Comparison of methods for compensation capacitor calculation in a three-phase wireless power transfer system
Bibliographic record
Abstract
This paper proposes a new approach to calculate the compensation capacitors values for high power three-phase wireless power transfer systems, suitable for deployment in wireless EV chargers. The proposed approach increases the power factor of transmitter phases, and thus reduces the DC bus voltage requirement significantly for systems with non-decoupled transmitter coils. The proposed approach derives the compensation capacitor values as a function of rated transmitter currents. The paper applies the transmitter currents from perfect alignment and extreme misalignment into the proposed approach to derive two sets of compensation capacitors. One set of capacitors provides unity power factors for each phase at perfect alignment while the other set of capacitors provides unity power factor for the phase delivering highest power for all misalignments. Simulation verification is performed at 3.3 kW output power and 300 V battery voltage showing that the proposed method can reduce the DC bus voltage requirement to below 800 V for all misalignments. Experimental results are obtained at 1000 W output power and 150 V battery voltage verifying the proposed approach.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".