Hybrid Resonant and Non-Resonant Coupled-Inductor-Based Current-Fed DC–DC Converter
Bibliographic record
Abstract
This paper presents a hybrid resonant and non-resonant coupled-inductor-based current-fed DC-DC converter, designed for solar-tile microinverter (MI) applications requiring high voltage gain. In the proposed circuit, a boost half-bridge (BHB) is connected to the PV side, providing higher voltage for the half-bridge stage and reducing the primary conduction losses. Additionally, an active voltage-doubler rectifier is utilized on the secondary-side to achieve a two-fold voltage gain, thereby reducing the required transformer turns ratio and size. The proposed circuit is derived by integrating the input dc inductor of the BHB into a coupled-inductor, introducing an additional resonant path that enhances power transfer capacity without requiring extra active switches. The introduction of the resonant path contributes to narrow the switching-frequency range, reduce the turn-off current and switching losses, and improve the efficiency while increasing the power transfer capability compared to the non-resonant configurations. The design procedure is presented to minimize current stress, extend ZVS range, and reduce reverse input current. The ZVS regions for primary and secondary switches are determined under different load conditions and voltage gains. Two control parameters, phase-shift and switching frequency, emerges due to the active rectifier and the resonant coupled-inductor, providing more flexibility in regulating output power, minimizing back-flow power, and maintaining ZVS across all switches. Experimental results provided from a 100 W prototype, to validate the performance of the proposed converter.
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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 | 0.001 | 0.001 |
| 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".