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.
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