Fault-Tolerant Control of Open-Circuit Faults in Standard PMSM Drives Considering Torque Ripple and Copper Loss
Bibliographic record
Abstract
Although many auxiliary circuits based fault-tolerant solutions have been developed for three-phase motor drives, the standard three-phase motor drive without any auxiliary circuits still dominates the market. It is important to improve the fault-tolerant capability of standard motor drive. In this paper, a predictive current control based fault-tolerant control scheme is proposed to optimize the fault-tolerant performance of standard PMSM drives under open-phase fault and open-switch fault. In the proposed scheme for open-phase fault, the fault-tolerant current references considering reluctance torque and overcurrent endurance of motor drive are derived. On this basis, the fault-tolerant current references are further optimized to reduce the copper loss without increasing the torque ripple. Besides, a fundamental period based speed calculation method is proposed to eliminate the negative impact of speed fluctuation. In the proposed scheme for open-switch fault, a two-mode current control based fault-tolerant control is designed to reduce the copper loss and torque ripple by fully utilizing the remaining healthy switch in the faulty inverter leg. The validity of the proposed scheme is verified by experiments.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".