Accurate Real-Time Simulation of CLLLC Converters on FPGA: A Study of Sampling Resolution and Beating Effect
Bibliographic record
Abstract
The CLLLC resonant converter, used for high-efficiency applications such as battery chargers, presents major challenges for real-time simulation, notably by its use at high frequencies and by the involvement of natural switching. Furthermore, the resonant nature and high-frequency AC transformer waveforms characterizing such converters make the simulation highly sensitive to sampling errors introduced by the discrete nature of the simulation. This work proposes an approach based on a reconfigurable switched matrix solver associated with explicit switch handling and implemented on a low-cost FPGA target to meet these requirements. The hardware architecture achieves a computational step size as low as 25 ns, even on an affordable FPGA platform. The algorithms, validated by comparison with SIMBA software, guarantee accuracy with relative errors of less than 2%. These results demonstrate the feasibility of using low-cost FPGAs for demanding applications, offering an effective solution for real-time simulation and control of high-frequency resonant converters. The model’s limitations are also explored, and avenues for improvement are proposed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".