A Novel Non-Isolated Bidirectional DC-DC Converter with Improved Current Ripples for Low-Voltage On-Board Charging
Bibliographic record
Abstract
This paper presents a novel single-phase non-isolated bidirectional buck converter topology. The proposed converter uses a basic switching cell structure with a coupled inductor and an interleaving switching scheme. This article addresses a crucial challenge in bidirectional DC-DC conversion by prioritizing reducing output current ripples and minimizing filter inductor size. The employed method includes using MOSFETs with fast recovery diodes to mitigate reverse recovery and body diode losses. Furthermore, the optimization of the switching frequency of the output inductor to be twice the actual switching frequency contributes to reducing the component size of the converter. The coupled inductor also helps to reduce stress on components by distributing currents among its legs. The experimental result demonstrates the proposed converter has a very low ripple current as compared to the conventional converter. The low current ripples and smaller filter inductor size enabled by high-frequency operation have improved the efficiency and size of the converter. A common ground between input and output terminals ensures robust performance without common mode current concerns. Overall, the proposed converter represents a significant improvement in DC-DC converters, promising enhanced efficiency, reliability, and compactness in bidirectional DC-DC conversion systems. In order to verify the performance of the proposed converter, a 460 W buck converter prototype was built and tested.
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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".