日本AEM学会誌
Online ISSN : 2187-9257
Print ISSN : 0919-4452
ISSN-L : 0919-4452
特集「AIによる電気機器の設計・解析技術」
トポロジー・パラメータ同時最適化とモンテカルロ木探索による総合設計
佐藤 駿輔五十嵐 一
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2022 年 30 巻 4 号 p. 384-389

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 This paper presents a novel total design method using Monte Carlo tree search and hybridized topology-parameter optimization. In this method, the global structure of an electrical machine is represented by nodes in a tree structure. Monte Carlo tree search is used to select a path in the tree structure, which corresponds to a machine structure. After that, detailed machine shape is optimized by the hybridized method considering both of flexibility and manufacturability. By repeating the above procedure, the global structure and detailed shape are simultaneously optimized. This method is applied to the design of a permanent magnet motor to enhance torque characteristics.

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