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Record W2626408523

Interactive Flexible Switch Mode Power Supplies for Reducing Volume and Improving Efficiency

2013· dissertation· en· W2626408523 on OpenAlexfundno aff
S. M. Ahsanuzzaman

Bibliographic record

VenueTSpace (University of Toronto) · 2013
Typedissertation
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Toronto
KeywordsVolume (thermodynamics)Power (physics)Electrical engineeringComputer scienceAutomotive engineeringProcess engineeringEngineeringPhysics
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this thesis is to introduce a family of interactive Switch Mode Power Supplies (SMPS) for reducing the overall volume of the conventional converter topologies in low-to-medium power (up to 60W) applications. As shown in this thesis, the interaction between power supplies and electronic devices can be incorporated with emerging digital controllers for SMPS, to implement flexible converter topologies. These flexible topologies dynamically change the converter configuration, based on the load requirement, to provide near ideal transient response and/or improved efficiency over a wide range of operating conditions. This interaction relaxes the energy storage requirement for the converter reactive components and results in a low volume implementation. The interaction with the SMPS can be between the electronic load and the power supply or different conversion stages of a multi-stage converter. The effectiveness of the introduced family of SMPS is verified on digitally controlled dc-dc and ac-dc converter topologies.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

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 communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.005
GPT teacher head0.224
Teacher spread0.219 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2013
Admission routes1
Has abstractyes

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