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Record W1970990078 · doi:10.1109/tii.2014.2361656

Physics-Based Device-Level Power Electronic Circuit Hardware Emulation on FPGA

2014· article· en· W1970990078 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Industrial Informatics · 2014
Typearticle
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsField-programmable gate arrayEmulationPhysicsElectrical engineeringPower (physics)Electronic circuitElectronicsHardware emulationComputer hardwareEmbedded systemElectronic engineeringComputer scienceEngineering

Abstract

fetched live from OpenAlex

Accurate models of power electronic devices are necessary for hardware-in-the-loop (HIL) simulators. This paper proposes a digital hardware emulation of device-level models for the insulated gate bipolar transistor (IGBT) and the power diode on the field programmable gate array (FPGA). The hardware emulation utilizes detailed physics-based nonlinear models for these devices, and features a fully paralleled implementation using an accurate floating-point data representation in VHSIC hardware description language (VHDL) language. A dc-dc buck converter circuit is emulated to validate the hardware IGBT and diode models, and the nonlinear circuit simulation process. The captured oscilloscope results demonstrate high accuracy of the emulator in comparison to the offline simulation of the original system using Saber software.

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.

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 score0.976
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.048
GPT teacher head0.236
Teacher spread0.188 · 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