Experimental assessment of a linear actuator driven by magnetorheological clutches for automotive active suspensions
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Bibliographic record
Abstract
The main functions of automotive suspensions are to improve passenger comfort as well as vehicle dynamic performance. Simultaneously satisfying these functions is not possible because they require opposing suspension adjustments. This fundamental design trade-off can be solved with an active suspension system providing real-time modifications of the suspension behavior and vehicle attitude corrections. However, current active suspension actuator technologies have yet to reach a wide-spread commercial adoption due to excessive costs and performance limitations. This paper presents a design study assessing the potential of magnetorheological clutch actuators for automotive active suspension applications. An experimentally validated dynamic model is used to derive meaningful design requirements. An actuator design is proposed and built using a motor to feed counter-rotating MR clutches to provide upward and downward forces. Experimental characterization shows that all intended design requirements are met, and that the actuator can output a peak force of ±5300 N, a peak linear speed of ±1.9 m/s and a blocked-output force bandwidth of 92 Hz. When compared to other relevant technologies, the MR approach simultaneously shows both better force density and speeds (bandwidth) while adding minimal costs and weight. Results from this experimental assessment suggest that MR slippage actuation is promising for automotive active suspensions.
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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 it