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Record W2144208853 · doi:10.1109/cipe.1998.779675

Simulation of active power filters using switching functions

2002· article· en· W2144208853 on OpenAlexaff
G. Joós

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Compatibility and Noise Suppression
Canadian institutionsConcordia University
Fundersnot available
KeywordsConvertersElectronic engineeringComputer scienceCapacitorInductorElectronic circuitActive filterTransient (computer programming)Switched capacitorSwitching powerFilter (signal processing)Power (physics)EngineeringVoltageElectrical engineering

Abstract

fetched live from OpenAlex

The operation of static power converters used in active filters can be simulated by means of widely available circuit simulation software packages such as PSpice. In these studies, converters are usually modeled as a set of real or idealized switches, which may result in long execution times and possible convergence problems, particularly in complex circuits. This paper proposes the use of macromodels to simulate active filters. The macromodels are based on converter switching functions rather than actual circuit components, and they are well suited for steady state and large signal transient analysis at the system level. In this approach, the converters are simulated as multiport networks avoiding the physical nonlinear micromodels associated with power switches. Computer memory and execution times required for the simulation of the power circuit are thereby significantly reduced. The procedure also allows rapid design of filter components, in particular passive elements such as inductors and capacitors. Complete examples of typical shunt filters are given to illustrate the effectiveness of the proposed models.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score0.999

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)0.0020.000

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 head0.021
GPT teacher head0.228
Teacher spread0.207 · 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

Citations4
Published2002
Admission routes1
Has abstractyes

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