Non-Isolated High Voltage Gain Bidirectional DC-DC Converters: A Review
Bibliographic record
Abstract
Battery storage systems have been developed for various applications, from power generation in wind and solar power plants to electric vehicles. Bidirectional DC-DC converters (BDCs) are key elements in battery storage systems as they allow power flow in two directions when operating in charging and discharging modes. BDCs are effective solutions to provide an appropriate output voltage in low-voltage battery storage systems. Generally, there are two major types of BDCs, isolated and nonisolated structures. Non-isolated BDCs have lower volume, weight, and power losses, and thus, are suitable where a compact structure is needed, and galvanic isolation is not mandatory. In this paper, a comprehensive review of recent non-isolated high voltage gain BDCs is conducted. Based on structures and components of BDCs, there are four types of methods to increase the voltage gain in these converters: capacitor-base, inductor-base, combined capacitor and inductor-base, and mixed structures-based methods. In this paper, the operational principle of each type of methods is examined in detail and their advantages and disadvantages are compared. The future research directions in this area are also recommended.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".