High Frequency Bidirectional Isolated Matrix Converter for AC-Motor Drives with Model Predictive Control
Bibliographic record
Abstract
This paper aims to develop the inverter mode of high frequency isolated matrix converter (HFI-MC) for on-board integrated motor drive and battery charger in electric vehicle. Unlike grid side, motor drive requires that HFI-MC could control flexibly amplitude and angle of AC voltage, especially at zero or low speed, it need to output extremely low voltage and high current, which is difficult for many existing methods. In this digest, a novel approach will be proposed for HFI-MC. MC works at AC current source inverter mode, which control the angle of current vector, and the selection of current vector is completed by model predictive control. Full bridge control the amplitude of current vector by duty cycle and phase shift. The explicit analytical relationships between amplitude of current vector and duty cycle as well as phase shift are given. Finally, the effectiveness and feasibility of the proposed approach is verified.
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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) | 0.000 | 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) | 0.000 | 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".