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A Framework for Practical Design of Switching Nodes with Parallel-Connected MOSFETs

2022· article· en· W4284887985 on OpenAlexafffund
Rachit Pradhan, Mohamed I. Hassan, Alan Dorneles Callegaro, Piranavan Suntharalingam, Mario F. Cruz, Ali Emadi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSilicon Carbide Semiconductor Technologies
Canadian institutionsMcMaster University
FundersCMC Microsystems
KeywordsFlexibility (engineering)MOSFETNode (physics)Computer sciencePower (physics)Electrical engineeringInterface (matter)Power MOSFETElectronic engineeringEngineeringTransistorVoltage

Abstract

fetched live from OpenAlex

The number of high current carrying interfaces originating from power-dense electronic sub-systems is increasing with the rise of electrified transportation. The order of magnitude of currents handled by these interfaces is in hundreds of amperes, and is generally beyond the power-handling capability of a single power switch. To manage these high current levels, discrete switch paralleling is a preferred practice compared to usage of power modules for two reasons; flexibility in packaging based on available thermal interfaces, and eliminating the need to over-design the solution. While the challenges in MOSFET paralleling and their mitigation techniques have been addressed in literature, this paper focuses on presenting a generalized framework that can be applied for the practical design of any switching node with parallel-connected MOSFETs. Utilizing this design framework aims to reduce the risk of revising hardware designs due to non-compliance with performance expectations on the electrical and thermo-mechanical fronts.

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 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 score0.329
Threshold uncertainty score0.485

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)0.0000.000

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 head0.051
GPT teacher head0.283
Teacher spread0.232 · 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.

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

Citations3
Published2022
Admission routes2
Has abstractyes

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