Flexible design of reluctance synchronous machines using constrained genetic algorithm optimization

T. Hubert; M. Reinlein; A. Kremser; H. G. Herzog

doi:10.1109/ICEMS.2015.7385159

Flexible design of reluctance synchronous machines using constrained genetic algorithm optimization

T. Hubert, M. Reinlein, A. Kremser, H. G. Herzog

Associate Professorship of Energy Conversion Technology

Technische Hochschule Nuernberg

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

The output performance of a reluctance synchronous machine strongly depends on a well-designed machine draft. Since there are many different requirements concerning the output capability, the machine design has to be done considering all specifications and demands also determined by the field of application. However the machine design and optimization by genetic algorithm is a simple and comparatively fast method to achieve adequate results and is therefore presented within this publication. The outcome of the optimization of course depends on the algorithm provided design variables as well as the calculation model concealed behind. In this case an analytical model based on a simplified magnetic circuit analysis is used for fitness value computation. The calculation method provides good results regarding some major parameters like d- and q-axis inductances as well as d- and q-axis currents. Within the genetic algorithm optimization a flexible design of reluctance synchronous machines in terms of the specific requirements is easily accessible. As a result important conclusions regarding the stator and rotor geometry can be achieved.

Original language	English
Title of host publication	2015 18th International Conference on Electrical Machines and Systems, ICEMS 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	882-887
Number of pages	6
ISBN (Electronic)	9781479988044
DOIs	https://doi.org/10.1109/ICEMS.2015.7385159
State	Published - 18 Jan 2016
Event	18th International Conference on Electrical Machines and Systems, ICEMS 2015 - Pattaya City, Thailand Duration: 25 Oct 2015 → 28 Oct 2015

Publication series

Name	2015 18th International Conference on Electrical Machines and Systems, ICEMS 2015

Conference

Conference	18th International Conference on Electrical Machines and Systems, ICEMS 2015
Country/Territory	Thailand
City	Pattaya City
Period	25/10/15 → 28/10/15

Keywords

genetic algorithm
machine design
optimization
reluctance synchronous machines

Access to Document

10.1109/ICEMS.2015.7385159

Cite this

Hubert, T., Reinlein, M., Kremser, A., & Herzog, H. G. (2016). Flexible design of reluctance synchronous machines using constrained genetic algorithm optimization. In 2015 18th International Conference on Electrical Machines and Systems, ICEMS 2015 (pp. 882-887). Article 7385159 (2015 18th International Conference on Electrical Machines and Systems, ICEMS 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICEMS.2015.7385159

Hubert, T. ; Reinlein, M. ; Kremser, A. et al. / Flexible design of reluctance synchronous machines using constrained genetic algorithm optimization. 2015 18th International Conference on Electrical Machines and Systems, ICEMS 2015. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 882-887 (2015 18th International Conference on Electrical Machines and Systems, ICEMS 2015).

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title = "Flexible design of reluctance synchronous machines using constrained genetic algorithm optimization",

abstract = "The output performance of a reluctance synchronous machine strongly depends on a well-designed machine draft. Since there are many different requirements concerning the output capability, the machine design has to be done considering all specifications and demands also determined by the field of application. However the machine design and optimization by genetic algorithm is a simple and comparatively fast method to achieve adequate results and is therefore presented within this publication. The outcome of the optimization of course depends on the algorithm provided design variables as well as the calculation model concealed behind. In this case an analytical model based on a simplified magnetic circuit analysis is used for fitness value computation. The calculation method provides good results regarding some major parameters like d- and q-axis inductances as well as d- and q-axis currents. Within the genetic algorithm optimization a flexible design of reluctance synchronous machines in terms of the specific requirements is easily accessible. As a result important conclusions regarding the stator and rotor geometry can be achieved.",

keywords = "genetic algorithm, machine design, optimization, reluctance synchronous machines",

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Hubert, T, Reinlein, M, Kremser, A & Herzog, HG 2016, Flexible design of reluctance synchronous machines using constrained genetic algorithm optimization. in 2015 18th International Conference on Electrical Machines and Systems, ICEMS 2015., 7385159, 2015 18th International Conference on Electrical Machines and Systems, ICEMS 2015, Institute of Electrical and Electronics Engineers Inc., pp. 882-887, 18th International Conference on Electrical Machines and Systems, ICEMS 2015, Pattaya City, Thailand, 25/10/15. https://doi.org/10.1109/ICEMS.2015.7385159

Flexible design of reluctance synchronous machines using constrained genetic algorithm optimization. / Hubert, T.; Reinlein, M.; Kremser, A. et al.
2015 18th International Conference on Electrical Machines and Systems, ICEMS 2015. Institute of Electrical and Electronics Engineers Inc., 2016. p. 882-887 7385159 (2015 18th International Conference on Electrical Machines and Systems, ICEMS 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Flexible design of reluctance synchronous machines using constrained genetic algorithm optimization

AU - Hubert, T.

AU - Reinlein, M.

AU - Kremser, A.

AU - Herzog, H. G.

PY - 2016/1/18

Y1 - 2016/1/18

N2 - The output performance of a reluctance synchronous machine strongly depends on a well-designed machine draft. Since there are many different requirements concerning the output capability, the machine design has to be done considering all specifications and demands also determined by the field of application. However the machine design and optimization by genetic algorithm is a simple and comparatively fast method to achieve adequate results and is therefore presented within this publication. The outcome of the optimization of course depends on the algorithm provided design variables as well as the calculation model concealed behind. In this case an analytical model based on a simplified magnetic circuit analysis is used for fitness value computation. The calculation method provides good results regarding some major parameters like d- and q-axis inductances as well as d- and q-axis currents. Within the genetic algorithm optimization a flexible design of reluctance synchronous machines in terms of the specific requirements is easily accessible. As a result important conclusions regarding the stator and rotor geometry can be achieved.

AB - The output performance of a reluctance synchronous machine strongly depends on a well-designed machine draft. Since there are many different requirements concerning the output capability, the machine design has to be done considering all specifications and demands also determined by the field of application. However the machine design and optimization by genetic algorithm is a simple and comparatively fast method to achieve adequate results and is therefore presented within this publication. The outcome of the optimization of course depends on the algorithm provided design variables as well as the calculation model concealed behind. In this case an analytical model based on a simplified magnetic circuit analysis is used for fitness value computation. The calculation method provides good results regarding some major parameters like d- and q-axis inductances as well as d- and q-axis currents. Within the genetic algorithm optimization a flexible design of reluctance synchronous machines in terms of the specific requirements is easily accessible. As a result important conclusions regarding the stator and rotor geometry can be achieved.

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KW - optimization

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Hubert T, Reinlein M, Kremser A, Herzog HG. Flexible design of reluctance synchronous machines using constrained genetic algorithm optimization. In 2015 18th International Conference on Electrical Machines and Systems, ICEMS 2015. Institute of Electrical and Electronics Engineers Inc. 2016. p. 882-887. 7385159. (2015 18th International Conference on Electrical Machines and Systems, ICEMS 2015). doi: 10.1109/ICEMS.2015.7385159

Flexible design of reluctance synchronous machines using constrained genetic algorithm optimization

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