Power Electronics Control of an Energy Regenerative Mechatronic Damper
Bibliographic record
Abstract
This paper presents the development of a power electronics controller for a proof-of-concept energy regenerative damper in vehicular applications. The damper consists of an efficient motion conversion mechanism to convert translational base vibration into reciprocating rotary motion, a brushless three-phase permanent-magnet rotary machine, and a three-phase power converter. A power electronics boost controller is developed to capture the generated electrical power and store it into a battery that allows overcoming kinematic nonlinearities in the motion conversion stage. To this end, a sliding-mode controller that can enforce a resistive behavior across the terminals of the rotary machine by regulating the converter's input current in real time is presented. Through the proposed approach, the mechanical damping coefficient of the system can be controlled, on demand, with an energy regenerative function. The performance of the developed system is evaluated under sinusoidal excitation inputs and transient conditions when operating with a damping coefficient of 650 $\hbox{N}\cdot\hbox{s/m} $ synthesized through power electronics and control. Experimental results that evaluate the performance of the proposed energy regenerative damper are presented.
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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 | 0.001 | 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".