Exploring the Efficiency and Cost Limits of Fractional hp Axial Flux PM Machine Designs

Abstract

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, identifying the limits of cost and efficiency. Optimized designs with different rotor polarities are systematically compared in order to form the basis for a set of generalized design rules.

Systematically Exploring the Effects of Pole Count on the Performance and Cost Limits of UltraHigh Efficiency Fractional hp Axial Flux PM Machines

“…This paper is an expanded follow-up to a previous conference paper by the same authors [16]. Together the current and the previous conference paper provide substantial contributions to the subject matter by: systematically investigating the optimal design and pole count selection of a surface mounted AFPM machine; employing an algorithm capable of solving optimization problems with 3D FEA design evaluations and a very wide search space; and proposing a method for interpreting the Pareto front and selecting the optimal design in a multi-objective problem.…”

Design Optimization of Electric Machines with 3D FEA and a New Hybrid DOE-DE Numerical Algorithm

“…1. An algorithm based on surrogate models and differential evolution, employing 3D models and elaborated in [8], [9], is utilized for the optimization study. It is demonstrated that the combined use of this surrogate assisted optimization technique, together with the proposed definition of the search space results in substantial savings in computation time.…”