Determination of Parameters of Asynchronous Electric Machines with Asymmetrical Windings of Electric Locomotives
Bibliographic record
Abstract
This article is devoted to development of a method for calculating the parameters of an asynchronous motor of an electric locomotive with asymmetrical windings of stator and rotor. A method for determining self and mutual inductances of the stator and rotor phases of an asynchronous motor with asymmetric windings and their relations to mechanical variables is proposed. It is based on comparing two equations of stored magnetic energy, one equation calculated through induction, magnetic field strength and geometrical dimensions and another equation calculated through the parameters of the motor circuits. It is shown that the obtained solutions correspond to the previously existing methods, but they give the additional possibilities in mathematical modeling. The proposed technical solution allows higher accuracy developing of a mathematical model of a drive with an asynchronous motor having asymmetrical stator and rotor windings for studying dynamic processes during the operation of the specified drive, in particular, the drive of auxiliary machines for electric locomotive, where an asynchronous motor with asymmetrical stator windings is used as a phase release.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".