Contribution to state and sensor fault estimation applied to PEM fuel cell systems

被引:0
|
作者
Olteanu, Severus [1 ]
Aitouche, Abdel [2 ]
Belkoura, Lotfi [1 ]
机构
[1] Univ Lyon 1, CNRS, Ctr Res Informat Signal & Automat Lille, CRIStAL Lab,UMR 9189, F-69622 Villeurbanne, France
[2] CNR, Ctr Res Informat Signal & Automat Lille, Sch High Studies Engn HEI, UMR 9189, Lille, France
来源
2016 5TH INTERNATIONAL CONFERENCE ON SYSTEMS AND CONTROL (ICSC) | 2016年
关键词
OBSERVERS; DESIGN;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper aims firstly at contributing to the problematic of nonlinear Takagi-Sugeno (TS) approach for state and fault estimation with unmeasurable premise variables. The second objective is the application of this method on Fuel Cell Systems (FCSs). In order to achieve the estimated value of the fault, an observer based method is essential. The development and optimization of Fuel Cell parameter estimation in parallel with fault estimation is not treated in an exhaustive manner in literature. The estimation is based on a PI observer where the estimation error is bounded, having an additional corrective sliding terms. This eliminates the inconvenient generated by the Lipschitz constant.
引用
收藏
页码:217 / 224
页数:8
相关论文
共 50 条
  • [21] Optimization of PEM Fuel Cell systems with RSM
    Xuan, Dongji
    Li, Zhenzhe
    Cheng, Taihong
    Shen, Yunde
    POWER AND ENERGY ENGINEERING CONFERENCE 2010, 2010, : 341 - 344
  • [22] Systematic parameter estimation for PEM fuel cell models
    Carnes, B
    Djilali, N
    JOURNAL OF POWER SOURCES, 2005, 144 (01) : 83 - 93
  • [23] Data-driven fault diagnosis and robust control: Application to PEM fuel cell systems
    Ocampo-Martinez, Carlos
    Sanchez-Pena, Ricardo
    Bianchi, Fernando
    Ingimundarson, Ari
    INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2018, 28 (12) : 3713 - 3727
  • [24] Model based Fault detection and isolation of PEM Fuel Cell
    Yang, Quan
    Aitouche, Abdel
    Bouamama, Belkacem Ould
    2010 CONFERENCE ON CONTROL AND FAULT-TOLERANT SYSTEMS (SYSTOL'10), 2010, : 825 - 830
  • [25] Reservoir Computing optimisation for PEM fuel cell fault diagnostic
    Morando, S.
    Pera, M. C.
    Steiner, N. Yousfi
    Jemei, S.
    Hissel, D.
    Larger, L.
    2017 IEEE VEHICLE POWER AND PROPULSION CONFERENCE (VPPC), 2017,
  • [26] ARTIFICIAL NEURAL NETWORK MODEL APPLIED TO A PEM FUEL CELL
    Falcao, D. S.
    Pires, J. C. M.
    Pinho, C.
    Pinto, A. M. F. R.
    Martins, F. G.
    IJCCI 2009: PROCEEDINGS OF THE INTERNATIONAL JOINT CONFERENCE ON COMPUTATIONAL INTELLIGENCE, 2009, : 435 - +
  • [27] Implementation of sensor based on neural networks technique to predict the PEM fuel cell hydration state
    Arama, Fatima Zohra
    Mammar, Khaled
    Laribi, Slimane
    Necaibia, Ammaar
    Ghaitaoui, Touhami
    JOURNAL OF ENERGY STORAGE, 2020, 27
  • [28] A review: Exergy analysis of PEM and PEM fuel cell based CHP systems
    Ozgur, Tayfun
    Yakaryilmaz, Ali Cem
    INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2018, 43 (38) : 17993 - 18000
  • [29] Fault diagnosis of a PEM fuel cell system by SP model and on-line expert systems techniques
    Liu, W
    Wang, XCG
    IASTED: PROCEEDINGS OF THE IASTED INTERNATIONAL CONFERENCE ON MODELLING AND SIMULATION, 2003, : 188 - 191
  • [30] Control of PEM fuel cell distributed generation systems
    Wang, C.
    Nehrir, M. H.
    Gao, H.
    IEEE TRANSACTIONS ON ENERGY CONVERSION, 2006, 21 (02) : 586 - 595