Using Multiple Reference Frame Theory for Considering Harmonics in Average-Value Modeling of Diode Rectifiers
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Bibliographic record
Abstract
Line-commutated converters (LCCs) are widely used in various high-power applications such as generator-rectifier systems, exciters, front-end rectifier loads, and classic high voltage dc systems. Among various techniques used for modeling LCC systems, the dynamic average value modeling (AVM) wherein the effect of switching is neglected or averaged over a prototypical switching interval has become indispensible since it results in continuous, linearizable, and computationally efficient models. The conventional AVMs can only predict the fundamental component of the ac voltages and currents, and neglect the harmonics injected at the ac side by the switching converter. In this paper, a recently proposed parametric average-value modeling (PAVM) approach is extended using multiple reference frame theory to include the significant harmonics of interest (e.g., fifth and seventh) for diode rectifiers. The new PAVM is verified against the detailed simulation in steady-state and transient studies, and is effective in predicting the transient waveforms, while achieving significant computational advantage (speed up) in time-domain simulation over conventional models.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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.
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