Neural network approach compared to sensitivity analysis based on finite element technique for optimization of permanent magnet generators

Neural network approach compared to sensitivity analysis based on finite element technique for optimization of permanent magnet generators

The paper presents the optimization procedure of a permanent magnet generator for a 20 kW wind turbine prototype "Peripheral" neodymium alloy magnet rotor structure has been considered to perform the optimal shape design. A fully connected four layer feedforward neural network has been int...

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Veröffentlicht in:IEEE transactions on magnetics 2001-09, Vol.37 (5), p.3618-3621
Hauptverfasser: Tsekouras, G., Kiartzis, S., Kladas, A.G., Tegopoulos, J.A.
Format: Artikel
Sprache:eng
Schlagworte:
Applied classical electromagnetism
Design optimization
Electromagnetism
electron and ion optics
Exact sciences and technology
Feedforward neural networks
Finite element method
Fundamental areas of phenomenology (including applications)
Generators
Magnetism
Magnetostatics
magnetic shielding, magnetic induction, boundary-value problems
Mathematical analysis
Neodymium alloys
Neural networks
Optimization
Permanent magnets
Physics
Prototypes
Rotors
Sensitivity analysis
Shape memory alloys
Wind turbines
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Zusammenfassung:The paper presents the optimization procedure of a permanent magnet generator for a 20 kW wind turbine prototype "Peripheral" neodymium alloy magnet rotor structure has been considered to perform the optimal shape design. A fully connected four layer feedforward neural network has been introduced and compared to a technique based on the finite element method and sensitivity analysis. The considered methods are in very good agreement.
ISSN:0018-9464
1941-0069
DOI:10.1109/20.952675