Control of an Electromechanical Clutch Actuator Using a Dual Sliding Mode Controller: Theory and Experimental Investigations
Bibliographic record
Abstract
The powertrain performance and comfort of a vehicle are largely dependent on the clutch control strategy for its Automated Manual Transmission (AMT). In most industrial cases, clutch control is managed by clutch pressure control, irrespective of clutch actuation technology. However, clutch pressure control represents a challenge with regard to clutch nonlinearities and time-varying parameters (especially with electromechanical technology). In this paper, the electrohydraulic AMT of a three-wheeled motorcycle is considered. In the context of replacing its electrohydraulic clutch actuator (EHA) by a new electromechanical clutch actuator (EMA) for fuel savings, a dual sliding mode controller (DSMC) is proposed in order to control clutch pressure with the EMA. The clutch and its EMA are modeled through an analytical model including two nonlinear components. The EMA was prototyped and subsequently enclosed in an environmental chamber. Experimental investigations revealed both predicted nonlinearities in the system and allowed identifying several numeric models of the system's dynamics. In keeping with these experimental investigations, the DSMC architecture and algorithm was developed, in which the robustness of the DSMC was proven through a Lyapunov analysis and the original use of the bang-bang component enabled to overcome static friction without introducing chattering. Finally, the test bench setup was used to experimentally highlight controller robustness and performance. Finally, the better control performance and accuracy of the EMA and its DSMC over the current integrated EHA and its associated PI controller were pointed out with respect to four critical clutch operational cases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".