An Interleaved Bridgeless Single-Stage AC/DC Converter With Stacked Switches Configurations and Soft-Switching Operation for High-Voltage EV Battery Systems
Bibliographic record
Abstract
A novel single-stage ac/dc isolated onboard charger with modular stacked switches structure utilizing interleaved control is proposed in this article for high-voltage (HV) battery systems in electric vehicles (EVs). In the proposed converter, modular interleaved bridgeless ac/dc boost converters are integrated with modularCLLresonant circuits through sharing the two legs of stacked switches. With this configuration, the voltage stress across each switch is reduced to half of the dc-link voltage, which makes the circuit applicable for HV battery system (such as 800 V) in EVs. In the proposed design, the integrated interleaved boost circuit modules allow low input current ripple to be achieved. Two step-up resonant circuit modules are then connected to the two interleaved legs with their outputs connected in series at the input of a current-fed high-frequency rectifier. Soft-switching commutation is achieved for all switches and diodes in the proposed converter. The descriptions of the proposed converter and its operating principles will be discussed in this article. A silicon-carbide-based hardware prototype with a rated power of 2.4 kW, 90–135 Vac/800 Vdc system has been tested in the laboratory. Results confirmed that a power factor of 0.97 and a peak efficiency of 97.9% were achieved.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".