Comparative Analysis of Noise and Vibration for Dual Three-Phase IPMSM Under Healthy and Multi-Phase Open-Circuit Fault Operations
Bibliographic record
Abstract
The dual three-phase interior permanent magnet synchronous machines (IPMSMs) exhibit excellent fault-tolerant capabilities due to their multi-phase winding configurations. Under certain winding failure circumstances, by using the fault tolerant control (FTC) to reconstruct the normal rotating magnetomotive force, the machine can still provide the expected comparable torque as the healthy mode does. However, in the existing literature, limited attention was paid to the noise and vibration (NV) problems targeting the dual three-phase IPMSMs in FTC operation. To fill this knowledge gap, this article conducts a quantitative comparison on the NV performance of a dual three-phase IPMSM under healthy and multi-phase open-circuit fault conditions under FTC. The comparative studies involve radial electromagnetic (EM) force, acceleration distribution, sound pressure level (SPL) as well as machine housing deformation, which are analyzed under healthy and multi-phase open-circuit fault operations. Based on our exclusive findings, after applying the FTC, even though the machine can deliver the desired EM performance, the maximum deformation and SPL of the IPMSM can be mitigated by 12.9% and 16.9%, respectively, compared to the ones under the faulty condition without FTC.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".