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Record W2886485116 · doi:10.1109/tvt.2018.2865852

Investigation of Interior Permanent Magnet Motor With Dampers for Electric Vehicle Propulsion and Mitigation of Saliency Effect During Integrated Charging Operation

2018· article· en· W2886485116 on OpenAlexaff
K. Lakshmi Varaha Iyer, Chunyan Lai, Shruthi Mukundan, Himavarsha Dhulipati, Kaushik Mukherjee, Narayan C. Kar

Bibliographic record

VenueIEEE Transactions on Vehicular Technology · 2018
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsConcordia UniversityUniversity of Windsor
Fundersnot available
KeywordsAutomotive engineeringPropulsionDamperElectric vehicleMagnetEngineeringElectrically powered spacecraft propulsionElectrical engineeringAerospace engineeringStructural engineeringPower (physics)Physics

Abstract

fetched live from OpenAlex

Power electronics and motor drive components existing in a conventional electric vehicle (EV) drivetrain employed to propel the EV can also be used to charge the battery under level 3 fast charging capacity. This integrated battery charging technology can be realized by employing the winding inductances of the three-phase interior permanent magnet synchronous motor (IPMSM) used for propulsion as line inductors while charging the EV's battery pack. The difference in the d- and q-axis inductances in the IPMSM offers unbalanced Thevenin impedances as viewed from stator terminals. This causes the voltages across the stator windings to become unbalanced when balanced three-phase currents synchronized with the grid utility voltages are forced into the three armature phases during charging. This paper first presents a case study employing a conventional laboratory IPMSM to illustrate the unbalanced phase winding impedance during an “emulated integrated charging” operation. Thereafter, the authors derive motivation to design and analyze an IPMSM with dampers in the rotor for propulsion and mitigation of the saliency effect, that is, the effect of unequal armature phase impedance at standstill during integrated charging. A novel design approach is presented and employed to design an IPMSM with dampers. Performance of the designed IPMSM with dampers is compared to that of the conventional IPMSM under both integrated charging and traction conditions. The proposed design is also validated experimentally using a laboratory IPMSM with dampers.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.205
Threshold uncertainty score0.497

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.004
GPT teacher head0.188
Teacher spread0.184 · 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 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

Citations24
Published2018
Admission routes1
Has abstractyes

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