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Saturation Consideration in Modeling of the Induction Machine Using Subdomain Technique to Predict Performance
- Source :
- IEEE Transactions on Industry Applications. 58:261-272
- Publication Year :
- 2022
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2022.
-
Abstract
- Refereed/Peer-reviewed In this article, the analysis of induction machines using five separated subdomains including the rotor slot, rotor slot opening, airgap, stator slot opening, and stator slot regions is considered. The Maxwell equations of each region are solved considering the boundary conditions. Uniform distributions of the current density in the rectangular slots of both the rotor and stator are considered to find the energy of the winding and to calculate the machine inductances using the energy equation. The calculated flux density of each subdomain is used to find the flux distribution. The calculated magnetic flux intensities are required to estimate the saturation level of the motor cores and correct the saturation-related values such as the leakage and magnetizing inductances. The machine core losses are calculated based on the Steinmetz equation at the no-load condition. The calculated inductances and resistances are used in the equivalent circuit of the squirrel-cage induction machine (SCIM) for the performance prediction. The results demonstrate the reliability of the saturation model in the prediction of the saturation influence in a wide range of magnetization levels. The accuracy of the proposed model in the prediction of the performance of the SCIM is validated using two-dimensional (2-D) and 3-D finite-element analysis results. A sensitivity analysis with 75 different geometries was conducted to show the capability of the model for the performance prediction of a wide range of induction machines.
- Subjects :
- magnetic vector potential (MVP)
subdomain model (SDM)
Induction machine
Materials science
Control and Systems Engineering
induction motor (IM)
saturation effect
Mechanics
Electrical and Electronic Engineering
Saturation (chemistry)
performance prediction
Industrial and Manufacturing Engineering
Subjects
Details
- ISSN :
- 19399367 and 00939994
- Volume :
- 58
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Industry Applications
- Accession number :
- edsair.doi.dedup.....d7ed12087be690638bab492a3d75f5f1