Proton exchange membrane fuel cell fault and degradation detection using a coefficient of variance method

Year 2021, Volume: 5 Issue: 1, 20 - 34, 31.03.2021

Sujit Barhate Rohini Mudhalwadkar

https://doi.org/10.30521/jes.817879

Cited By: 2

Abstract

Proton exchange membrane fuel cell is a clean energy generator as it emits water as a by-product. The fuel cell has various applications in stationary power generation and transportation. However, there is a need to improve durability for transportation applications. Fuel cell durability is limited as its performance degrades over a period due to aging, and fault conditions. In this study, we have compared fuel cell performance by using a new cell, and an aged cell. Degradation due to aging is experimented with by using a membrane that was operated for more than 2000 hours. Fuel cell performance degrades around 90% due to aging. Moreover, experimentally faults were created to study the degradation of fuel cell performance. We created three faults in the fuel cell system: Water flooding, reactant gas starvation, and high operating temperature. Fuel cell performance observed more than 30% degradation during the fault conditions. Furthermore, the coefficient of variance technique is used to detect aging, and the fault condition.

Keywords

Coefficient of variance, Degradation, Fault, Fuel cell, PEM

Supporting Institution

Department of Automobile Engineering, PSG College of Technology, Coimbatore, India

Thanks

We sincerely thank Dr. P. Karthikeyan for his guidance. We are thankful to his research group for helping us in the experimentation.

References

• [1] Monthly Energy Review April 2020. U. S. Energy Information Administration, Office of Energy Statistics, U. S. Department of Energy, Washington, DC.
• [2] Thompson, ST, Papageorgopoulos, D. Platinum group metal-free catalysts boost cost competitiveness of fuel cell vehicles. Nature Catalysis 2019; 2: 558-561.
• [3] Gaikwad, SD, Ghosh, PC. Sizing of fuel cell electric vehicle: A pinch analysis-based approach. International Journal of Hydrogen Energy 2020; 45(15): 8985-8993, DOI: 10.1016/j.ijhydene.2020.01.116
• [4] Khan, SS, Shareef, H, Mutlag, AH. Dynamic temperature model for proton exchange membrane fuel cell using online variations in load current and ambient temperature. International Journal of Green Energy 2019; 16(5): 361-370, DOI: 10.1080/15435075.2018.1564141
• [5] Lue, X, Qu, Y, Wang, Y, Qin, C, Liu, G. A comprehensive review on hybrid power system for PEMFC-HEV: issues and strategies. Energy Convers Manag 2018; 171: 1273-91, DOI: 10.1016/j.enconman.2018.06.065
• [6] Vichard, L, Harel, F, Ravey, A, Venet, P, Hissel, D. Degradation prediction of PEM fuel cell based on artificial intelligence. International Journal of Hydrogen Energy 2020; 45(29): 14953-14963, DOI: 10.1016/j.ijhydene.2020.03.209
• [7] Wang, Z. Lifetime Prediction Modeling of Automotive Proton Exchange Membrane Fuel Cells. SAE Technical Paper 2019; 2019-01-0385, DOI: 10.4271/2019-01-0385
• [8] Detti, AH, Steiner, NY, Bouillaut, L, Same, AB, Jemei, S. Fuel Cell Performance Prediction using an AutoRegressive Moving-Average ARMA Model. In: IEEE Vehicle Power and Propulsion Conference; 14-17 October 2019: IEEE, DOI: 10.1109/VPPC46532.2019.8952535
• [9] Kim, TY, Kim, BS, Park, TC, Yeo, YK. Development of Predictive Model based Control Scheme for a Molten Carbonate Fuel Cell (MCFC) Process. International Journal of Control, Automation and Systems 2018; 16(2): 791-803, DOI: 10.1007/s12555-016-0234-0
• [10] Zhou, D, Al-Durra, A, Zhang, K, Ravey, A, Gao, F. Online remaining useful life prediction of proton exchange membrane fuel cells using a novel robust methodology. Journal of Power Sources 2018; 399: 314-328, DOI: 10.1016/j.jpowsour.2018.06.098
• [11] Davies, B, Jackson, L, Dunnett, S. Expert diagnosis of polymer exchange fuel cells. International Journal of Hydrogen Energy 2017; 42: 11724-11734, DOI: 10.1016/j.ijhydene.2017.02.121
• [12] Mao, L, Jackson, L, Jackson, T. Investigation of polymer electrolyte membrane fuel cell internal behaviour during long term operation and its use in prognostics. Journal of Power Sources 2017; 362: 39-49, DOI: 10.1016/j.jpowsour.2017.07.018
• [13] Chen, K, Laghrouche, S, Djerdir, A. Degradation model of proton exchange membrane fuel cell based on a noval hybrid method. Applied Energy 2019; 252: 113439, DOI: 10.1016/j.apenergy.2019.113439
• [14] Barhate, SS, Mudhalwadkar, R, Prakash, AK. A survey on factors affecting performance and durability of PEM Fuel Cells in Automotive applications. International Journal of Control Theory and Applications 2017; 10(9): 659-669.
• [15] Liu, H, Chen, J, Hou, M, Shao, Z, Su, H. Data-based short-term prognostics for proton exchange membrane fuel cells. International Journal of Hydrogen Energy 2017; 42: 20791-20808, DOI: 10.1016/j.ijhydene.2017.06.180
• [16] Hissel, D, Pera, MC. Diagnostic & health management of fuel cell systems: Issues and solutions. Annual Reviews in Control 2016; 42: 201-211, DOI: 10.1016/j.arcontrol.2016.09.005
• [17] Saadi, A, Becherif, M, Aboubouc, A, Ayad, MY. Comparison of proton exchange membrane fuel cell static models. Renewable Energy 2013; 56: 64-71, DOI: 10.1016/j.renene.2012.10.012
• [18] Pathapati, PR, Xue, X, Tang, J. A new dynamic model for predicting transient phenomena in a PEM fuel cell system. Renewable Energy 2005; 30: 1–22, DOI: 10.1016/j.renene.2004.05.001
• [19] Chen, M, Rincon-Mora, GA. Accurate Electrical Battery Model Capable of Predicting Runtime and I–V Performance. IEEE Transactions on Energy Conversion 2006; 21(2): 504-511, DOI: 10.1109/TEC.2006.874229
• [20] Ritzberger, D, Striednig, M, Simon, C, Hametner, C, Jakubek, S. Online estimation of the electrochemical impedance of polymer electrolyte membrane fuel cells using broad-band current excitation. Journal of Power Sources 2018; 405: 150-161, DOI: 10.1016/j.jpowsour.2018.08.082
• [21] Jeppesen, C, Araya, SS, Sahlin, SL, Thomas, S, Andreasen, SJ, Kaer, SK. Fault detection and isolation of high temperature proton exchange membrane fuel cell stack under the influence of degradation. Journal of Power Sources 2017; 359: 37-47, DOI: 10.1016/j.ijhydene.2014.04.163
• [22] Pivac, I, Bezmalinovic, D, Barbir, F. Catalyst degradation diagnostics of proton exchange membrane fuel cells using electrochemical impedance spectroscopy. International Journal of Hydrogen Energy 2018; 43: 13512-13520, DOI: 10.1016/j.ijhydene.2018.05.095
• [23] Ifrek, L, Rosini, S, Cauffet, G, Chadebek, O, Rouveyre, L, Bultel, Y. Fault detection for polymer electrolyte membrane fuel cell stack by external magnetic field. Electrochimica Acta 2019; 313: 141-150, DOI: 10.1016/j.electacta.2019.04.193
• [24] Abbaspour, A, Yen, KK, Forouzannezhad, P, Sargolzaei A. Active Adaptive Fault-Tolerant Control Design for PEM Fuel Cells. In: IEEE Energy Conversion Congress and Exposition, 23-27 September 2018: IEEE, DOI: 10.1109/ECCE.2018.8557620
• [25] Pivac, I, Simic, B, Barbir, F. Experimental diagnostics and modeling of inductive phenomena at low frequencies in impedance spectra of proton exchange membrane fuel cells. Journal of Power Sources 2017; 365: 240-248, DOI: 10.1016/j.jpowsour.2017.08.087
• [26] Lin, RH, Pei, ZX, Ye, ZZ, Guo, CC, Wu, BD. Hydrogen fuel cell diagnostics using random forest and enhanced feature selection. International Journal of Hydrogen Energy 2020; 45(17), 10523-10535, DOI: 10.1016/j.ijhydene.2019.10.127
• [27] Noorkami, M, Robinson, JB, Meyer, Q, Obeisun, OA, Fraga, ES, Reisch, T, Shearing, PR, Brett, DJL. Effect of temperature uncertainty on polymer electrolyte fuel cell performance. International Journal of Hydrogen Energy 2014; 39: 1439-1448, DOI: 10.1016/j.ijhydene.2013.10.156
• [28] Liu, LF, Liu, B, Wu, CW. Reliability prediction of large fuel cell stack based on structure stress analysis. Journal of Power Sources 2017; 363: 95-102, DOI: 10.1016/j.jpowsour.2017.06.041
• [29] Nagasawa, T, Hanamura, K. Investigation of oxide ion flux at cathode/electrolyte interface in solid oxide fuel cell. Journal of Power Sources 2019; 412: 695-700, DOI: 10.1016/j.jpowsour.2018.12.013
• [30] Hou, Y, Ouyang, Y, Pei, F, Hao, D. Voltage and Voltage Consistency Attenuation Law of the Fuel Cell Stack Based on the Durability Cycle Condition. SAE Technical Paper 2019; 2019-01-0386, DOI: 10.4271/2019-01-0386
• [31] Zhoung, D, Lin, R, Jiang, Z, Zhu, Y, Liu, D, Cai, X, Chen, L. Low temperature durability and consistency analysis of proton exchange membrane fuel cell stack based on comprehensive characterization. Applied Energy 2020; 264: 114626, DOI: 10.1016/j.apenergy.2020.114626