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Record W1993417600 · doi:10.1109/iecon.2013.6699887

Modified DC-link voltage balancing algorithm for a 3-level neutral point clamped (NPC) traction inverter based electric vehicle PMSM drive

2013· article· en· W1993417600 on OpenAlexaff
Abhijit Choudhury, Pragasen Pillay, Sheldon S. Williamson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsConcordia University
Fundersnot available
KeywordsPulse-width modulationTopology (electrical circuits)Control theory (sociology)VoltageComputer scienceTraction (geology)InverterTorqueSpace vector modulationAlgorithmEngineeringElectrical engineeringPhysics

Abstract

fetched live from OpenAlex

This paper presents a modified DC bus voltage balancing algorithm for a neutral-point clamped (NPC) three-level inverter based motor drives for permanent magnet synchronous machines (PMSM) used in electric vehicle applications. The topology used for DC bus voltage balancing is based on nearest three vectors (N3V) with a space vector pulse width modulation scheme (SV-PWM). In this scheme, the voltage space vectors are rearranged based on the four redundant small voltage vectors, to keep the two DC link capacitor voltages in their specific tolerance bands, even during fast transient conditions of the machine. This topology provides high stability and lower switching loss compared to the conventional N3V scheme. The performance of the proposed scheme is verified by simulation and hardware experimental tests.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.944
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 communication0.0000.001
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 head0.018
GPT teacher head0.210
Teacher spread0.192 · 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 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

Citations13
Published2013
Admission routes1
Has abstractyes

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