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Optimized SHE-PWAM with Maximum Harmonic Elimination and Minimum Switching Frequency for PEC9 Inverter

2020· article· en· W3017254516 on OpenAlexaff
Mohammad Sharifzadeh, Mohammad Babaie, Majid Mehrasa, Gabriel Chouinard, Kamal Al‐Haddad

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsÉcole de Technologie SupérieureUniversité du Québec à Montréal
Fundersnot available
KeywordsPulse-width modulationCapacitorWaveformVoltageControl theory (sociology)HarmonicInverterMATLABHarmonic analysisAmplitudeComputer scienceElectronic engineeringElectrical engineeringEngineeringPhysicsAcousticsOptics

Abstract

fetched live from OpenAlex

This article introduces an Optimized SHE-Pulse Width and Amplitude Modulation (OSHE-PWAM) for single-DC source, single-phase nine-level Packed E-Cell (PEC9) to suppress maximum harmonic while switching frequency is minimized. PEC9 is a developed compact multilevel inverter based on the horizontal extension of capacitors to provide single auxiliary DC-bus and effective charging and discharging states for active capacitor voltage balancing. Based on the proposed OSHE, both switching angles and DC input voltage amplitude are considered as variable in the conventional SHE equations and new equations are developed to deal with maximum harmonic elimination. On the other hand, OSHE also handles capacitor voltage balancing by defining a symmetrical preprogramed output voltage waveform for establishing SHE equations. Simulation results are attained by Matlab-Simulink and confirm the excellent operation of the OSHE-PWM obtaining maximum harmonic elimination and achieving capacitor voltage balancing in PEC9 inverter while the switching frequency is minimized.

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 score0.988
Threshold uncertainty score0.688

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 head0.019
GPT teacher head0.199
Teacher spread0.180 · 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

Citations22
Published2020
Admission routes1
Has abstractyes

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