An Extended-Speed Low-Ripple Torque Control of Switched Reluctance Motor Drives
Bibliographic record
Abstract
In this paper, an extended-speed low-ripple torque control of switched reluctance motor (SRM) drives using torque sharing function (TSF) is proposed. Two operational modes are defined for the online TSF during commutation: In Mode I, absolute value of rate of change of flux linkage (ARCFL) of incoming phase is higher than outgoing phase; in Mode II, ARCFL of outgoing phase is higher than incoming phase. In order to compensate the torque error produced by imperfect tracking of phase current, a proportional and integral compensator with torque error is added to the torque reference of outgoing phase in Mode I and incoming phase in Mode II. Therefore, the total torque is determined by the phase with lower ARCFL rather than the phase with higher ARCFL as in conventional TSFs. The maximum torque-ripple-free speed of the proposed TSF is increased to more than ten times as the best case in conventional TSFs. Finally, the proposed TSF is verified by both simulations and experiments with a 2.3 kW, 6000 rpm, three-phase 12/8 SRM operating in both linear magnetic and saturated magnetic regions. Results show that the proposed TSF has higher average torque, and much lower torque ripples compared to conventional TSFs.
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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 | 0.000 | 0.000 |
| 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".