An Improved Adaptive Sinusoidal Single Phase Shift Modulation for Bidirectional Single-Stage Onboard EV Chargers
Bibliographic record
Abstract
Single-stage onboard chargers (SSOBCs) integrate traditional two-stage structures of front-end power factor correction (PFC) AC/DC converter and back-end DC/DC converter, which increases compactness and reliability. However, PFC function and DC voltage regulation need to be achieved simultaneously within only a single converter. Hence, it is challenging for SSOBCs to obtain high efficiency with a unity power factor (PF) under a wide operating range. To address the above issue, this paper presents an adaptive sinusoidal single phase shift (ASSPS) modulation strategy that introduces a sinusoidal single phase shift for maintaining a high PF. Firstly, the proposed adaptive technique solves the high current issue at the zero-crossing point of grid voltage based on different operating modes, significantly decreasing conduction loss and increasing efficiency. Moreover, the full-range zero-voltage switching (ZVS) technique on the secondary bridge can be achieved under universal specification from 300 V to 800 V battery voltage, which reduces the switching loss. The proposed ASSPS modulation has only one variable, which is easy to implement for hardware design. Finally, a generalized design guideline of the 6 kW SiC-based bidirectional SSOBC is proposed, and the prototype is built. The experimental results validate the operating principle and ZVS achievement of the proposed ASSPS modulation. Compared with the traditional modulation methods, the proposed ASSPS modulation increases the peak efficiency by 1.1%.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".