Saturable and Decoupled Constant-Parameter VBR Model for Six-Phase Synchronous Machines in State-Variable Simulation Programs
Bibliographic record
Abstract
Six-phase electrical machines are often found in special purpose applications, such as vehicular, ship, and aircraft power systems, and are now becoming considered in renewable energy generation. For design and analysis of such power systems, accurate and numerically efficient models are required for various transient simulation programs. Recently, a constant-parameter voltage-behind-reactance (CPVBR) model has been developed for magnetically linear six-phase synchronous machines as an alternative to the conventional qd0 and VBR machine models. In this paper, a saturable CPVBR model is presented for six-phase machines, which includes the main flux saturation and achieves magnetically decoupled and constant RL interfacing branches. The new magnetically decoupled CPVBR (DCPVBR) model has many advantages for implementation in commonly available simulation programs where it can be easily interfaced with inductive and/or power-electronic circuit elements. The proposed DCPVBR model is demonstrated to have improved computational performance compared to the conventional qd0 and VBR models.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".