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Record W3001134072 · doi:10.5539/cis.v13n2p1

Software Based Programmable IGBT IPM Dead-Time Insertion Module Using 16-bit Micro Controller for BLDC Motor Control Application with 3-Phase Sinusoidal and Trapezoidal Drive

2020· article· en· W3001134072 on OpenAlexvenueno aff
Hastanto SM Widodo, Suryadi Harmanto, Sarifuddin Madenda, Lingga Hermanto

Bibliographic record

VenueComputer and Information Science · 2020
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsnot available
Fundersnot available
KeywordsInsulated-gate bipolar transistorComputer scienceTimerRobustness (evolution)Motor driveMotor controllerEmbedded systemSoftwareTorque rippleComputer hardwarePower (physics)Electrical engineeringMicrocontrollerDirect torque controlInduction motorVoltageEngineering

Abstract

fetched live from OpenAlex

Motor control application, especially for medium to high power implementation, will benefit the most with the compactness and robustness of an Integrated Power Module of Insulated Gate Bipolar Transistor also known as IGBT IPM. Nevertheless, implementation motor control with a general purpose micro-processor without any advance timer functionality with IGBT IPM will be challenged by the Dead-Time switching requirement in its power switching implementation. Further, a combined sinusoidal and trapezoidal drive of a motor control is also believed will provides a better control performance in term of lower torque ripple and higher motor top speed. This paper proposed a low-cost alternative to address the requirement by implementing a software based dead time functionality using the low cost 16-bit micro controller board with capability of serving up sinusoidal drive as well as trapezoidal drive for motor control application.

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 score0.935
Threshold uncertainty score0.482

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 communication0.0000.002
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 head0.009
GPT teacher head0.207
Teacher spread0.198 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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