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Record W2568097450 · doi:10.1109/iecon.2016.7793092

SoC FPGA-based field oriented control of BLDC motor using low resolution Hall sensor

2016· article· en· W2568097450 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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSensorless Control of Electric Motors
Canadian institutionsMicrosemi (Canada)
Fundersnot available
KeywordsTorque rippleField-programmable gate arrayRotor (electric)TorqueHall effect sensorCommutationVector controlComputer scienceControl theory (sociology)EngineeringElectrical engineeringDirect torque controlComputer hardwareInduction motorControl (management)PhysicsVoltageMagnetArtificial intelligence

Abstract

fetched live from OpenAlex

This paper presents an algorithm to generate a smooth rotor angle from Hall signals. Hall sensors are widely used in BLDC motor applications to provide rotor information for phase commutation, but the low angle resolution provided results in torque ripple and reduced efficiency. While the raw angle cannot be used directly, the rotor angle generated with the algorithm can be used in vector control to meet speed and torque demand on the drive with optimum power. The proposed algorithm has been designed to avoid multiplication and division operations for optimal use of FPGA resources to balance economical constraints with computational performance. It has been implemented in the Microsemi SmartFusion <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">®</sup> 2 SoC FPGA.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.673
Threshold uncertainty score0.564

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 head0.008
GPT teacher head0.202
Teacher spread0.194 · 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

Quick stats

Citations13
Published2016
Admission routes1
Has abstractyes

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