Design and testing of a hybrid electromagnetic damping device for automotive applications
Bibliographic record
Abstract
This study proposes a new design concept for combining a viscous fluid damper (VFD) with an eddy current damper (ECD). Three main concepts were thoroughly discussed: the magnetic system, the conductive material, and the housing. In particular, the excitation circuit and magnetic field were applied from the exterior of the main chamber of the VFD to minimize the intrusive risks introduced into the damper when trying to connect an internal magnetic system to an external power source. Experimental investigations on a test rig developed for this purpose were carried out in this work. The design aimed to generate eddy currents in an oscillating cylinder made of copper placed around an existing real-world car damper and secured to its moving rod. When exposed to an electromagnetic field, the newly designed system rapidly generated an extra level of damping in addition to the initial damping effect provided by the viscous mechanism. The obtained results showed that applying an electric current of only 1A increased the amplitude of the drag force by 12 % for an electrode with a thickness of 1.5 mm. A magnetic saturation phenomenon resisted any extra increase in the current. Making the metal conductor thicker is expected to increase the volume of the conductor in which the currents are flowing and, consequently, increase the damping effect.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".