FE Based Multi-Objective Optimization of a 3.2MW Brushless Doubly-Fed Induction Machine

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FE Based Multi-Objective Optimization of a 3.2MW Brushless Doubly-Fed Induction Machine

Conference Paper (2017)

Author(s)

Xuezhou Wang (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Henk Polinder (TU Delft - Mechanical Engineering)

Domenico Lahaye (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Jan A. Ferreira (TU Delft - ESE Programmes)

Research Group

DC systems, Energy conversion & Storage

Multi-objective optimization Brushless Doubly-fed Induction machine Nested-loop rotor

DOI related publication

https://doi.org/10.1109/WEMDCD.2017.7947729 Final published version

To reference this document use

https://resolver.tudelft.nl/uuid:0787348d-eb51-4124-ad14-ffe42f01fe76

More Info

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Publication Year

2017

Language

English

Research Group

DC systems, Energy conversion & Storage

Article number

7947729

Pages (from-to)

89-94

ISBN (electronic)

978-1-5090-5853-2

Event

IEEE WEMDCD'2017 (2017-04-20 - 2017-04-21), University of Nottingham, Nottingham, United Kingdom

Downloads counter

187

Abstract

The brushless doubly-fed induction machine (DFIM) has great potential for wind turbine applications. However, it has not yet been commercialized due to its complicated operating principle. Previously, a computationally efficient FE model has been developed. Some design guidelines for the stator pole-pair combinations and the nested-loop rotors have been gained from the previous work. This paper brings the model and design guidelines together to optimize the design of a 3.2MW brushless DFIM. Both the active material cost and the efficiency are optimized. The results show that the magnetic loading of the brushless DFIM is increased for a better design by using the FE based optimization tool. The optimized designs increase the efficiency and the shear stress while reducing the torque ripple and the THD level of the stator voltages. However, the optimized designs result in a high electric loading which would be a challenge for cooling.