A new approach for the diagnosis of different types of faults in DC-DC power converters based on inversion method

• Type: Article in International Scientific Journal
• Date: 2020

Authors

Silveira, AM (Author) Other; Rui Esteves Araújo (Author) FEUP

Journal

Title: Electric Power Systems Research

Vol. 180

ISSN: 0378-7796

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 1 Citation

Scopus - 8 Citations

Other information

Authenticus ID: P-00R-E9R

DOI: 10.1016/j.epsr.2019.106103

Abstract (EN): This paper presents theory, a new approach and validation results for fault detection and isolation (FDI) in DC-DC power converters, based on inversion method. The developed method consists on the inversion-based estimation of faults and change detection mechanisms adapted to the power converters context. With the inverse model of a switched linear system, we have designed a real-time FDI algorithm with an integrated fuzzy logic scheme which detects and isolates abrupt changes (faults) at unknown time instants. A smoothing strategy is used to attenuate the effect of unknown disturbances and noise that are present at the outputs of this inverse model. Once the fault event is detected, a dedicated fuzzy-logic-based scheme is proposed to isolate the four types of faults: switch, voltage and current sensor, and capacitor. The performance of the proposed method is verified experimentally to detect and isolate the mentioned faults in the DC-DC boost power converter.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 12