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Record W3005325829 · doi:10.1109/jestpe.2020.2972056

A Fault-Tolerant Five-Level Inverter Topology With Reduced Component Count for OEIM Drives

2020· article· en· W3005325829 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 Journal of Emerging and Selected Topics in Power Electronics · 2020
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsÉcole de Technologie Supérieure
FundersUniversiteit Leiden
KeywordsInverterGrid-tie inverterCapacitorTopology (electrical circuits)Redundancy (engineering)Control theory (sociology)VoltageComputer scienceFault toleranceEngineeringElectrical engineeringMaximum power point tracking

Abstract

fetched live from OpenAlex

This article proposes a fault-tolerant five-level inverter scheme for open-end induction motor (OEIM) drive application using a single dc link. The drive is fed with a primary inverter (a two-level inverter cascaded with a capacitor-fed H-bridge inverter) from one end and a secondary inverter (capacitor-fed two-level inverter) from the other end. The ratio of the dc-link voltage to the nominal capacitor voltage in the H-bridge and the secondary two-level inverter is maintained at 4:2:1. The capacitor balancing in the proposed scheme is achieved by space-vector (SV) redundancy. The proposed scheme gives five-level inverter operation with less number of components compared with other existing inverter topologies. Furthermore, the scheme provides fault-tolerant capability against a failure of the power switches in the H-bridges and the secondary two-level inverter. The experimental results in steady and transient states are presented. Also, the inverter operation during fault is provided to validate the effectiveness of the proposed scheme.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.855
Threshold uncertainty score0.732

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 head0.017
GPT teacher head0.234
Teacher spread0.217 · 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