Vibration noise suppression approach based on random switching frequency control for permanent magnet motor
Bibliographic record
Abstract
The vibration noise of the distributed drive autonomous ground vehicle (AGV) is mainly produced by the inverter-fed brushless DC permanent magnet in-wheel motor (PMIWM). It is necessary to reduce the vibration noise level of the PMIWM driven by pulse width modulation (PWM). A suppression approach of electromagnetic vibration noise for the PMIWM is investigated. First, the air gap magnetic field of the inverter-fed PMIWM was analyzed. The electric current harmonics and the unbalanced magnetic force (UMF) were investigated. The natural frequency and noise of the PMIWM were presented. Then, a flux-weaken approach was employed to maintain the robustness of the PMIWM when a sudden drop of DC bus voltage. The random switching frequency (RSF) PWM control method based on a two-state Markov chain is proposed to decrease the amplitude of the harmonics caused by the switching frequency and the multiple switching frequencies. The experimental results show that the RSFPWM can not only effectively reduce the vibration noise and the inverter losses, but also improve the robustness of the PMIWM control system under unpredictable uncertainties.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".