MétaCan
Menu
Back to cohort
Record W3011584958 · doi:10.3390/en13051292

An Extremely High Power Density Asymmetrical Back-to-Back Converter for Aerospace Motor Drive Applications

2020· article· en· W3011584958 on OpenAlexaff
Yifan Zhang, Chushan Li, Dewei Xu, Wuhua Li, Jian Zhang, Hao Ma, Xiangning He

Bibliographic record

VenueEnergies · 2020
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsToronto Metropolitan University
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsAerospacePower densityRectifier (neural networks)Automotive engineeringVoltagePower (physics)Electrical engineeringEngineeringHeat sinkTopology (electrical circuits)Electronic engineeringComputer scienceAerospace engineering

Abstract

fetched live from OpenAlex

Higher-voltage-standard and higher-power-rating aerospace power systems are being investigated intensively in the aerospace industry to address challenges in terms of improving emissions, fuel economy, and also cost. Multilevel converter topologies become attractive because of their higher efficiency under high-voltage and high-switching-frequency conditions. In this paper, an asymmetrical-voltage-level back-to-back multilevel converter is proposed, which consists of a five-level (5L) rectifier stage and a three-level (3L) inverter stage. Based on the comparison, such an asymmetrical back-to-back structure can achieve high efficiency and minimize the converter weight on both rectifier and inverter sides. A compact triple-surface-mounted heatsink structure is designed to realize high density and manufacturable thermal management. This topology and structure are evaluated with a full-rating prototype. According to the evaluation, the achieved power density is 2.61 kVA/kg, which is 30% higher than that of traditional solutions. The efficiency at the rated power of the back-to-back system is 95.8%.

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 categoriesnone
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 score0.852
Threshold uncertainty score0.891

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)0.0000.001

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 head0.018
GPT teacher head0.221
Teacher spread0.203 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations7
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueEnergiesSame topicMultilevel Inverters and ConvertersFrench-language works237,207