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February 2, 2026Journal of Power Electronics

Neural network-based distributed parameter modeling of permanent magnet synchronous machines considering spatial harmonics and iron losses

Zhongshu Shao Yong Bao Zaimin Zhong Zhixun Ma Yeqin Wang

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Key Points

Modeling efficiency improves in permanent magnet synchronous machines with the introduced framework, and the results highlight the role of spatial harmonics.
Key evidence includes a demonstrated reduction in iron losses when applying the neural network-based modeling approach, leading to better performance.
Distributed parameter modeling is utilized, incorporating spatial harmonics and iron losses, showcasing the relevance of advanced methodologies.
The findings suggest potential advancements in machine efficiency, calling for further exploration of neural network approaches in electrical engineering.

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Implication

Analysis demonstrates improved modeling of efficiency in permanent magnet synchronous machines, suggesting enhanced performance capabilities.

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Cite This Study

Shao et al. (2026) studied this question.

synapsesocial.com/papers/69a76555badf0bb9e87d8c15 https://doi.org/10.1007/s43236-026-01280-w

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