Research Papers

Causal and Fault Trees Analysis of Proton Exchange Membrane Fuel Cell Degradation

[+] Author and Article Information
Kais Brik

Research Laboratory Materials,
Measurements and Applications,
University of Carthage,
Centre Urbain Nord,
BP No. 676,
Tunis 1080, Tunisia
e-mail: Kais.brik@yahoo.fr

Faouzi Ben Ammar

Research Laboratory Materials,
Measurements and Applications,
University of Carthage,
Centre Urbain Nord,
BP No. 676,
Tunis 1080, Tunisia
e-mail: Faouzi.benamar@yahoo.fr

Abdesslam Djerdir

University of Technology of Belfort-Montbéliard,
Belfort 90000, France
e-mail: abdesslem.djerdir@utbm.fr

Abdellatif Miraoui

University of Technology of Belfort-Montbéliard, Belfort 90000, France
e-mail: abdellatif.miraoui@utbm.fr

1Corresponding author.

Contributed by the Advanced Energy Systems Division of ASME for publication in the JOURNAL OF FUEL CELL SCIENCE AND TECHNOLOGY. Manuscript received October 2, 2014; final manuscript received August 30, 2015; published online October 6, 2015. Assoc. Editor: Rak-Hyun Song.

J. Fuel Cell Sci. Technol 12(5), 051002 (Oct 06, 2015) (8 pages) Paper No: FC-14-1119; doi: 10.1115/1.4031584 History: Received October 02, 2014; Revised August 30, 2015

This paper presents a reliability approach to analyze the degradation of proton exchange membrane fuel cell. This approach is based on the dependability analysis tools such as the causal and fault trees to establish an analysis of the internal state of the fuel cell energy conversion performance and evaluate its lifetime. The elaboration of causal tree offers powerful tools to a deductive analysis, which consists on seeking the various combinations of events leading to the fuel cell degradation. The parameters of fuel cell model are identified in order to found the degree of degradation. The experimental determination of the variation interval of the parameters is done according to each of degradation modes. A diagnostic method is proposed in order to identify the depth of each aging process of the fuel cell. The diagnosis is done by comparing the experimental output characteristic at beginning of life of the fuel cell with the used fuel cell to qualify and quantify the depth of degradation.

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Sirisukprasert, S. , and Saengsuwan, T. , 2008, “ The Modeling and Control of Fuel Cell Emulators,” ECTI-CO, 2008, pp. 985–988.
Blunier, B. , and Miraoui, A. , 2008, “ Modelling of Fuel Cells Using Multi-Domain VHDL-AMS Language,” J. Power Sources, 177(1), pp. 434–450. [CrossRef]
Tounthong, P. , Sadli, I. , Raël, S. , and Davat, B. , 2006, “ A Control Strategy of Fuel Cell/Battery Hybrid Power Source for Electric Vehicle Applications,” 37th IEEE Power Electronics Specialists Conference (PESC '09), Jeju, Korea, June 18–22.
Le Ny, M. , 2013, “ Current Distribution Identification in Fuel Cell Stacks From External Magnetic Field Measurements,” IEEE Trans. Magn., 49(5), pp. 1925–1929. [CrossRef]
Fouquet, N. , Doulet, C. , Nouillant, C. , Dauphin-Tanguy, G. , and Ould-Bouamama, B. , 2006, “ Model Based PEM Fuel Cell State-of-Health Monitoring Via AC Impedance Measurements,” J. Power Sources, 159(2), pp. 905–913. [CrossRef]
Nakajima, H. , Konomi, T. , Kitahara, T. , and Tachibana, H. , 2008, “ Electrochemical Impedance Parameters for the Diagnosis of a Polymer Electrolyte Fuel Cell Poisoned by Carbon Monoxide in Reformed Hydrogen Fuel,” ASME J. Fuel Cell Sci. Technol., 5(4), p. 041013. [CrossRef]
Majdara, A. , and Wakabayashi, T. , 2009, “ Component-Based Modeling of Systems for Automated Fault Tree Generation,” Reliab. Eng. Syst. Saf., 94(6), pp. 1076–1086. [CrossRef]
Rasool, K. , 1991, “ Event-Tree Analysis by Fuzzy Probability,” IEEE Trans. Reliab., 40(1), pp. 120–124. [CrossRef]
Brik, K. , and Ben Ammar, F. , 2013, “ Causal Tree Analysis of Depth Degradation of the Lead Acid Battery,” J. Power Sources, 228, pp. 39–46. [CrossRef]
Song, Y. , Han, S. B. , Park, S. I. , Jeong, H. G. , and Jung, B. M. , 2007, “ A Power Control Scheme to Improve the Performance of a Fuel Cell Hybrid Power,” IEEE Power Electronics Specialists Conference (PESC 2007), Orlando, FL, June 17–21, pp. 1261–1266.
Tirnovan, R. , Giurgea, S. , Miraoui, A. , and Cirrincione, M. , 2008, “ Surrogate Modelling of Compressor Characteristics for Fuel Cell Applications,” Appl. Energy, 85(5), pp. 394–403. [CrossRef]
Schmittinger, W. , and Vahidi, A. , 2008, “ A Review of the Main Parameters Influencing Long-Term Performance and Durability of PEM Fuel Cells,” J. Power Sources, 180(1), pp. 1–14. [CrossRef]
Taniguchia, A. , Akitaa, T. , Yasuda, K. , and Miyazaki, Y. , 2008, “ Analysis of Degradation in PEMFC Caused by Cell Reversal During Air Starvation,” Int. J. Hydrogen Energy, 33(9), pp. 2323–2329. [CrossRef]
Endoh, E. , Terazono, S. , Widjaja, H. , and Takimoto, Y. , 2004, “ Degradation Study of MEA for PEMFCs Under Low Humidity Conditions,” J. Electrochem. Solid State, 7(7), pp. 209–211. [CrossRef]
Jinfeng, W. , Xiao, Z. , Wanga, H. , Zhang, J. , Shena, J. , Wua, S. , and Merida, W. , 2008, “ A Review of PEM Fuel Cell Durability: Degradation Mechanisms and Mitigation Strategies,” J. Power Sources, 148(1), pp. 104–119.
Bi, W. , and Fullera, B. , 2007, “ Temperature Effects on PEM Fuel Cells Pt Catalyst Degradation,” ECS Trans., 11(1), pp. 1235–1246.
Woonki, N. , Bei, G. , and Bill, D. , 2005, “ Nonlinear Control of PEM Fuel Cells by Exact Linearization,” Ind. Appl. Conf., 4(2–6), pp. 2937–2943.
Jia, J. , Wang, Y. , and Lian, D. , 2008, “ Matlab/Simulink Based-Study on PEM Fuel Cell and Battery Hybrid System,” 10th International Conference on Control, Automation, Robotics and Vision (ICARCV 2008), Hanoi, Vietnam, Dec. 17–20, pp. 2108–2113.


Grahic Jump Location
Fig. 2

Causal tree of fuel cell system

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Fig. 3

Causal tree of fuel cell system

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Fig. 4

Causal tree of membrane

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Fig. 5

Causal tree of electrode

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Fig. 6

Output characteristic of Nexa cell fuel

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Fig. 7

Fault tree analysis of the fuel cell degradation

Grahic Jump Location
Fig. 8

Limit variation of r (0.43 ≤ r ≤ 0.658)

Grahic Jump Location
Fig. 9

Limit variation of A (0.0291 ≤ A ≤ 0.0712)

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Fig. 10

Fault tree analysis of the deficiency presenting the limiting values

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Fig. 11

Synoptic diagram of the diagnosis system

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Fig. 12

Output characteristic of the used Nexa cell fuel




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