Emulation of a Permanent Magnet Synchronous Machine with Stator Winding Fault
Bibliographic record
Abstract
Permanent Magnet Synchronous Machines (PMSMs) are used in electric vehicles because they are compact, highly efficient, and have high dynamic performances. High reliability and fault tolerance are required for these applications. The electric machines when exposed to high temperature, vibration and chemicals suffer from various faults. One of the common and catastrophic faults in PMSMs is the inter-turn short circuit fault in one stator coil. Hence it is required to study the PMSM behavior in the event of this fault. The Power hardware-in-the-loop (PHIL) emulation of a PMSM with Interturn Short Circuit (ITSC) Fault has not been done in the literature. This paper proposes to do the PHIL emulation of a PMSM with ITSC fault. The analytical model developed is used in the emulator setup. A comparison of the results obtained in the hardware setup for the emulator is compared with the simulation results obtained in MATLAB.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".