Fault diagnosis for fuel cell systems: A data-driven approach using high-precise voltage sensors

Zhongliang Li 1 Rachid Outbib 1 Stefan Giurgea 2 Daniel Hissel 2 Alain Giraud Pascal Couderc
1 LIS - Laboratoire d'Informatique et Systèmes
2 FEMTO-ST - Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174)
Document type :
Journal articles
Complete list of metadatas
https://hal-amu.archives-ouvertes.fr/hal-02004101
Contributor : Zhongliang Li <>
Submitted on : Friday, February 1, 2019 - 3:31:37 PM
Last modification on : Thursday, February 7, 2019 - 5:13:48 PM

Identifiers

  • HAL Id : hal-02004101, version 1

Collections

UNIV-AMU | CNRS | UNIV-BM | UNIV-FCOMTE | UNIV-BM-THESE | FEMTO-ST | LIS-LAB | UNIV-TLN | TDS-MACS

Citation

Zhongliang Li, Rachid Outbib, Stefan Giurgea, Daniel Hissel, Alain Giraud, et al.. Fault diagnosis for fuel cell systems: A data-driven approach using high-precise voltage sensors. Renewable Energy, Elsevier, 2018. ⟨hal-02004101⟩

Export

BibTeX TEI DC DCterms EndNote

Share

Metrics

Record views

62

Contact

Informations

CCSD