Localization of Open-Circuit Faults in GaN-Based Three-Phase Dual Active Bridge Converters with Reduced Sensing Requirements
Bibliographic record
Abstract
The paper presents a cost-effective method for detecting and localizing single-switch open-circuit faults (OCFs) in three-phase dual active bridge converters using the αβ transformation. The proposed algorithm reduces the number of required current sensors and simplifies the detection and localization processes compared to state-of-the-art methods. The algorithm is verified using an experimental prototype operating at 400 V delivering 2 kW, using 650-V GaN devices switching at 300 kHz. Successful detection of all single-switch OCFs is demonstrated, with a worst-case detection time of 5 switching periods, verifying the effectiveness of the proposed algorithm. An auto-correction process to compensate for dc biases in the detected signals due to variations in system and component parameters is developed, which dynamically optimizes the detection time in different operating conditions. Fast OCF detection, as enabled by the proposed method, allows for the reconfiguration of the converter for post-fault operation.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".