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Electrical and Computer Engineering Commons™
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Full-Text Articles in Electrical and Computer Engineering
Two-Level Surrogate-Assisted Differential Evolution Multi-Objective Optimization Of Electric Machines Using 3-D Fea, Narges Taran, Dan M. Ionel, David G. Dorrell
Two-Level Surrogate-Assisted Differential Evolution Multi-Objective Optimization Of Electric Machines Using 3-D Fea, Narges Taran, Dan M. Ionel, David G. Dorrell
Power and Energy Institute of Kentucky Faculty Publications
A two-level surrogate-assisted optimization algorithm is proposed for electric machine design using 3-D finite-element analysis (FEA). The algorithm achieves the optima with much fewer FEA evaluations than conventional methods. It is composed of interior and exterior levels. The exploration is performed mainly in the interior level, which evaluates hundreds of designs employing affordable kriging models. Then, the most promising designs are evaluated in the exterior loop with expensive 3-D FEA models. The sample pool is constructed in a self-adjustable and dynamic way. A hybrid stopping criterion is used to avoid unnecessary expensive function evaluations.
Exploring The Efficiency And Cost Limits Of Fractional Hp Axial Flux Pm Machine Designs, Narges Taran, Vandana Rallabandi, Greg Heins, Dan M. Ionel
Exploring The Efficiency And Cost Limits Of Fractional Hp Axial Flux Pm Machine Designs, Narges Taran, Vandana Rallabandi, Greg Heins, Dan M. Ionel
Power and Energy Institute of Kentucky Faculty Publications
Optimizing the design of electric machines is a vital step in ensuring the economical use of active materials. The three-dimensional flux paths in axial flux PM (AFPM) machines necessitate the use of computationally expensive 3D 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 FEA evaluations. The proposed algorithm is employed to optimally design an AFPM machine within a specified envelope, …