Maximum-Torque-per-Square-Ampere Control for Interior PMSMs Considering Cross-Saturation Inductances
Bibliographic record
Abstract
This article proposes an efficient maximum-torque-per-square-ampere (MTPSA) control for the interior permanent magnet synchronous machines (IPMSMs). The objective of the MTPSA control is to find the optimal current angle, denoted as MTPSA angle, to maximize the ratio of the output torque to the square of the stator current. The proposed MTPSA control is equivalent to the maximum-torque-per-ampere (MTPA) control, but it can eliminate the need of machine parameters and thus is independent of parameter variation. This article first derives the MTPSA control objective from the machine model considering cross-coupling inductances. Then, computation-efficient gradient descent algorithm is employed to detect the MTPSA angle from the derived objective. The proposed MTPSA control is based on available measurements without the need of machine parameters and invasive signal injection, which has not been simultaneously achieved in existing MTPA controls. The proposed control is validated with simulations, experiments, and comparisons with existing approaches on a laboratory IPMSM.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".