Wavelet Modulation With an Optimized Resolution-Level to Minimize Common-Mode Voltages in Variable Frequency Induction Motor Drives
Bibliographic record
Abstract
This article presents the employment of the wavelet modulation with an optimized resolution-level to minimize the common-mode voltage (CMV) in variable frequency induction motor drives. The optimization of the resolution-level approach allows adjusting the duration and location of each <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on</small> switching pulse generated by the wavelet modulation technique. Such adjustments can significantly reduce the energy allocated in the harmonic contents of stator voltages, thus minimizing the instantaneous unbalance in the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\textbf{3}\boldsymbol{\mathbf{\phi}}$</tex-math></inline-formula> stator voltages. As a result, the CMV and current can be minimized without additional filtering circuits and/or modification of the power converters comprising the drive. The proposed method to minimize the CMV is experimentally tested using a 10<bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>hp</i></b> induction motor frequency drive under various operating conditions. Test results show that optimizing the resolution-level has negligible impacts on control actions to operate the motor and/or dc link voltage.
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How this classification was reachedexpand
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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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.
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 teacher head, 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".