Healthy and Open-Phase Fault-Tolerant Unified Control for Dual Three-Phase PMSMs With Rapid Fault Response and False Alarm Recovery Capability
Bibliographic record
Abstract
This paper proposes a healthy and open-phase fault tolerant unified control approach for dual three-phase permanent magnet synchronous machines (DT-PMSMs). The proposed approach enables seamless switch between healthy control and fault tolerant control (FTC). When open-phase fault happens, the proposed approach can rapidly respond to the fault within 1/20 electrical cycle. Moreover, when false alarm happens due to noise or disturbance, the proposed approach can switch back to the healthy control effectively. Firstly, a healthy and FT unified control model is derived through the analysis of currents under healthy and fault conditions. The model parameters are optimized to achieve full range minimum copper loss (FRML), and the analytical solutions are derived to improve the computation efficiency and ensure the optimal performance in the full range operating conditions. Compared with existing methods, the proposed approach can achieve higher efficiency and larger torque range. The proposed approach is verified on the test machine under different operating conditions and compared with existing methods in terms of the response speed to fault, copper loss, peak phase current and maximum attainable torque to show the performance improvement.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".