, the feasibility of this model for topology optimization was verified through a case study of a magnetic actuator.
Document Type: conference object
Language: English
Availability: https://hal.science/hal-04317244
https://hal.science/hal-04317244v1/document
https://hal.science/hal-04317244v1/file/Digest_Intermag_2023_Ming_final_14_01_2023.pdf
Rights: info:eu-repo/semantics/OpenAccess
Accession Number: edsbas.EB0AE3A7
Database: BASE
Description
Abstract:International audience ; Topology Optimization (TO) has great significance in primarily the concept design of a product. In the electrical engineering community, conventional topology optimization is usually based on a spatial discretization that also is used as the mesh for Finite Element Analysis (FEA). In this paper, we proposed to use a local equivalent circuit modeling method-Reluctance Network Analysis (RNA). Afterward, a gradient-based optimization algorithm, line search method, was chosen as the optimizer where the sensitivity information was calculated by Adjoint Variable Method (AVM). Finally, the feasibility of this model for topology optimization was verified through a case study of a magnetic actuator.