Optimizing the design of electric machines is a vital step in ensuring the economical use of active materials. The three-dimensional (3-D) flux paths in axial flux permanent magnet (AFPM) machines necessitate the use of computationally expensive 3-D electromagnetic analysis. Furthermore, a large number of design evaluations is required to find the optimum, causing the total computation time to be excessively long. In view of this, a two-level surrogate assisted algorithm capable of handling such expensive optimization problems is introduced, which substantially reduces the number of finite element analysis (FEA) evaluations to less than 200 while conventional algorithms require thousands of designs to be analyzed. The proposed algorithm is employed to optimally design an AFPM machine within a specified envelope, and to identify the limits of cost and efficiency. In order to obtain these limits, the variables' ranges are assigned to be as wide as possible, resulting in a vast design space, the study of which was enabled by the developed special algorithm. Additionally, optimized designs with different rotor polarities are systematically compared in order to form the basis for a set of generalized design rules.

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Published in IEEE Transactions on Industry Applications, v. 56 , issue: 1.

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The document available for download is the authors’ manuscript version that is accepted for publication. The final published version is copyrighted by IEEE and will be available as: N. Taran, V. Rallabandi, G. Heins, and D. M. Ionel, “Systematically Exploring the Effects of Pole Count on the Performance and the Cost Limits of Ultra-high Efficiency Fractional hp Axial Flux PM Machines,” in IEEE Transactionson Industry Applications, 2019, 10 p.

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The support of Regal Beloit Corp., University of Kentucky, the L. Stanley Pigman endowment and the SPARK program, and ANSYS Inc. is gratefully acknowledged.