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Maximum Torque Per Ampere Control of Brushless DC Motors with Misaligned Hall Sensors

2025· article· en· W4409426886 on OpenAlexafffund
Manh Duong Phung, Matthew Hasman, Ziliang Feng, Juri Jatskevich

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSensorless Control of Electric Motors
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDC motorAmpereHall effect sensorTorqueElectrical engineeringPhysicsHall effectControl theory (sociology)Control (management)Computer scienceEngineeringMagnetVoltage

Abstract

fetched live from OpenAlex

Three-Phase Hall-Sensor-controlled brushless DC (BLDC) motors are widely used in many industrial and electric mobility applications due to their high efficiency, power density, and cost-effectiveness. A typical voltage-source inverter (VSI) with the 120° commutation controls the motor's stator currents based on the Hall sensor signals that give the rotor position at discrete intervals. However, many low-cost motors often have misaligned Hall sensors, leading to distorted switching sequences and degraded performance. Furthermore, the BLDC motors with large winding inductance have non-negligible commutation intervals that shift the operation angle away from the desirable maximum torque-per-Ampere (MTPA) operation. This paper extends the previous research in this area and combines the filtering of Hall sensor signals with the automatic correction of the commutation angle to maintain the MTPA operation. The effectiveness of the proposed method is demonstrated on a typical industrial motor with a large electrical time constant and misalignment of Hall sensors.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.216
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 head0.003
GPT teacher head0.184
Teacher spread0.181 · 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 designBench or experimental
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
Published2025
Admission routes2
Has abstractyes

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