Braking a Variable Flux-Intensifying IPMSM in Minimal Time
Bibliographic record
Abstract
This paper proposes a method for braking the variable flux-intensifying interior permanent-magnet synchronous motor (FI IPMSM) under a minimal time condition while operating in the high-speed region. The rare-earth PMs retain its magnetization as the flux weakening current is decreased. This inherent feature of the PMs makes the braking torque maximization possible for IPMSMs, thus minimal-time braking can be achieved. In contrast, the low-coercive magnets utilized in variable-flux IPMSMs are partially demagnetized in the highspeed region. This means that the variable-flux IPMSM takes a longer time to stop if compared to the IPMSM. Supplying a magnetizing current that ranges from 1 to 3 p.u. in the highspeed region while the inverter is running out of voltage is quite challenging. In this paper, an analytical solution to the amount of magnetizing current required to maximize the braking torque based on the available voltage to ensure minimal-time braking is presented. The simulated and experimental results obtained using a 5-hp variable FI IPMSM show the validity of the proposed braking scheme. A front-end active rectifier is utilized to recuperate the braking energy and maintain the dc bus voltage constant.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".