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Record W2966490305 · doi:10.1109/compel.2019.8769618

PWM Control of a Dual Inverter Drive using a Floating Capacitor Inverter

2019· article· en· W2966490305 on OpenAlexaff
Sukhjit Singh, Chatumal Perera, Gregory J. Kish, John Salmon

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPulse-width modulationInverterControl theory (sociology)VoltageCapacitorWaveformComputer scienceInduction motorEngineeringElectronic engineeringElectrical engineeringControl (management)

Abstract

fetched live from OpenAlex

A carrier-based pwm scheme is presented for a dual inverter drive operating an open winding induction machine. One inverter is supplied from a dc power source while the other uses a floating capacitor dc voltage source. The output voltages of the two inverters have a nominal 90° phase shift relative to each other and low quality pwm motor voltages is obtained when using "standard" pwm techniques. Two pwm controllers are compared: 1R2C uses a single reference and a dual carrier to control a switch; 2R2C uses both a dual carrier and a dual reference signal (phase-difference and phase-average). The latter scheme allows for independent control of the two inverter output voltages while simultaneously coordinating their pwm switching patterns to obtain high quality motor pwm voltages. Independent inverter voltage control allows a field-oriented controller to be used for a fast motor speed response, whilst allowing decoupled control of the floating inverter dc voltage. The 2R2C pwm scheme is shown to produce a 5-level "effective line voltage" and is compared with several alternatives using either a single or dual inverter drive. The quality of the pwm waveforms is demonstrated using simulations, load current THDF, and the line voltage harmonic volt-seconds. Results are experimentally validated using a DSP digital controller.

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 categoriesInsufficient payload (model declined to judge)
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 score0.977
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.189
Teacher spread0.179 · 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.

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

Citations6
Published2019
Admission routes1
Has abstractyes

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