Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 257

The DOI matches its Crossref record; 51 of the 51 references it cites were found in a registry or an index.

Model-Based Fault Detection and Identification for Switching Power Converters

Poon, Jason, Jain, Palak, Konstantakopoulos, Ioannis C., Spanos, Costas, Panda, Sanjib Kumar, Sanders, Seth R.·2017·IEEE Transactions on Power Electronics

Abstract

We present the analysis, design, and experimental validation of a model-based fault detection and identification (FDI) method for switching power converters using a model-based state estimator approach. The proposed FDI approach is general in that it can be used to detect and identify arbitrary faults in components and sensors in a broad class of switching power converters. The FDI approach is experimentally demonstrated on a nanogrid prototype with a 380-V dc distribution bus. The nanogrid consists of four different switching power converters, including a buck converter, an interleaved boost converter, a single-phase rectifier, and a three-phase inverter. We construct a library of fault signatures for possible component and sensor faults in all four converters. The FDI algorithm successfully achieves fault detection in under 400 $\mu$s and fault identification in under 10 ms for faults in each converter. The proposed FDI approach enables a flexible and scalable solution for improving fault tolerance and awareness in power electronics systems.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1109/tpel.2016.2541342

Cites

51 of 51 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 51 references

Cited by

See all 257

Metadata

Authors
Poon, J., Jain, P., Konstantakopoulos, I. C., Spanos, C., Panda, S. K., & Sanders, S. R.
Venue
IEEE Transactions on Power Electronics
Published
2017-02
Volume
32
Issue
2
Pages
1419-1430
ISSN
  • 0885-8993 (ISSN-L)
  • 1941-0107
OpenAlex
W2318970278
Cited by
257
References
51
FWCI
18.80
Type
journal article
Language
en
Open access
closed

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

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Model-Based Fault Detection and Identification for Switching Power Converters. https://app.cochat.ai/papers/10.1109/tpel.2016.2541342
The paper
Poon, J., Jain, P., Konstantakopoulos, I. C., Spanos, C., Panda, S. K., & Sanders, S. R. (2017). Model-Based Fault Detection and Identification for Switching Power Converters. IEEE Transactions on Power Electronics. https://doi.org/10.1109/tpel.2016.2541342

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.