Alternative Approach to Analysis and Design of Series Resonant Converter at Steady State
Bibliographic record
Abstract
In this paper, new steady-state analysis is proposed for a series resonant converter (SRC) that provides closed-form expressions for converter waveforms. Using the proposed analysis, explicit equations are obtained to design the converter components. It is shown that an SRC can be modeled through a nonlinear differential equation with discontinuous inputs. A Laplace-based theorem (LBT) is provided to obtain the steady-state analytic solution of the resonant converter differential equations. Using the LBT, a flowchart is proposed to analyze the converter where the nonlinearity of differential equation is removed by defining intermediate variables. The variable duty ratio SRC is analyzed using the proposed flowchart. Accurate, closed-form, and explicit equations for converter waveforms, voltage gain, current phase lag, zero voltage switching, and discontinuous conduction mode boundaries are derived. The proposed analysis is compared with conventional methods and its accuracy is validated through simulations and experimental results. Moreover, using the proposed method, a novel procedure is provided for the optimal design of the converter and is compared with conventional design approaches.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.005 | 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".