Abstract
The optimization of five-phase induction machines is addressed using a new procedure based on genetic algorithms. A constrained optimization model is introduced which considers the main machine dimensions as free variables. Number of stator and rotor slots, winding pitch, and rotor bar inclination angle are among the free design variables. In addition, the relationship between fundamental and third harmonic component of the airgap induction is also considered as a free variable. This relationship is used to shape the airgap induction making it near to a trapezoid, thus potentially increasing the output torque. The underlying machine model used in the optimization process is detailed in previous works and includes the effect of losses and saturation on the steady state performance. Thus, a mixed-integer optimization problem is defined, in which the continuous variables are codified as integer variables making the optimization problem easier to solve. Three objective functions are defined and tested: efficiency, cost of conductor material, and a weighted combination of efficiency and material costs; other objective functions can be defined, too. The proposed method was applied to the optimization of a 5.5-kW prototype machine, and the results are presented and discussed.
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Acknowledgments
The authors thank WEG Motors (Santa Catarina—Brazil) for the support on developing and building the prototype machines and the test rig. The authors also thank to the Brazilian research funding agencies FAPERGS (process number 110894/2) and CNPq (process number 485972/2011-5) for their financial support. Finally, the authors thank the CNPq for the research support associated with Grants 303650/2011-7, 303842/2011-3 and 140357/2013-0.
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Haffner, S., Pereira, L.A. & Pereira, L.F.A. A Method for Optimization of Five-Phase Induction Machines Based on Genetic Algorithms. J Control Autom Electr Syst 26, 521–534 (2015). https://doi.org/10.1007/s40313-015-0197-z
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DOI: https://doi.org/10.1007/s40313-015-0197-z