Experimental Assessment of a Controlled Slippage Magnetorheological Automotive Active Suspension for Ride Comfort
Bibliographic record
Abstract
Active suspensions can alter the dynamic behavior of a vehicle in real time to respond optimally to any given operating scenario. Today’s active suspension technologies such as hydraulics, rotary electromagnetics, and linear electromagnetics do offer performance gains but these gains are outweighed by important disadvantages including high power consumption, low quality of force, and high costs and weights. Controlled slippage magnetorheological (MR) actuators are an emerging alternative actuation technology that is light, compact, power dense, and produces a high-quality force, making it ideal for active suspension applications. This article conducts an in-depth experimental assessment of the potential of MR actuators to increase vehicle ride comfort quality when used as active suspensions. Four high power MR actuators are installed on a BMW 330Ci and tests are performed on a closed road. Results show that with an impedance controller, comfort is increased by 67% at 65 km/h and by 61% at 80 km/h. These results compare favorably with the best-in-class electromagnetic active suspension technologies reported to date and suggest that MR actuators are promising for automotive active suspensions.
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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 | 0.000 | 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) | 0.002 | 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 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".