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Enhancing the Efficiency of Dual Active Bridge Converter in Low-Voltage Supercapacitor Applications

2025· article· W7128787372 on OpenAlexaff
Henar Mike O. Canilang, S. Wang, Ning Zhu, Jiacheng Wang

Bibliographic record

Venuenot available
Typearticle
Language
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsSheridan CollegeSimon Fraser University
Fundersnot available
KeywordsDual (grammatical number)Thermal conductionSupercapacitorPower (physics)ConvertersMode (computer interface)InductorSwitching timeInductance

Abstract

fetched live from OpenAlex

This paper investigates discontinuous conduction mode (DCM) in the Dual Active Bridge (DAB) DC-DC converter to enhance its operational efficiency in supercapacitor (SC)based energy storage systems (ESS). SCs' low-voltage and high current characteristics pose a challenge for DAB when the converter needs to operate under a high-voltage conversion ratio. At high-voltage conversion ratio, conventional switching mode such as the continuous conduction mode (CCM) leads to higher conduction and switching losses. To address these challenges in efficiency, this study employs DCM switching as an alternative to CCM, which introduces a zero-crossing time (ZCT) interval during switching transitions. DCM facilitates zero-current switching (ZCS) and reduces conduction losses. Additionally, the elimination of specific switching transitions under low-voltage operating conditions enables consistent ZCS, further minimizing switching losses. This approach is particularly advantageous in configurations involving a highvoltage primary and a low-voltage, high-current secondary. Analytical modeling and steady-state derivation are provided to characterize the current and power behavior under different switching modes, and the theoretical findings are validated through simulation. The results demonstrate that DCM operation significantly lowers the power losses at low SC voltages, confirming the effectiveness of the ZCT-to-ZCS transition in enhancing DAB converter efficiency for SC applications.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.006
GPT teacher head0.233
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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