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.