Vector controlled drive to measure inductances of variable flux machine
Bibliographic record
Abstract
Variable flux machines use low coercive-force magnets to control the air-gap flux density. The magnet flux is controlled by applying direct-axis armature current pulses. The magnetization state of the magnets depends on the peak value of the direct-axis current. Any overshoot in the direct-axis current adversely affects the magnetization state. As the controller parameters are dependent on the inductance values, accurate estimation of inductances and their dependence on the magnetization level will allow a proper design of controllers, improving the dynamic performance of the drive. Further, the estimates of current dependent inductances can be used for utilization of the available reluctance torque. This paper presents an inductance measurement method for variable flux machines using vector controlled drive. The advantage of the proposed scheme is that the measurement of both direct and quadrature-axis inductances can be performed at any arbitrary rotor position, requiring no change in rotor setup either to demagnetize or re-magnetize the magnets. Experimental results are provided for various magnetization levels. The comparison of inductances show that both direct and quadrature-axis inductances decrease with an increase in the magnetization level.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".