Nonlinear dynamic and electromagnetic interference coupled-field analysis in a semi-active suspension system with magneto-rheological damper
Bibliographic record
Abstract
A groundhook controlled semi-active suspension system equipped with magneto-rheological damper (MRD) is considered. Both the hysteresis of MRD and control discontinuity, the nonlinearity will greatly affect system stability of the vehicle. In this paper, the performance and nonlinear dynamic of semi-active suspension adopting modified groundhook is evaluated. The influence of frequency of harmonic excitation and parameter of modified groundhook controller on the nonlinear dynamics of the semi-active suspension system is investigated. More importantly, nonlinear dynamic analysis is carried out to study the semi-active suspension system, with the methods of bifurcation diagram, the Lyapunov exponent spectrum, time history, phase plane and power spectrum in detail for the first time. Furtherly, electromagnetic interference (EMI) problems induced by chaotic motion are analyzed and discussed according to EN 55022 for another first time. It is indicated that both of periodic, quasi-periodic and chaotic motions exist. The system undergoes a complex nonlinear dynamical evolution with the excitation change. The coupling influence between chaos and EMI problems cannot be ignored in the further design of the semi-active controller. This work laid a theoretical foundation for EMI reduction and nonlinear control of the intelligent MR semi-active suspension.
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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) | 0.001 | 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".