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Record W2774221689 · doi:10.1109/iecon.2017.8216314

Comparative performance analysis of 3-phase IPMSM rotor configurations with dampers for integrated charging application in EVs

2017· article· en· W2774221689 on OpenAlexaff
Shruthi Mukundan, Himavarsha Dhulipati, K. Lakshmi Varaha Iyer, Chunyan Lai, Kaushik Mukherjee, Narayan C. Kar

Bibliographic record

VenueIECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society · 2017
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsRotor (electric)TorqueAutomotive engineeringMagnetDrivetrainDamperVoltageEngineeringComputer scienceElectrical engineeringPhysicsControl engineering

Abstract

fetched live from OpenAlex

Integrated charging (IC) technology in electric vehicles (EVs) employing conventional power electronics and motor drivetrain components facilitates level 3 fast charging capabilities with reduction in overall weight and cost of the vehicle. However, when the winding inductances of 3-phase interior permanent magnet synchronous machines (IPMSMs) are realized as line inductors for battery charging, due to machine saliency, the magnetic fields produced by the sinusoidal AC supply results in 1) asymmetrical voltages in the air-gap as a function of rotor position and 2) relatively high magnitudes of oscillating torques causing harmful noise and vibrations. This can lead to significant AC losses with risk of permanent magnet demagnetization in the machine. Since the same motor is employed for traction application as well, it is of significance to optimally design the machine for IC operation. Thus, this paper exclusively investigates three IPMSM rotor configurations to be employed for IC operation in EV. This paper firstly presents a conventional dq-axis circuit model based damper design approach implemented for mitigating the saliency effect during IC. Then, a comparative performance analysis of the rotor configurations with damper bars during IC operation on machine saliency; asymmetrical voltage waveforms; oscillating electromagnetic torque; permanent magnet operating point and magnet losses is performed using finite-element analysis (FEA). Results obtained are analyzed and discussed.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.648
Threshold uncertainty score0.724

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.056
GPT teacher head0.298
Teacher spread0.242 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

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Same venueIECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics SocietySame topicElectric Motor Design and AnalysisFrench-language works237,207