Title :
Characterization of SRM drive systems under normal and fault operating conditions
Author :
Arkada, A.A. ; Sidani, M. ; Du, P.
Author_Institution :
Dept. of Electr. & Comput. Eng., Marquette Univ., Milwaukee, WI, USA
Abstract :
Two methods to predict the performance characteristics of switched reluctance motor (SRM) drive systems under normal and fault operating conditions are presented. The first method is based on the use of an iterative approach which indirectly couples a two-dimensional nonlinear finite element model to a state space model describing the SRM drive system. The second method uses an artificial neural networks approach which is applied for its interpolation capabilities for highly nonlinear systems in order to obtain a fast and accurate prediction of the performance of the SRM drive system
Keywords :
electric machine analysis computing; electrical faults; finite element analysis; interpolation; iterative methods; machine theory; neural nets; reluctance motor drives; state-space methods; 2-D nonlinear finite element model; SRM drive systems characterisation; artificial neural network; fault operating conditions; highly nonlinear systems; interpolation capabilities; iterative approach; normal operating conditions; performance characteristics; state space model; Circuit faults; Coupling circuits; Finite element methods; Interpolation; Magnetic circuits; Nonlinear systems; Power electronics; Reluctance machines; Reluctance motors; State-space methods;
Conference_Titel :
Electric Machines and Drives, 1999. International Conference IEMD '99
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-5293-9
DOI :
10.1109/IEMDC.1999.769083
