MétaCan
Menu
Back to cohort
Record W2052186474 · doi:10.1108/03321641011008037

Instantaneous torque control using flux‐based commutation and phase‐torque distribution technique for SR motor EV

2009· article· en· W2052186474 on OpenAlexaff
Hiroki Goto, Ayumu Nishimiya, Hai‐Jiao Guo, O. Ichinokura

Bibliographic record

VenueCOMPEL The International Journal for Computation and Mathematics in Electrical and Electronic Engineering · 2009
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsHatch (Canada)
Fundersnot available
KeywordsDirect torque controlSwitched reluctance motorControl theory (sociology)Torque rippleStall torqueTorqueDamping torqueTorque motorTorque limiterComputer scienceVector controlEngineeringInduction motorVoltagePhysicsElectrical engineeringControl (management)

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to propose a new instantaneous torque control method for switched reluctance motor (SR motor) and presents experimental data in electric vehicle (EV) application. Design/methodology/approach The proposed control method uses two kind of techniques: a flux‐based commutation technique prevents the negative phase torque always. On the other hand, a direct phase‐torque distribution technique gives suitable each phase‐torque command under limited DC voltage. These techniques can track motor torque to the command. These control schemes are implemented on a small processor and a field programmable gate array. Findings The experimental results of the EV show small torque ripple at low speed on both acceleration and regenerative braking. Changing the parameter of the current stop angle can improve torque ripple at high speed. The proposed method can effectively control motor torque. Practical implications The proposed method can reduce torque ripple but the implementation is very simple. The proposed control method can be used for any applications. So, that contributes to expand the application of SR motors. Originality/value The proposed control scheme requires just static torque curve obtain by finite element analysis or simple experiments. Complex parameters, such as nonlinear inductance, current to torque profiles, and other heuristics parameters, are not necessary. The proposed control is simple but practical.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.922
Threshold uncertainty score0.577

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 head0.011
GPT teacher head0.270
Teacher spread0.259 · 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

Citations21
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueCOMPEL The International Journal for Computation and Mathematics in Electrical and Electronic EngineeringSame topicElectric Motor Design and AnalysisFrench-language works237,207