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Record W2890419543 · doi:10.1109/tie.2018.2869355

A Transformerless Hybrid Modular Multilevel DC–DC Converter With DC Fault Ride-Through Capability

2018· article· en· W2890419543 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Industrial Electronics · 2018
Typearticle
Languageen
FieldEngineering
TopicHVDC Systems and Fault Protection
Canadian institutionsOpal-Rt Technologies (Canada)McGill University
Fundersnot available
KeywordsOvermodulationModular designTopology (electrical circuits)EngineeringNetwork topologyVoltageShunt (medical)Control theory (sociology)InverterElectronic engineeringComputer scienceElectrical engineeringControl (management)

Abstract

fetched live from OpenAlex

This paper proposes a hybrid modular multilevel dc-dc converter with dc fault ride-through capability. In each phase, the lower arm and shunt arm are composed of half-bridge submodules and full-bridge submodules (FBSMs) respectively, and the upper arm is composed of both types of submodules. The shunt arm eliminates the large ac filter required at the output of dc side. Moreover, it provides the bidirectional fault ride-through capability together with the FBSMs in the upper arm. Required kVA rating of the switches in the proposed topology is analyzed and compared to other topologies. With the optimal number of FBSMs in the upper and shunt arms designed by overmodulation, the proposed topology has a reduced kVA rating of switches, especially for the voltage conversion ratio above 0.54. A control strategy is presented to control the ac circulating current and balance the energy between the three arms. The performance of the proposed topology is validated by real-time simulation and a lab-scale test bench.

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.

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 score0.677
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 head0.024
GPT teacher head0.234
Teacher spread0.210 · 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