Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 6

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Analysis on Static Current Sharing of N-Paralleled Silicon Carbide MOSFETs

He, Yang, Wang, Xun, Zhang, Junming, Shao, Shuai, Li, Han, Luo, Cheng·2021·2021 IEEE Energy Conversion Congress and Exposition (ECCE)

Abstract

The influences of on-resistances and parasitic elements on the static current sharing of N-paralleled discrete silicon carbide (SiC) MOSFETs are analyzed in this paper. First of all, the limitation of self-balancing effect of MOSFETs caused by the positive temperature dependent on-resistance is quantitatively analyzed. From a statistical analysis, the current sharing distribution according to the spread of on-resistances is presented, which helps to screen the proper devices based on the current sharing requirement. Furthermore, a general circuit model is proposed to analyze the effect of inevitable circuit parasitic elements on current sharing with a given current slew rate. With the recursive circuit model, current imbalance contributed by parasitic resistances and inductances can be separately calculated, which can be used to guide the hardware design to improve current sharing in a real converter. The theoretical analysis is verified by experimental results.

Overview

Integrity signals

Registry

Crossref · 10.1109/ecce47101.2021.9595666

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

Research works printed but not linked: 8

  1. 10.1109/TPEL.2020.2978718 · DOI
  2. 10.1109/TIE.2017.2716868 · DOI
  3. 10.1109/TPEL.2019.2954716 · DOI · Paper page
  4. 10.1109/TPEL.2020.3009008 · DOI
  5. 10.23919/ICPE2019-ECCEAsia42246.2019.8797172 · DOI
  6. 10.1109/TPEL.2015.2408054 · DOI · Paper page
  7. 10.1109/ECCE44975.2020.9236326 · DOI · Paper page
  8. 10.1109/MIE.2012.2193291 · DOI

Cited by

See all 6

Metadata

Authors
He, Y., Wang, X., Zhang, J., Shao, S., Li, H., & Luo, C.
Venue
2021 IEEE Energy Conversion Congress and Exposition (ECCE)
Publisher
IEEE
Published
2021-10-10
Pages
5590-5596
Cited by
6
References
1
Funders
Eaton Corporation

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.