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Record W4388192114 · doi:10.18280/mmep.100526

Peak Current Mode Control of a Two-Module Independent-Input Series-Output Boost Converter with Mismatched Inductors

2023· article· en· W4388192114 on OpenAlexvenueno aff
M.R.D. Al-Mothafar

Bibliographic record

VenueMathematical Modelling and Engineering Problems · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsnot available
Fundersnot available
KeywordsInductorSeries (stratigraphy)Current (fluid)Control theory (sociology)Mode (computer interface)Boost converterComputer scienceControl (management)EngineeringElectrical engineeringVoltageBiology

Abstract

fetched live from OpenAlex

This study investigates the application of peak current-mode control to a dual-module, independent-input, series-output boost DC-DC converter characterized by mismatched inductors.The converter, operating in continuous-conduction mode, incorporates nonidentical modules, each supplied by a distinct voltage source while their outputs are interconnected in series.A small-signal state-space averaged model, useful for individual module control, is proposed.Utilizing this model, both direct and crosscoupling control-to-output voltage small-signal responses under inductor mismatch are generated with MATLAB assistance.A conventional Type-2 Proportional-Integral controller is designed for the module voltage loop, guided by the direct control-tooutput voltage responses.The impact of inductor mismatch on the transient performance of the module input current and output voltage under step changes in the load current and module source voltage is examined.The cycle-by-cycle simulations conducted via PSIM demonstrate significant agreement with the model predictions.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.852
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.216
Teacher spread0.199 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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