Control Strategies for Wide Output Voltage Range LLC Resonant DC–DC Converters in Battery Chargers
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Bibliographic record
Abstract
In this paper, a control strategy is presented for a high-performance capacitively loaded loop (LLC) multiresonant dc-dc converter in a two-stage smart charger for neighborhood electric vehicle (NEV) applications. It addresses several aspects and limitations of LLC resonant dc-dc converters in battery charging applications, such as very wide output voltage range while keeping the efficiency maximized, implementation of the current mode control at the secondary side, and optimization of burst mode operation for current regulation at very low output voltage. The proposed control scheme minimizes both low- and high-frequency current ripples on the battery while maintaining stability of the dc-dc converter, thus maximizing battery life without penalizing the volume of the charger. Experimental results are presented for a prototype unit converting 390 V from the input dc link to an output voltage range of 3-72 V dc at 650 W. The prototype achieves a peak efficiency value of 96%.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it