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Record W4411446810 · doi:10.1109/tie.2025.3577372

Nonisolated High Step-Up Impedance Source DC–DC Converter With ZVS Operation, Low Switches Voltage Stress, and Diodes Losses

2025· article· en· W4411446810 on OpenAlexaff
Maryam Hajilou, Hosein Farzanehfard, S. Ali Khajehoddin

Bibliographic record

VenueIEEE Transactions on Industrial Electronics · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDiodeMaterials scienceElectrical impedanceStress (linguistics)Electrical engineeringOptoelectronicsVoltageCharge pumpLow voltageCapacitorElectronic engineeringEngineering

Abstract

fetched live from OpenAlex

In this article, a high voltage gain quasi-Z-source converter with reduced voltage stress and low diode loss is proposed. The innovative integration of voltage enhancement methods with the basic structure provides high conversion ratio with reduced imposed voltage on the switches. The input side diode loss in the basic quasi-Z-source converter along with hard switching operation and substantial switch voltage stress lead to low efficiency. Due to the modifications made in the proposed structure, the diode losses are eliminated, the switches voltage stress is remarkably reduced, and zero voltage switching conditions are provided for all switches which remove the capacitive turn-<sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on</small> loss. Additionally, the presented converter benefits from continuous input current with low ripple and common ground between the input and output. The mentioned advantages and features make the proposed converter stand out among existing quasi-Z-source topologies. The converter is fully analyzed, a laboratory prototype is implemented, and the results are compared with other counterparts to confirm the achieved features.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.855
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 integrity0.0000.001
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 head0.007
GPT teacher head0.204
Teacher spread0.197 · 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 designSimulation or modeling
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

Explore more

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