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Record W4398249837 · doi:10.1109/tte.2024.3404864

A ZVS Bidirectional 48-/12-V Converter With Magnetic Integration for 48-V Mild Hybrid Vehicles

2024· article· en· W4398249837 on OpenAlexaff
Mohammad Reza Mohammadi, Mohammad Ebrahimi, Alireza Safaee, S. Ali Khajehoddin

Bibliographic record

VenueIEEE Transactions on Transportation Electrification · 2024
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMaterials scienceComputer scienceBiomedical engineeringEngineering

Abstract

fetched live from OpenAlex

This paper presents a ZVS-bidirectional converter for 48V MHVs. The proposed converter boasts attractive features, including enhanced voltage gain, minimized voltage stresses, a shared electrical ground for input and output, positive output voltage polarity, and continuous low-ripple current on both sides facilitated by the presence of inductors. Additionally, the proposed converter benefits from a single-magnetic core integrating three-winding coupled inductors. In this arrangement, the currents in the second and third windings, which correspond to the currents of the converter’s 12V and 48V sides, are ripple-free, while the first winding experiences a sufficient current swing (i.e., TCM operation) to achieve ZVS. Consequently, both ZVS and current-ripple-cancellation are achieved using this magnetic integration. Mathematical and physical models, as well as magnetic system simulation, are used to elucidate the current-ripple-cancellation and to design the magnetic system. Variable-frequency control is applied to optimize the current ripple according to the output power, improving efficiency. Finally, we present the experimental results of an 800W Si-based prototype that operates under variable-frequency control within a switching frequency range of 250-500 kHz. The converter achieves a peak efficiency of 96.5%, with efficiencies of 96.1% and 96% in boost and buck modes at full-load conditions, respectively. Moreover, the converter retains above 94% power efficiency at above 25% of full load.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.966
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.215
Teacher spread0.201 · 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 teacher head, not a consensus.

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

Citations3
Published2024
Admission routes1
Has abstractyes

Explore more

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