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

Xuezhou Wang; Henk Polinder; Domenico Lahaye; Jan A. Ferreira

doi:10.1109/WEMDCD.2017.7947729

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

Xuezhou Wang, Henk Polinder, Domenico Lahaye, Jan A. Ferreira

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

5 Citations (Scopus)

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.

Original language	English
Title of host publication	Proceedings - 2017 IEEE Workshop on Electrical Machines Design, Control and Diagnosis, WEMDCD 2017
Place of Publication	Piscataway, NJ
Publisher	IEEE
Pages	89-94
Number of pages	6
ISBN (Electronic)	978-1-5090-5853-2
DOIs	https://doi.org/10.1109/WEMDCD.2017.7947729
Publication status	Published - Apr 2017
Event	IEEE WEMDCD'2017: IEEE Workshop on Electrical Machines Design, Control and Diagnosis - University of Nottingham, Nottingham, United Kingdom Duration: 20 Apr 2017 → 21 Apr 2017 http://w1.icem.cc/wemdcd2017/index.php/component/users/?view=reset

Conference

Conference	IEEE WEMDCD'2017
Abbreviated title	WEMDCD
Country/Territory	United Kingdom
City	Nottingham
Period	20/04/17 → 21/04/17
Internet address	http://w1.icem.cc/wemdcd2017/index.php/component/users/?view=reset

Keywords

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

Access to Document

10.1109/WEMDCD.2017.7947729

Cite this

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title = "FE Based Multi-Objective Optimization of a 3.2MW Brushless Doubly-Fed Induction Machine",

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.",

keywords = "Brushless, Doubly-fed, Induction machine, Multi-objective optimization, Nested-loop rotor",

author = "Xuezhou Wang and Henk Polinder and Domenico Lahaye and Ferreira, {Jan A.}",

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publisher = "IEEE",

address = "United States",

note = "IEEE WEMDCD'2017 : IEEE Workshop on Electrical Machines Design, Control and Diagnosis, WEMDCD ; Conference date: 20-04-2017 Through 21-04-2017",

url = "http://w1.icem.cc/wemdcd2017/index.php/component/users/?view=reset",

}

Wang, X, Polinder, H , Lahaye, D & Ferreira, JA 2017, FE Based Multi-Objective Optimization of a 3.2MW Brushless Doubly-Fed Induction Machine. in Proceedings - 2017 IEEE Workshop on Electrical Machines Design, Control and Diagnosis, WEMDCD 2017., 7947729, IEEE, Piscataway, NJ, pp. 89-94, IEEE WEMDCD'2017, Nottingham, United Kingdom, 20/04/17. https://doi.org/10.1109/WEMDCD.2017.7947729

FE Based Multi-Objective Optimization of a 3.2MW Brushless Doubly-Fed Induction Machine. / Wang, Xuezhou; Polinder, Henk ; Lahaye, Domenico et al.
Proceedings - 2017 IEEE Workshop on Electrical Machines Design, Control and Diagnosis, WEMDCD 2017. Piscataway, NJ: IEEE, 2017. p. 89-94 7947729.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

TY - GEN

T1 - FE Based Multi-Objective Optimization of a 3.2MW Brushless Doubly-Fed Induction Machine

AU - Wang, Xuezhou

AU - Polinder, Henk

AU - Lahaye, Domenico

AU - Ferreira, Jan A.

PY - 2017/4

Y1 - 2017/4

N2 - 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.

AB - 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.

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KW - Multi-objective optimization

KW - Nested-loop rotor

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

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