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Record W2223017408 · doi:10.4271/2011-01-1230

Real Time Virtual Temperature Sensor for Transmission Clutches

2011· article· en· W2223017408 on OpenAlex
Gang Chen, Kevin Baldwin, Edward Czarnecki

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

VenueSAE International Journal of Engines · 2011
Typearticle
Languageen
FieldEngineering
TopicElectric and Hybrid Vehicle Technologies
Canadian institutionsChrysler (Canada)
Fundersnot available
KeywordsClutchTransmission (telecommunications)Automatic transmissionAutomotive engineeringMaterials scienceComputer scienceEngineeringTelecommunications

Abstract

fetched live from OpenAlex

<div class="section abstract"><div class="htmlview paragraph">Many experiments have demonstrated that clutch overheating is a major cause of clutch deterioration. Clutch friction material deterioration not only leads to clutch failure, but also causes poor shift quality. Unfortunately, it is not practical to monitor each individual clutch temperature in a production vehicle due to high costs or technical challenges. This paper introduces a proposal for a virtual clutch temperature sensor to monitor the real time clutch temperature changes in Chrysler transmissions with PWM solenoid based control systems. Both vehicle and laboratory dynamometer (dyno) tests demonstrate that the model results match very closely with the thermocouple temperature measurements under many different driving conditions. The real time virtual temperature sensor provides a tool for clutch surface overheat protection and for design improvement and enhancement to shift quality.</div></div>

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score0.340

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 head0.011
GPT teacher head0.220
Teacher spread0.209 · 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