Automatic Design of Synchronous Reluctance Motors Focusing on Barrier Shape Optimization


The automated style of synchronous reluctance (SyR) motors primarily based on multiobjective genetic optimization and finite-component analysis is considered in this paper. Three types of barrier shapes are thought of, all described by an effective limited set of input variables. The three solutions are investigated to establish which of the geometries can give the best torque output and conjointly which one represents the most effective compromise between output performance and computational time. The analysis presented in this paper shows that SyR motors designed automatically can give a good performance and will be designed in a very cheap time, and it is also shown that not all design degrees of freedom are helpful in terms of motor performance. Two prototypes of automatically designed machines have been fabricated and experimentally compared with a third prototype designed consistent with state-of-the-art style principles.

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