A Fully Soft-Switched Resonant Based DC-DC Converter using Adder Architecture for Fast EV Battery Charging Applications
Bibliographic record
Abstract
Persistent efforts are being made to enable electrification of the transport industry for a cleaner environment. Though there has been substantial increase in the number of electric vehicles (EVs); lack of adequate and quick charging points are proving to be major stumbling blocks to the wide spread adoption of same. This paper presents a potential DC-DC converter architecture intended for fast battery charging applications. The converter is capable of generating wide output voltage (150V-920V) while maintaining soft-switching transitions for all the switches in the mentioned voltage range. It is conceived on the principle of adder architecture in which multiple power conversion modules are connected in a series-parallel combination for processing high power (55-175 kW). Detailed modelling and analysis of the converter is presented to select system components. A scaled down experimental prototype (voltage range of 36V-218V and power range of 0.32kW – 1.2kW) showing 97% peak efficiency is built to demonstrate proof of concept.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".