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Record W3211557505 · doi:10.1109/jssc.2021.3123160

A Calibration-Free Energy-Efficient IC for Link-Adaptive Real-Time Energy Storage Optimization of CM Inductive Power Receivers

2021· article· en· W3211557505 on OpenAlexafffund
Mansour Taghadosi, Hossein Kassiri

Bibliographic record

VenueIEEE Journal of Solid-State Circuits · 2021
Typearticle
Languageen
FieldEngineering
TopicWireless Power Transfer Systems
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEnergy (signal processing)Computer scienceCapacitorPower (physics)CMOSElectrical engineeringElectronic engineeringMathematicsVoltageEngineeringPhysics

Abstract

fetched live from OpenAlex

The design, development, and experimental characterization of an integrated circuit (IC) for maximizing the energy storage efficiency in resonant inductive current-mode (CM) power receivers are presented. The IC is designed to monitor the receiver’s incident energy and to determine and employ an optimal timing scheme for controlling its operation to maximize energy storage for a given period of time. Thanks to continuous monitoring of incident waveform dynamics, the IC automatically adapts its optimal solution on-the-fly to any change in the inductive link’s physical or electrical parameters (e.g., <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Q$ </tex-math></inline-formula> -factor variations and coils movement). To minimize the IC’s power consumption, all the high-speed blocks for monitoring, optimization point computation, and system control are implemented using analog circuits, making the solution needless of a high-speed analog-to-digital converter (ADC)/digital-to-analog converter (DAC). The IC is fabricated in a standard 0.18 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> CMOS process with an active area of 0.45 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> . Its efficacy in real-time optimization of energy storage efficiency is experimentally validated for two different inductive links, showing perfect agreement with empirical measured data and theoretical predictions. Our measurement results show that by using the presented IC, the energy storage efficiency is improved by 53% and 67% for the two tested links, compared to the conservative schemes used for the receiver’s operation control. It has also been shown that the IC’s power consumption in the worst case scenario is two orders of magnitude smaller than the energy it saves through optimization. To the best of our knowledge, this is the first reported integrated link-adaptive calibration-free solution for optimizing the energy storage efficiency in CM inductive receivers.

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 score0.929
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 head0.012
GPT teacher head0.215
Teacher spread0.202 · 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

Citations7
Published2021
Admission routes2
Has abstractyes

Explore more

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