Decoupled Dual-PWM Control for Naturally Commutated Current-Fed Dual-Active-Bridge DC/DC Converter
Bibliographic record
Abstract
The naturally commutated current-fed dual-active-bridge (CF-DAB) dc/dc converter is a suitable solution for the distributed generation system with low input current ripple and convenient current control. However, the efficiency under light load conditions is still a challenging issue with existing modulation schemes. In this article, a decoupled dual-pulse width modulation (PWM) control strategy is proposed to enhance the efficiency within a wide load range. The proposed modulation adjusts turn-on moments of secondary-side switches flexibly and charges the leakage inductor properly based on the instantaneous input current. The peak leakage inductor current, primary-side rms current, and the corresponding losses are reduced effectively compared to existing methods. Meanwhile, the proposed modulation strategy avoids the interactions between the primary-side duty cycle and the secondary-side duty cycle so as to decouple the voltage conversion ratio with leakage inductance and load conditions and simplify the control-loop design. The design process, power loss analysis, and implementation of the proposed modulation strategy are presented in detail. The impacts of deviations in parameters of input inductor and leakage inductor are also analyzed. Based on parameter estimation, a specific compensation loop without an additional current sensor is proposed to further improve the stability of the closed-loop control for the converter. The experimental results are given to verify the theoretical analysis and validity of the proposed modulation.
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".