Parallel Inverters using a DC Common Mode PWM Filter with an AC Differential Mode PWM Filter
Bibliographic record
Abstract
An inductor filter arrangement is assessed that filters the high-frequency PWM common mode, CM, and differential mode, DM, PWM voltages experience between two 180° interleaved 2-level voltage source converters (VSCs) connected to the same dc-link voltage. A 3-limb coupled inductor, CI, connecting the two inverters presents a large inductance for filtering DM PWM voltages between the two inverters, and a CM dc choke that presents a high inductance for the CM PWM voltage between the two inverters is used as a CM PWM filter. However, the dc-choke has a low inductance for current drawn by the inverters to supply the load. Likewise, the 3-limb CI has a low inductance to the flow of fundamental currents to the load. The size and weight of the filter arrangement are compared with separate CIs used in each phase, which can cope with both CM and DM PWM voltages without saturating and are shown to be 20% smaller in comparison. A PWM scheme is demonstrated to produce high-quality 3-level phase and 5-level PWM line voltages. The system described is suitable for medium voltage high power drives and high-speed machines with application in aerospace, electric vehicles, and utility connected rectifiers. The performance of the system is demonstrated with PLECS simulation and experimental results of an 8 kW (300V, 208 V/22A) laboratory prototype operating with a fundamental voltage of 60 Hz and 1.1 kHz.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".