MétaCan
Menu
Back to cohort
Record W2030107307 · doi:10.1109/apec.2013.6520475

Mixed-signal CPM controlled DC-DC converter IC with embedded power management for digital loads

2013· article· en· W2030107307 on OpenAlexaff
Amir Parayandeh, Aleksandar Prodić

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicLow-power high-performance VLSI design
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDigital controlElectrical engineeringElectronic engineeringController (irrigation)Power (physics)Boost converterVoltageComputer scienceBuck converterDigital signalPower factorEngineeringDigital signal processing

Abstract

fetched live from OpenAlex

This paper presents a novel system and a method for dynamic minimum power point tracking of digital loads in portable applications. The system combines a dc-dc power stage converter IC and the supplied digital load. The dc-dc converter IC employs a mixed-signal current mode (CPM) controller to regulate the supply voltage of an on-chip integrated digital load. The CPM controller is also utilized to obtain information about the input current of the system in real-time, eliminating the need for a dedicated power sensing circuits. The obtained information about the current is utilized by a minimum power point tracking (MiPPT) controller. The MiPPT sets the supply and threshold voltages for the digital load to minimize its power consumption while maintaining a targeted frequency. The dc-dc converter IC, providing 600mW of power, and its digital load IC are fabricated in a 0.13 μm process. Experimental results verify that the introduced system results in up to a 30% lower power consumption.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.172
Teacher spread0.167 · 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 designBench or experimental
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
Published2013
Admission routes1
Has abstractyes

Explore more

Same topicLow-power high-performance VLSI designFrench-language works237,207