Abstract
A new method for modeling stator winding fault with one shorted coil in a switched reluctance motor (SRM) is presented in this paper. The method is based on artificial neural network (ANN), incorporated with a simple analytical model in electromagnetic analysis to estimate the flux-linkage characteristics of SRM under the stator winding fault. The magnetic equivalent circuit method with ANN is applied to calculate the nonlinear flux-linkage characteristics under stator winding fault condition. A stator winding fault 12/8 SRM prototype system is developed to verify the effectiveness of the proposed method. The results for a stator winding fault with one shorted coil are obtained from the proposed method and from the experimental work on a developed prototype. It is shown that the simulation results are close to the test results.
| Original language | English |
|---|---|
| Article number | 7428868 |
| Journal | IEEE Transactions on Applied Superconductivity |
| Volume | 26 |
| Issue number | 4 |
| Number of pages | 6 |
| ISSN | 1051-8223 |
| DOIs | |
| Publication status | Published - Jun 2016 |
Keywords
- Artificial neural network
- Fluxlinkage
- Motor fault
- Switched Reluctance Motor