High-Bandwidth Differential Voltage Probe for Accurate Switching Characterization of WBG Devices
Bibliographic record
Abstract
For a more secure, anti-interference characterization of high-speed wide-bandgap (WBG) power devices, there is a growing need for galvanically isolated measurement methods with higher bandwidth and wider dynamic range. Among these techniques, the differential sensing method has gained attention due to its simplicity, cost-effectiveness, wide dynamic range, and floating measurement capability. Nevertheless, the limited bandwidth of the differential method remains a significant obstacle for characterizing ultrafast switching transients of WBG devices. This article highlights the significant bandwidth limitations encountered in the front-end highvoltage attenuation of the differential method, i.e. the parasitic effects of capacitive networks and the overlooked high-frequency transmission line effects. To address these limitations, the concept of transmission line voltage divider (TL-VD) is introduced, enabling the extension of the operating frequency range of the front-end high-voltage attenuation into the GHz level. To achieve this, four underlying matching principles regarding resistance, capacitance, inductance, and wave impedance are established, which are further simplified to three decoupled, mutually independent, and easily implementable matching objectives of resistance, wave impedance, and transmission line length. These contributions collectively result in the successful development of a ±2.0-kV differential voltage sensing system (DVSS) with an ultrahigh measurement bandwidth of 1.3 GHz and a common-mode rejection ratio (CMRR) of 48 dB at 100 MHz. Experimental comparisons with state-of-the-art commercial galvanically isolated products in both the frequency and time domains confirm the superior performance of the developed TL-VD-based DVSS.
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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 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".