A Fixed-Frequency <inline-formula> <tex-math notation="TeX">$LCL$</tex-math></inline-formula>-Type Series Resonant Converter With a Capacitive Output Filter Using a Modified Gating Scheme
Bibliographic record
Abstract
A fixed-frequency modified (or LCL-type) series resonant converter (SRC) with a capacitive output filter using a modified gating scheme is proposed. Steady-state analysis of the converter using an approximate complex ac circuit analysis method is presented. Based on the analysis, a simple design procedure is given and illustrated with a design example of a 50- to 100-V dc input, 200-W, 200-V dc output converter. Due to the increased number of switches operating with zero-voltage switching, this converter with the modified gating scheme gives higher efficiency as compared to that with the regular phase-shift gating scheme. With minimum input voltage, this converter requires a narrow variation in pulsewidth for a wide variation in the load current, whereas the peak current through the switches decreases with the load current. Detailed PSIM simulation results are presented to substantiate the performance of the designed converter for varying input voltage and load conditions. In addition, an experimental model of the designed converter has been built, and waveforms obtained using the experimental setup are presented. A comparison of theoretical, simulation, and experimental results is given in the form of a table.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".