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Record W2947446192 · doi:10.1109/access.2019.2919113

Numerical and Experimental Investigations of Noise and Vibration Characteristics for a Dual-Motor Hybrid Electric Vehicle

2019· article· en· W2947446192 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Access · 2019
Typearticle
Languageen
FieldEngineering
TopicMechanical Engineering and Vibrations Research
Canadian institutionsUniversity of Waterloo
FundersFundamental Research Funds for the Central UniversitiesNational Natural Science Foundation of China
KeywordsVibrationNoise (video)Electric vehiclePlanetElectric motorComputer scienceNon-circular gearNoise, vibration, and harshnessAcousticsAutomotive engineeringEngineeringSpiral bevel gearPhysicsMechanical engineering

Abstract

fetched live from OpenAlex

This paper investigates the abnormal noise and vibration of a hybrid electric vehicle during the electric-only driving mode. The sources of the noise and vibration are first identified through the frequency analysis, and then several measures are implemented to reduce the noise and vibration level. The experimental results have identified the gear meshing in the compound planetary gear set is the main source of the noise and vibration. The theoretical analysis demonstrates that gear pairs of the short planet-small sun gear and short planet-long planet in the compound planetary gear set contribute to the main noise and vibration of the hybrid system in the electric-only driving mode. This research also shows that the gear-meshing noise level in the compound planetary gear set can be decreased significantly by matching the engagement parameters, such as meshing stiffness, tooth error, and pitch error. The observation results in this paper are able to provide a practical reference for improving the ride comfort of hybrid electric vehicles in the future study.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.587
Threshold uncertainty score0.294

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 head0.019
GPT teacher head0.280
Teacher spread0.261 · 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