A Hybrid String-Inverter/Rectifier Soft-Switched Bidirectional DC/DC Converter
Bibliographic record
Abstract
In this article, a new bidirectional dc/dc converter topology based on a hybrid string-inverter/rectifier structure with an isolated CLLC resonant circuit is presented for energy storage applications. In this topology, a novel inverter/rectifier leg is presented that enables this circuit to operate in rectifying mode with much lower voltage ripple compared to the standard four-switch string rectifier circuit with the same capacitive filter. Compared to the dual-active-bridge circuit structure, the proposed inverter/rectifier leg is able to reduce the number of high-voltage switches required. A CLLC resonant circuit is employed to step-up/down the dc voltage levels. The operating principles of the proposed converter are discussed in this article. Silicon Carbide switches are used in both legs of the proposed converter, with zero-voltage switching turn-on and zero-current switching (ZCS) turn-off realized for all switches, whereas ZCS turn-on and off are achieved for all diodes. Simulation and experimental results are provided on a 1-kW, 100-kHz, 400-V/700-V converter system to highlight the merits of the proposed converter. Experimental results demonstrated that an efficiency of close to 97% is achieved in the proposed converter in both boost mode and buck mode at the full-load condition.
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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 | 0.001 |
| 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) | 0.006 | 0.002 |
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".