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A Single-Phase MMC-based Solid-State Transformer Suitable for EV Charging

2024· article· en· W4407317120 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectrical Contact Performance and Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSolid-stateTransformerMaterials scienceElectrical engineeringComputer scienceOptoelectronicsElectronic engineeringEngineering physicsVoltageEngineering

Abstract

fetched live from OpenAlex

This paper introduces a single-phase ac-dc solid-state transformer, based on the modular multilevel converter topology, termed the 2-String 2-Inductor MMC. Designed to link a medium-voltage ac network to a low-voltage dc load, it facilitates power transfer at a sub-megawatt scale, well suited for electric vehicle charging applications. Compared to other single-transformer MMC-based ac-dc SSTs, this topology significantly reduces size and volume by employing a higher frequency transformer. A modulation scheme, termed the Harmonic Shaping Nearest-Level Modulation, is developed to generate a modulated voltage with a sinusoidally varying time-averaged value while maintaining a constant switching frequency harmonic component over each sampling period. Simulation results of a 6-module, 4-kW converter in PLECS validate the proposed topology, control, and modulation design.

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 categoriesnone
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 score0.758
Threshold uncertainty score0.481

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 head0.015
GPT teacher head0.273
Teacher spread0.257 · 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