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Article Dans Une Revue International Journal of Applied Electromagnetics and Mechanics Année : 2017

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

Résumé

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.
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Dates et versions

hal-01692450 , version 1 (25-01-2018)

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Tiago Staudt, Laurent Gerbaud, Frédéric Wurtz, Nelson Jhoe Batistela, Patrick Kuo-Peng, et al.. Modeling and sizing by optimization of a Brushless Doubly-Fed Reluctance Machine. International Journal of Applied Electromagnetics and Mechanics, 2017, 53, pp.S261 - S277. ⟨10.3233/JAE-140167⟩. ⟨hal-01692450⟩
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