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Record W3186111164 · doi:10.1139/tcsme-2021-0004

A mathematical model and a method to measure the instantaneous power output of vehicular driving wheels

2021· article· en· W3186111164 on OpenAlexvenueno aff
Wei Zhao, Zhizhong Li, Haitao Zhang

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Fluid Dynamics Research
Canadian institutionsnot available
FundersChina Postdoctoral Science Foundation
KeywordsDynamometerPower (physics)Automotive engineeringTorqueMeasure (data warehouse)Control theory (sociology)Rolling resistanceSimulationEngineeringComputer scienceMechanical engineeringControl (management)

Abstract

fetched live from OpenAlex

The internal resistance of a dynamometer is regarded as a constant force when using traditional test methods, which means that the measurement values for the instantaneous power output of the vehicle driving wheel are underestimated. In this study, we aimed to resolve this issue. Thus, we constructed a system for measuring drum movement and propose a method for measuring the instantaneous power output of a vehicle’s driving wheel. Further, we created a mathematical model of the instantaneous power output from a vehicle’s driving wheel. Comparing the results from our model with our experimental results, we found that the actual power output of the driving wheel was reflected more accurately by our proposed method, and that the accuracy of the measurement results was not affected by the vehicle’s speed. The output torque of the vehicle’s driving wheel calculated using our proposed model was closer to the running resistance of the vehicle. Thus, our model facilitates accurate no-dismounting, rapid measurement of the power output of a driving wheel, and accurate simulation of road running resistance using a dynamometer.

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: Methods · Consensus signal: none
Teacher disagreement score0.884
Threshold uncertainty score0.393

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 head0.013
GPT teacher head0.226
Teacher spread0.214 · 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
GenreMethods

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

Citations1
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicAerodynamics and Fluid Dynamics ResearchFrench-language works237,207