Research Papers

Fuel Cell Diagnostics Using Identification Measurement Theory

[+] Author and Article Information
K. T. Koshekov

Department of Energetics and Instrumentation,
North-Kazakhstan State University,
ul. Pushkina, 86,
Petropavlovsk KZ-150000, Kazakhstan
e-mail: kkoshekov@mail.ru

Yu. N. Klikushin

Department of the Technology of Electronics,
Omsk State Technical University,
pr. Mira, 11,
Omsk RU-644050, Russia
e-mail: iit@omgtu.ru

V. Yu. Kobenko

Department of the Technology of Electronics,
Omsk State Technical University,
pr. Mira, 11,
Omsk RU-644050, Russia
e-mail: kobra_vad@rambler.ru

Yu. K. Evdokimov

Department of Radio Electronics
and Measuring Instruments,
Kazan National Research
Technical University,
ul. K. Marksa, 10,
Kazan RU-420111, Russia
e-mail: evdokimov1@mail.ru

A. V. Demyanenko

Department of Energetics and Instrumentation,
North-Kazakhstan State University,
ul. Pushkina, 86,
Petropavlovsk KZ-150000, Kazakhstan
e-mail: demianenkoav@mail.ru

1Corresponding author.

Contributed by the Advanced Energy Systems Division of ASME for publication in the JOURNAL OF FUEL CELL SCIENCE AND TECHNOLOGY. Manuscript received March 5, 2014; final manuscript received March 18, 2014; published online May 2, 2014. Editor: Nigel M. Sammes.

J. Fuel Cell Sci. Technol 11(5), 051003 (May 02, 2014) (9 pages) Paper No: FC-14-1027; doi: 10.1115/1.4027395 History: Received March 05, 2014; Revised March 18, 2014

The possibility to use instruments of identification measurement theory to solve the problems of diagnostics of fuel cells according to their noise characteristics is considered in this paper. The offered techniques of diagnostic signals processing are based on the identification measurement of time and probabilistic characteristics, the comparison of model signals with the ones under analysis according to the reading values, the classification of signals according to the waveform parameter and characteristic frequency, the building of hierarchical structures, and the assessment of the signal structures by the fractal indices. All proposed techniques are applicable for the diagnosis of a fuel cell, but thanks to graphical representation of classification trees of noise signals, the more efficient method for experts is the one based on the building of hierarchical structures.

Copyright © 2014 by ASME
Topics: Signals , Fuel cells
Your Session has timed out. Please sign back in to continue.


Barbir, F., 2005, PEM Fuel Cells. Theory and Practice, Elsevier, New York.
Kadjo, J.-J. A., Garnier, J.-P., Maye, J.-P., Martemianov, S. A., Coutanceau, Ch., Evdokimov, Yu. K., Bazylev, N. B., Fomin, N. A., Lavinskaya, E. I., Grigoriev, S. A., and Fateev, V. N., 2005, “PEM FUEL CELL Study by Multidisciplinary Approach,” Minsk International Colloquium on Physics of Shock Waves, Combustion, Detonation and Non-Equilibrium Processes (MIC 2005), Minsk, Belarus, November 12–17, pp. 40–41.
Bograchev, D., and MartemianovS., 2011, “Thermo-Electrical Instabilities Arising in Proton Exchange Membrane of Fuel Cell,” Int. J. Heat Mass Transfer, 54(11), pp. 4965–4971. [CrossRef]
Evdokimov, Yu. K., Denisov, E. S., and Martemianov, S. A., 2009, “Electrical Noise of Hydrogen Fuel Cell and Diagnostic Characteristic Research,” Nonlinear World, 7(9), pp. 706–713. Available at: http://www.radiotec.ru/catalog.php?cat=jr11&art=7022
Yevdokimov, Y. K., and Denisov, D. S., 2011, “On Developing the Systems of Control and Diagnostics of Hydrogen Fuel Cell by Using as the Base Its Electrical Fluctuations and Noises,” Herald Kazan State Technical Univ., 61, pp. 47–54.
Lopes, V. V., Rangel, C. M., and Novais, A. Q., 2013, “Modeling and Identification of the Dominant Phenomena in Hydrogen Fuel-Cells by the Application of DRT Analysis,” Comput. Aided Chem. Eng., 32, pp. 283–288. [CrossRef]
Denisov, E. S., 2008, “Nonlinear and Linear Electric Models of a Hydrogen Fuel Cell and Identification of Its Parameters,” Nonlinear World, 6(8), pp. 483–488. Available at: http://www.radiotec.ru/catalog.php?cat=jr11&art=4975
Giurgea, S., Tirnovan, R., Hissel, D., and Outbib, R., 2013, “An Analysis of Fluidic Voltage Statistical Correlation for a Diagnosis of PEM Fuel Cell Flooding,” Int. J. Hydrogen Energy, 38(11), pp. 4689–4696. [CrossRef]
Kanevskii, L. S., Grafov, B. M., and Astaf'ev, M. G., 2005, “Dynamics of Electrochemical Noise of the Lithium Electrode in Aprotic Organic Electrolytes,” Russ. J. Electrochem., 41(10), pp. 1091–1096. [CrossRef]
Liu, L., 2008, “Pitting Mechanism on an Austenite Stainless Steel Nanocrystalline Coating Investigate by Electrochemical Noise and In-Situ AFM Analysis,” Electrochim. Acta, 54(2), pp. 768–780. [CrossRef]
Martinet, S., Durand, R., Ozil, P., Leblanc, P., and Blanchard, P., 1999, “Application of Electrochemical Noise Analysis to the Study of Batteries: State-of-Charge Determination and Overcharge Detection,” J. Power Sources, 83(1–2), pp. 93–99. [CrossRef]
Sergi, F., Brunaccini, G., Stassi, A., Di Blasi, A., Dispenza, G., Aricò, A. S., Ferraro, M., and Antonucci.V., 2011, “PEM Fuel Cells Analysis for Grid Connected Applications,” Int. J. Hydrogen Energy, 36(17), pp. 10,908–10,916. [CrossRef]
Pukėnas, K., 2010, “Nonlinear Detection of Weak Pseudoperiodic Signals Hidden Under the Noise Floor,” Electron. Electric. Eng., 4(100), pp. 77–80.
Přibil, J., Přibilová, A., and Frollo, I., 2012, “Analysis of Spectral Properties of Acoustic Noise Produced During Magnetic Resonance Imaging,” Appl. Acoust., 73(8), pp. 687–697. [CrossRef]
Klikushin, Yu. N., and Koshekov, K. T., 2011, Fundamentals of Identification Measurements and Transformation, Academic Publishing, Saarbrücken, Germany.
Gubarev, V. V., 1992, Probabilistic Models: Reference Book, NETI, Novosibirsk, Russia.
Gorshenkov, A. A., and Klikushin, Y. N., 2010, “Presentation of Models of Signals in the System Identifiers,” J. Radio Electronics, No. 9, http://jre.cplire.ru
Ward, J. H., 1963, “Hierarchical Grouping to Optimize an Objective Function,” J. Am. Stat. Assoc., 58(301), pp. 236–244. [CrossRef]
Klikushin, Yu. N., 2000, “Identification Scales: Theory, Technologies, Systems,” Ph.D. thesis, Omsk State Technical University, Omsk, Russia.
Klikushin, Yu. N., 2000, “Classification Scales for Probability Distributions,” J. Radio Electronics, No. 11, http://jre.cplire.ru
Klikushin, Y. N., and Koshekov, K. T., 2010, “Signal Classifier,” J. Radio Electronics, No. 10, http://jre.cplire.ru
Feder, E., 1991, Fractals, Mir, Moscow.
Anischenko, V. S., and Saparin, P. I., 1989, “Dimension of Feigenbaum's Transition Attractors in the Experiment,” J. Tech. Phys, Lett., 15(24), pp. 28–32. Available at: http://journals.ioffe.ru/pjtf/1989/24/p28-32.pdf
Klikushin, Yu. N., Gorshenkov, A. A., and Kobenko, V. Yu., 2013, “Identification Method of Comparison of Signals,” Testing. Diagn., 6, pp. 28–34.
Gorshenkov, A. A., Klikushin, Yu. N., and Kobenko, V. Yu., 2012, “Algorithm for Detecting, Measuring and Classifying Signal Trends,” Digital Sign. Process., 2, pp. 46–48. Available at: http://www.dspa.ru/en/2012/dsp-2012-2.htm


Grahic Jump Location
Fig. 1

Identification measurement logic

Grahic Jump Location
Fig. 2

Visual patterns of signal time characteristic (waveform graph) and probabilistic characteristic (histogram) files: (a) R1_0.4.txt, (b) R1_1.txt, (c) R1_2.4.txt, (d) R1_4.4.txt, (e) R1_10.4.txt, and (f) R1_OC.txt

Grahic Jump Location
Fig. 3

Classification tree algorithm

Grahic Jump Location
Fig. 4

The example of assessment algorithm for rank distance between the scales

Grahic Jump Location
Fig. 5

General tree of FC noise signals




Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In