Ultra-Fast Dynamic Response and Current Harmonic Reduction in PFC Applications
Bibliographic record
Abstract
This article introduces a digital zero crossing voltage control (ZCVC) strategy designed for general power factor correction (PFC) applications. The ZCVC approach performs voltage control calculations and updates the current reference precisely at input voltage zero-crossings. This timing ensures that the control output remains constant for each half-grid cycle, resulting in a pure sinusoidal ac current waveform. This method effectively eliminates second harmonic distortions in the bus voltage without requiring a notch filter (NF), thereby reducing even harmonics from the RMS filter. ZCVC offers a significantly faster dynamic response, achieving stability within 1.5 grid cycles during load changes, input voltage fluctuations, or step changes in output voltage reference. This preserves a power factor close to unity and results in very low total harmonic distortion. Furthermore, the proposed ZCVC considerably reduces the computational burden on the microcontroller by minimizing the execution of the digital voltage loop controller per grid cycle, thereby eliminating the need for NFs. The mathematical average model of the ZCVC is derived for general PFC applications. Various scenarios are simulated to validate the effectiveness of this method compared to prior approaches. The implementation of ZCVC on a 7.2 kW GaN-based interleaved totem pole PFC confirms the claimed improvements, demonstrating four times faster dynamic response and very low harmonic distortion. Additionally, the ZCVC reduces voltage sampling and control computations from a typical range of 200 times per grid cycle to only two times, achieved by eliminating the need for notch and low-pass filters.
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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 | 0.000 | 0.001 |
| 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".