Title :
Neural network approach compared to sensitivity analysis based on finite element technique for optimization of permanent magnet generators
Author :
Tsekouras, G. ; Kiartzis, S. ; Kladas, A.G. ; Tegopoulos, J.A.
Author_Institution :
Dept. of Electr. & Comput. Eng., Nat. Tech. Univ. of Athens, Greece
fDate :
9/1/2001 12:00:00 AM
Abstract :
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
Keywords :
electric machine CAD; feedforward neural nets; finite element analysis; machine theory; optimisation; permanent magnet generators; sensitivity analysis; wind turbines; 20 kW; FEM; Nd alloy magnet rotor structure; finite element technique; four layer feedforward neural network; neural network approach; optimal shape design; optimization procedure; permanent magnet generators; sensitivity analysis; wind turbine prototype; Design optimization; Feedforward neural networks; Neodymium alloys; Neural networks; Permanent magnets; Prototypes; Rotors; Sensitivity analysis; Shape memory alloys; Wind turbines;
Journal_Title :
Magnetics, IEEE Transactions on
