An Exact Time Domain Analysis of DCM Boost Mode LLC Resonant Converter for PV applications
Bibliographic record
Abstract
The search for a cost feasible, optimal design of LLC converter for wide input voltage range conditions is inhibited by errors in steady state values of peak gain, tank current, tank voltage, active power etc., due to various approximations in the analysis. This leads to erroneous selection of circuit parameters. The present work provides an exact, approximation free time domain mathematical model of LLC converter operating in transformer secondary current discontinuous mode (DCM) below resonance in boost mode. The proposed approach defines voltage gain as a function of relative switching frequency ω and td, which represents the rectifier diode to switch conduction ratio for DCM operation. Existing works have defined voltage gain as an explicit function of quality factor (Q) and ω. The current approach leads to accurate derivation of converter voltage gain, tank RMS current, tank capacitor voltage, zero voltage switching (ZVS) angle etc. Analytical expressions are validated with simulation studies using PSIM for various inductor ratio values. A final design is verified on an experimental prototype of 320W output LLC converter designed for an input range of 20-40V for solar PV applications.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".