Design and Optimization of A High Power Density Low Voltage DC-DC Converter for Electric Vehicles
Bibliographic record
Abstract
This paper presents a high power density LLC converter for Electric Vehicles (EVs) on-board low voltage DC-DC converter. The design specification imposes critical challenges on size and efficiency due to extremely high load current rating and wide input/output voltage range. The proposed design enables high switching frequency by using wide-band-gap (WBG) devices to significantly reduce the size of magnetic components and meet the power density requirement. A two-transformer configuration with series connected primary windings and parallel connected secondary windings is used to reduce the heavy I2R loss on the output side. The structures of parallel resonant inductor and transformers are carefully designed to reduce the fringing loss and AC conduction loss. A single phase 1.3kW LLC prototype with water cooling was built and experiment results verified the design considerations. The prototype achieved 3kW/L of power density and 97% peak efficiency. Full input voltage range from 250V to 430V and output voltage from 9V to 16V operation was verified with 96.5% efficiency achieved at nominal input and full load.
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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 | 0.000 | 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 | 0.000 |
| 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".