An Adaptive Energy Storage Technique for Efficiency Improvement of Single-Stage Three-Level Resonant AC/DC Converters
Bibliographic record
Abstract
The use of single-stage power-factor-corrected (SSPFC) three-level resonant ac/dc converters solves many problems that present SSPFC converters face today, namely, high component stresses, high circulating currents, and low efficiency. This makes single-stage three-level resonant ac/dc converters a good candidate for high-power applications. These converters provide the flexibility of simultaneously using two control variables. They can operate with a combined variable-frequency and asymmetrical pulsewidth modulation or with a combined variable-frequency phase-shift modulation. This provides good regulation of the output voltage, dc-bus voltage, and input current. The drawback of these methods is that the efficiency of the converter drops as the load is reduced because the converter starts to drift away from its resonance frequency, thus leading to more circulating currents and conduction losses. Therefore, a load-adaptive energy storage technique is proposed in this paper to guarantee the converter operation near its maximum efficiency point for a wide range of loading. This leads to almost constant converter efficiency from full load to 40% load. The use of interleaved converters is also proposed to extend the constant efficiency range of operation to lighter loads (15%-20% of full load). Analytical simulation and experimental results are presented to verify the proposed methods.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".