Electromagnetic design optimization of a low speed Slotted Switched Reluctance Machine using genetic algorithm

Author

Moreau, L. ; Zaïm, M.E. ; Machmoum, M.

Author_Institution

IREENA (Inst. de Rech. en Electrotech. et Electron. de Nantes Atlantique), St. Nazaire, France

fYear

2012

fDate

2-5 Sept. 2012

Firstpage

233

Lastpage

237

Abstract

This paper describes the design of a low speed Slotted Switched Reluctance Machine (SSRM) for wind turbine applications. The modeling and the dimensioning of the machine structure are investigated. Teeth shapes and global design are analyzed by optimizing the mass torque. Dimensions are obtained thanks to a genetic algorithm (GA) associated to the finite element method for the resolution of the electromagnetic equations. The optimization is executed 50 times in order to study convergence and to perform a statistical study on dimensioning parameters.

Keywords

convergence; finite element analysis; genetic algorithms; reluctance machines; statistical analysis; wind turbines; SSRM; convergence study; electromagnetic design optimization; electromagnetic equations; finite element method; genetic algorithm; machine structure dimensioning parameters; machine structure modeling; mass torque optimization; speed slotted switched reluctance machine; statistical study; teeth shapes; wind turbine applications; Genetic algorithms; Histograms; Optimization; Rotors; Switches; Torque; Wind turbines; Genetic algorithms; Reluctance Machine; Wind power generation;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical Machines (ICEM), 2012 XXth International Conference on

Conference_Location

Marseille

Print_ISBN

978-1-4673-0143-5

Electronic_ISBN

978-1-4673-0141-1

Type

conf

DOI

10.1109/ICElMach.2012.6349870

Filename

6349870