High-Efficiency Discontinuous Current-Mode Power Factor Correction-Based Plug-In Battery Charger for Local e-Transportation
Bibliographic record
Abstract
This article presents a high-efficiency dual sensor-based two-stage battery charger for low-voltage battery packs. The charger utilizes a discontinuous current-mode (DCM)-based front-end ac-dc interleaved buck-boost converter for active power factor correction (PFC) and an unregulated LLC converter with synchronous rectification (SR) for achieving high efficiency. Only two sensors are utilized for implementing converter charge control, thus increasing converter reliability and robustness. A detailed loss analysis is done in order to estimate an optimal dc-link voltage for high performance along with small-signal modeling for closed-loop control. Experimental results from a proof-of-concept 1.0-kW hardware prototype are demonstrated in order to verify the converter feasibility. An input power factor of 0.99, an input current total harmonic distortion of 3.85%, and a high efficiency of 96.06% are achieved from the prototype.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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 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".