Electromechanical Clutch Actuator: Design, Analysis and Experiments
Bibliographic record
Abstract
With the aim of producing innovative clutch actuation mechanisms for automotive transmissions, we are investigating a design based on power screws. The design strives to improve clutch actuation technology and minimize energy consumption by maintaining clutch lock-up independent of an external energy source. The system consists of a lead screw shaft-and-nut assembly, a clutch apply-plate, a set of wet clutch disks and a brushless DC motor. The clutch actuation assembly is separated from the clutch-pack via thrust bearings, which allows the use of a motor, while reducing the inertial load imposed by the conventional clutch-pack. A prototype of the design was fabricated and installed on a testbed, to mimic the installation of the actuator to replace the hydraulic components. A standard 12-disk clutch-pack of an automatic transmission was used within the apparatus. The formulation of the mathematical model of the entire testbed is described in this paper. The clutch-pack stiffness is modeled as a hardening spring, to account for its elastostatic behavior. The simulated response of the model was compared to its experimental counterpart, which allowed for a rough estimate of the model parameters. Compressive force testing of the apparatus using a load cell is included.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".