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Communication Dans Un Congrès Année : 2023

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

Résumé

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.
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Dates et versions

hal-04317244 , version 1 (01-12-2023)

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  • HAL Id : hal-04317244 , version 1

Citer

Ming Yin, Mohammed Naidjate, Nicolas Bracikowski, Antoine Pierquin, Didier Trichet. Topology Optimization of Magnetic Actuator based on Reluctance Network Modeling and Adjoint Variable Method. INTERMAG 2023, May 2023, Sendai, Japan. ⟨hal-04317244⟩
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