Improved Model Predictive Control With Reduced DC-Link Capacitor RMS Current for Back-to-Back Converter-Fed PMSM Drives
Bibliographic record
Abstract
A low root mean square (RMS) current flowing through the intermediate dc-link capacitor is always desired in the back-to-back (BTB) voltage source converters (VSCs)-fed motor drive, such that the designed capacitor lifespan can be extended or a lower dc-link size could be the alternative with improved power density. The conventional modulator-based control involves the inherent carrier-based switching operation, and hence the dominant harmonics at carrier frequency multiplier and carrier sideband are introduced into the capacitor current. Therefore, the finite-control-set model predictive control (FCS-MPC) is proposed to optimize the capacitor RMS current. The switching pulse is generated directly without using the carrier, which can give a distinctive capacitor current spectrum and more possible current pulse cancelation between the BTB VSCs can be conveniently achieved through the cost function. Besides, the acceptable grid-current quality and the motor performance are maintained by using a tunable weighting factor. The simulated and experimental results highlight the effectiveness and benefits of the proposed method in terms of 20%–35% capacitor RMS current reduction compared to the synchronous carrier-based space vector pulsewidth modulation scheme and also significant improvements over the distributed predictive manner.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".