Bibliographic record
Abstract
High-power multimodular matrix converters (MMMCs) comprising multiple threephase to single-phase matrix converter modules have emerged as a viable topology candidate for medium-voltage adjustable speed drives. As a combination of direct power conversion and cascaded multilevel structure, the MMMCs inherit features such as elimination of dc capacitors, four quadrant operation capability, employment of lowvoltage devices only, and superior output waveform quality under a limited device switching frequency. Due to their particular topological structure, modulation scheme design for the MMMCs is not straightforward and complicated. The presented work is mainly focused on development of suitable modulation schemes for the MMMCs. Several viable schemes as well as their corresponding switching patterns are proposed and verified by both simulation and experimental results. In order for the MMMCs to produce sinusoidal waveforms at both input and output ac terminals, a direct transfer matrix based modulation scheme is presented. It is revealed that a suitable modulation strategy for the MMMCs should aim at fabricating the total input current on the primary side of the isolation transformer. For topologies with more than two modules in cascade on each output phase, switching period displacement is necessary among modules to generate multilevel output waveforms. An indirect space vector based modulation scheme for the MMMCs is developed. With a few presumptions satisfied and viewed from a certain perspective, the MMMCs can still be modeled indirectly and be divided into fictitious rectifier and inverter stages. Therefore, space vector modulation methods can be independently applied to both stages for duty ratio calculation, before the results are converted and combined for determining per-phase output pulses. A new output switching pattern providing improved harmonic performance is also proposed. A novel modulation scheme based on diode rectifier emulation and phase-shifted sinusoidal pulse-width modulation is proposed. The method sacrifices input power factor adjustment, but enables the use of an indirect module construction leading to significantly reduced device count and complexity. Strategy for reducing additional switchings caused by input voltage ripples is also implemented and explained. In addition to simulation verifications, all the proposed schemes are further tested experimentally on a low-voltage prototype built in the lab. Details about the prototype implementation are introduced.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".