Energy Regenerative Suspension Using an Algebraic Screw Linkage Mechanism
Bibliographic record
Abstract
This paper presents the development of a novel energy-regenerative suspension mechanism. The system consists of a mass-spring unit coupled with an algebraic screw kinematic pair, a rotary permanent magnet synchronous generator (PMSG), and a three-phase boost charger connected to a battery. The algebraic screw converts the translational vibration into a reciprocating rotary motion which drives the PMSG through a planetary gearhead. A pulse-width-modulated three-phase boost converter is then used to convert the energy generated by the rotary machine into battery charge. To this end, a control and switching algorithm is utilized that makes the battery appear as a pseudo-resistor across the terminals of the rotary machine. Introducing this pseudo-resistive characteristic across the machine produces the same effect as mechanical damping with an energy regenerative function. The design and analysis of the regenerative suspension mechanism are presented by considering the dynamics of the electromechanical device, parameters of the suspension system, and the base excitation input profile. Experimental results are presented that evaluate performance of the proposed regenerative damper on a small-scale suspension system, which demonstrate the feasibility of building energy-regenerative dampers.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".