Modeling and sizing by optimization of a Brushless Doubly-Fed Reluctance Machine

Issue title: Special Supplement Issue: Selected papers from the 13th International Workshop on Optimization and Inverse Problems in Electromagnetism (OIPE 2014)

Guest editors: Domenico Lahaye

Article type: Research Article

Authors: Staudt, Tiago^{a; b; *} | Gerbaud, Laurent^a | Wurtz, Frédéric^a | Batistela, Nelson Jhoe^b | Kuo-Peng, Patrick^b

Affiliations: [a] University Grenoble Alpes, Grenoble, France | [b] Federal University of Santa Catarina, Florianopolis, Brazil

Correspondence: [*] Corresponding author: Tiago Staudt, University Grenoble Alpes, G2Elab-CNRS, F-38000 Grenoble, France. Tel.: +55 48 3721 9649; Fax: +55 48 3234 3790; E-mail:[email protected]

Abstract: The paper proposes an optimization approach to address the modeling and sizing complexities of Brushless Doubly-Fed Reluctances Machines. A semi-analytical model and a reluctance network model are coupled to a deterministic optimization algorithm where several inputs and outputs parameters can be constrained to solve sizing equations iteratively by maximizing or minimizing an objective function. A Pareto Front strategy is used to illustrate the models capabilities, highlighting the trade-offs on the design of this kind of electrical machines. The optimization model provides fast results to define a first design, reducing the number of unknown parameters of early development stages. This saves computation time and computer resources in the design process compared to Finite Element Analysis.

Keywords: Design optimization, brushless machines, electromagnetic analysis, wind energy

DOI: 10.3233/JAE-140167

Journal: International Journal of Applied Electromagnetics and Mechanics, vol. 53, no. S2, pp. S261-S277, 2017