An Unscented Kalman Filter Based on-line Diagnostic Approach For PEM Fuel Cell Flooding
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Published
Nov 1, 2020
Xian Zhang
Pierluigi Pisu
Abstract
Poor water management usually leads to various degrees of flooding in the hydrogen type fuel cell, affecting both the instantaneous performance and the long-term durability of the system adversely. While a lot of fuel cell diagnostic tools exist that could be utilized for the flooding diagnostics, most of these approaches are intrusive, requiring special modification to the fuel cell that affects its integrity, or special equipment (e.g. AC spectrometer) that adds to the complexity and cost of the system, and therefore are not considered to be a viable solution for the on-board integration of the diagnostic scheme.
This paper proposes a model based approach for the fuel cell flooding diagnostics problem, utilizing only the cell current and voltage, and the inlet pressures of the fuel cell as the input signals of the diagnostic scheme. A diagnostic-oriented fuel cell system dynamic model is developed to incorporate the effects of the fault, i.e. the flooding, on the system dynamics. For simplicity, only the cathode channel flooding, the cathode gas diffusion layer (GDL) flooding, and the anode channel flooding are considered while we neglect the mass transport loss through the anode GDL. The cathode channel flooding and the GDL flooding diagnostic problems are decoupled and formulated as standard joint state and parameter estimation problems, with the amounts of the liquid water treated as varying system parameters to be identified. The unscented Kalman Filter technique has been applied to solve these problems. Simulation results validate the applicability of the cascading unscented Kalman filter design for flooding diagnostics.
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Keywords
PHM
References
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Barbir, F., Gorgun, H., & Wang, X. (2005). Relationship between pressure drop and cell resistance as a diagnostic tool for PEM fuel cells. Journal of Power Sources, 141(1), 96–101. doi:10.1016/j.jpowsour.2004.08.055
Bosco, A. D., & Fronk, M. H. (2000). Fuel cell flooding detection and correction.
Chen, J., & Zhou, B. (2008). Diagnosis of PEM fuel cell stack dynamic behaviors. Journal of Power Sources, 177(1), 83–95.
Danzer, M. A., Wilhelm, J., Aschemann, H., & Hofer, E. P. (2008). Model-based control of cathode pressure and oxygen excess ratio of a PEM fuel cell system. Journal of Power Sources, 176(2), 515–522.
Fouquet, N., Doulet, C., Nouillant, C., Dauphin-Tanguy, G., & Ould-Bouamama, B. (2006). Model based PEM fuel cell state-of-health monitoring via ac impedance measurements. Journal of Power Sources, 159(2), 905–13. doi:10.1016/j.jpowsour.2005.11.035
Gazzarri, J., Eikerling, M., Qianpu Wang, & Zhong-Sheng Liu. (2010). Estimation of Local Relative Humidity in Cathode Catalyst Layers of PEFC. Electrochemical and Solid-State Letters, 13(6), 58–62. doi:10.1149/1.3355233
Gebregergis, A., Pillay, P., & Rengaswamy, R. (2010). PEMFC fault diagnosis, modeling, and mitigation (Vol. 46, pp. 295–303). 445 Hoes Lane / P.O. Box 1331, Piscataway, NJ 08855-1331, United States: Institute of Electrical and Electronics Engineers Inc. doi:10.1109/TIA.2009.2036677
Gorgun, H., Arcak, M., & Barbir, F. (2006). An algorithm for estimation of membrane water content in PEM fuel cells. Journal of Power Sources, 157(1), 389–394. doi:10.1016/j.jpowsour.2005.07.053
Hissel, D., Péra, M., & Kauffmann, J. (2004). Diagnosis of automotive fuel cell power generators. Journal of Power Sources, 128(2), 239–246.
Hoshiko, T., Nakajima, H., Konomi, T., Kitahara, T., & Kita, S. (2008). Estimation of Water Layer Thickness Adjacent to the Cathode Catalyst Layer of a PEFC (Analysis Using Electrochemical Impedance Spectroscopy) (Vol. 16, pp. 2117–2123). ECS. doi:10.1149/1.2982051
Kadyk, T., Hanke-Rauschenbach, R., & Sundmacher, K. (2009). Nonlinear frequency response analysis of PEM fuel cells for diagnosis of dehydration, flooding and CO-poisoning. Journal of Electroanalytical Chemistry, 630(1-2), 19–27.
Kumbur, E. C., Sharp, K. V., & Mench, M. M. (2006). Liquid droplet behavior and instability in a polymer electrolyte fuel cell flow channel. Journal of Power Sources, 161(1), 333–45.
Le Canut, J.-M., Abouatallah, R. M., & Harrington, D. A. (2006). Detection of Membrane Drying, Fuel Cell Flooding, and Anode Catalyst Poisoning on PEMFC Stacks by Electrochemical Impedance Spectroscopy. Journal of The Electrochemical Society, 153(5), A857. doi:10.1149/1.2179200
Makharia, R., Mathias, M. F., & Baker, D. R. (2005). Measurement of Catalyst Layer Electrolyte Resistance in PEFCs Using Electrochemical Impedance Spectroscopy. Journal of The Electrochemical Society, 152(5), A970. doi:10.1149/1.1888367
McKay, D., & Stefanopoulou, A. (2004). Parameterization and validation of a lumped parameter diffusion model for fuel cell stack membrane humidity estimation. In American Control Conference, 2004. Proceedings of the 2004 (Vol. 1, pp. 816–821). Retrieved from http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1383706
McKay, D.A., Ott, W. T., & Stefanopoulou, A. G. (2005). Modeling, parameter identification, and validation of reactant and water dynamics for a fuel cell stack. In 2005 ASME International Mechanical Engineering Congress and Exposition, IMECE 2005, November 5, 2005 - November 11, 2005 (Vol. 74 DSC, pp. 1177–1186). Orlando, FL, United states: American Society of Mechanical Engineers.
McKay, Denise A., Siegel, J. B., Ott, W., & Stefanopoulou, A. G. (2008). Parameterization and prediction of temporal fuel cell voltage behavior during flooding and drying conditions. Journal of Power Sources, 178(1), 207–222.
Narjiss, A., Depernet, D., Candusso, D., Gustin, F., & Hissel, D. (2008). Online diagnosis of PEM fuel cell. In 2008 13th International Power Electronics and Motion Control Conference, EPE-PEMC 2008, September 1, 2008 - September 3, 2008 (pp. 734–739). Poznan, Poland: Inst. of Elec. and Elec. Eng. Computer Society. doi:10.1109/EPEPEMC.2008.4635354
Niroumand, A. M., Merida, W., & Saif, M. (2011). PEM fuel cell low flow FDI. Journal of Process Control, 21(4), 602–612. doi:10.1016/j.jprocont.2010.12.013
O’Hayre, R., Cha, S.-W., Colella, W., & Prinz, F. B. (2009). Fuel Cell Fundamentals (2nd ed.). Wiley.
Pei, P., Ouyang, M., Feng, W., Lu, L., Huang, H., & Zhang, J. (2006). Hydrogen pressure drop characteristics in a fuel cell stack. International Journal of Hydrogen Energy, 31(3), 371–377.
Pukrushpan, J. T., Peng, H., & Stefanopoulou, A. G. (2004). Control-Oriented Modeling and Analysis for Automotive Fuel Cell Systems. Journal of Dynamic Systems, Measurement, and Control, 126(1), 14. doi:10.1115/1.1648308
Steiner, N. Yousfi, Candusso, D., Hissel, D., & Mooteguy, P. (2010). Model-based diagnosis for proton exchange membrane fuel cells (Vol. 81, pp. 158–170). P.O. Box 211, Amsterdam, 1000 AE, Netherlands: Elsevier. doi:10.1016/j.matcom.2010.02.006
Steiner, N.Y., Hissel, D., Mocoteguy, P., & Candusso, D. (2011). Non intrusive diagnosis of polymer electrolyte fuel cells by wavelet packet transform. International Journal of Hydrogen Energy, 36(1), 740–6. doi:10.1016/j.ijhydene.2010.10.033
Vepa, R. (2012). Adaptive State Estimation of a PEM Fuel Cell. IEEE Transactions on Energy Conversion, 27(2), 457–467. doi:10.1109/TEC.2012.2190073
Wan, E., & Merwe, R. (2001). Chapter 7: The Unscented Kalman Filter. In Kalman Filtering and Neural Networks. Wiley Publishing.
Wasterlain, S., Harel, F., Candusso, D., Hissel, D., & Francois, X. (2009). First results obtained with an impedance meter developed for the diagnosis of large Proton-Exchange-Membrane Fuel-Cell stacks. In Advanced Electromechanical Motion Systems & Electric Drives Joint Symposium, 2009. ELECTROMOTION 2009. 8th International Symposium on (pp. 1–6).
Wu, J., Yuan, X. Z., Wang, H., Blanco, M., Martin, J. J., & Zhang, J. (2008). Diagnostic tools in PEM fuel cell research: Part I Electrochemical techniques. International Journal of Hydrogen Energy, 33(6), 1735–1746.
Xiaozi Yuan, Haijiang Wang, Jian Colin Sun, & Jiujun Zhang. (2007). AC impedance technique in PEM fuel cell diagnosis - a review. International Journal of Hydrogen Energy, 32(17), 4365–80. doi:10.1016/j.ijhydene.2007.05.036
Yuan, X., Sun, J. C., Wang, H., & Zhang, J. (2006). AC impedance diagnosis of a 500 W PEM fuel cell stack. Part II: Individual cell impedance. Journal of Power Sources, 161(2), 929–937. doi:10.1016/j.jpowsour.2006.07.020
Zhang, X. (2012). Prognostic and Health-Management Oriented Fuel Cell Modeling and On-line Supervisory System Development (Dissertation). Clemson University.
Zhang, X., & Pisu, P. (2012). An Unscented Kalman Filter Based Approach for the Health-Monitoring and Prognostics of a PEM Fuel Cell (Vol. 3). Presented at the Annual Conference of the Prognostics and Health Management Society 2012, Minneapolis, MN.
Zhang, X., & Pisu, P. (2014). Prognostic-oriented Fuel Cell Aging Modeling and Its Application to Health-Monitoring and Prognostics of a PEM Fuel Cell. International Journal of Prognostics and Health Management 1(5).
Arcak, M., Gorgun, H., Pedersen, L. M., & Varigonda, S. (2004). A Nonlinear Observer Design for Fuel Cell Hydrogen Estimation. IEEE Transactions on Control Systems Technology, 12(1), 101–110. doi:10.1109/TCST.2003.821958
Barbir, F., Gorgun, H., & Wang, X. (2005). Relationship between pressure drop and cell resistance as a diagnostic tool for PEM fuel cells. Journal of Power Sources, 141(1), 96–101. doi:10.1016/j.jpowsour.2004.08.055
Bosco, A. D., & Fronk, M. H. (2000). Fuel cell flooding detection and correction.
Chen, J., & Zhou, B. (2008). Diagnosis of PEM fuel cell stack dynamic behaviors. Journal of Power Sources, 177(1), 83–95.
Danzer, M. A., Wilhelm, J., Aschemann, H., & Hofer, E. P. (2008). Model-based control of cathode pressure and oxygen excess ratio of a PEM fuel cell system. Journal of Power Sources, 176(2), 515–522.
Fouquet, N., Doulet, C., Nouillant, C., Dauphin-Tanguy, G., & Ould-Bouamama, B. (2006). Model based PEM fuel cell state-of-health monitoring via ac impedance measurements. Journal of Power Sources, 159(2), 905–13. doi:10.1016/j.jpowsour.2005.11.035
Gazzarri, J., Eikerling, M., Qianpu Wang, & Zhong-Sheng Liu. (2010). Estimation of Local Relative Humidity in Cathode Catalyst Layers of PEFC. Electrochemical and Solid-State Letters, 13(6), 58–62. doi:10.1149/1.3355233
Gebregergis, A., Pillay, P., & Rengaswamy, R. (2010). PEMFC fault diagnosis, modeling, and mitigation (Vol. 46, pp. 295–303). 445 Hoes Lane / P.O. Box 1331, Piscataway, NJ 08855-1331, United States: Institute of Electrical and Electronics Engineers Inc. doi:10.1109/TIA.2009.2036677
Gorgun, H., Arcak, M., & Barbir, F. (2006). An algorithm for estimation of membrane water content in PEM fuel cells. Journal of Power Sources, 157(1), 389–394. doi:10.1016/j.jpowsour.2005.07.053
Hissel, D., Péra, M., & Kauffmann, J. (2004). Diagnosis of automotive fuel cell power generators. Journal of Power Sources, 128(2), 239–246.
Hoshiko, T., Nakajima, H., Konomi, T., Kitahara, T., & Kita, S. (2008). Estimation of Water Layer Thickness Adjacent to the Cathode Catalyst Layer of a PEFC (Analysis Using Electrochemical Impedance Spectroscopy) (Vol. 16, pp. 2117–2123). ECS. doi:10.1149/1.2982051
Kadyk, T., Hanke-Rauschenbach, R., & Sundmacher, K. (2009). Nonlinear frequency response analysis of PEM fuel cells for diagnosis of dehydration, flooding and CO-poisoning. Journal of Electroanalytical Chemistry, 630(1-2), 19–27.
Kumbur, E. C., Sharp, K. V., & Mench, M. M. (2006). Liquid droplet behavior and instability in a polymer electrolyte fuel cell flow channel. Journal of Power Sources, 161(1), 333–45.
Le Canut, J.-M., Abouatallah, R. M., & Harrington, D. A. (2006). Detection of Membrane Drying, Fuel Cell Flooding, and Anode Catalyst Poisoning on PEMFC Stacks by Electrochemical Impedance Spectroscopy. Journal of The Electrochemical Society, 153(5), A857. doi:10.1149/1.2179200
Makharia, R., Mathias, M. F., & Baker, D. R. (2005). Measurement of Catalyst Layer Electrolyte Resistance in PEFCs Using Electrochemical Impedance Spectroscopy. Journal of The Electrochemical Society, 152(5), A970. doi:10.1149/1.1888367
McKay, D., & Stefanopoulou, A. (2004). Parameterization and validation of a lumped parameter diffusion model for fuel cell stack membrane humidity estimation. In American Control Conference, 2004. Proceedings of the 2004 (Vol. 1, pp. 816–821). Retrieved from http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1383706
McKay, D.A., Ott, W. T., & Stefanopoulou, A. G. (2005). Modeling, parameter identification, and validation of reactant and water dynamics for a fuel cell stack. In 2005 ASME International Mechanical Engineering Congress and Exposition, IMECE 2005, November 5, 2005 - November 11, 2005 (Vol. 74 DSC, pp. 1177–1186). Orlando, FL, United states: American Society of Mechanical Engineers.
McKay, Denise A., Siegel, J. B., Ott, W., & Stefanopoulou, A. G. (2008). Parameterization and prediction of temporal fuel cell voltage behavior during flooding and drying conditions. Journal of Power Sources, 178(1), 207–222.
Narjiss, A., Depernet, D., Candusso, D., Gustin, F., & Hissel, D. (2008). Online diagnosis of PEM fuel cell. In 2008 13th International Power Electronics and Motion Control Conference, EPE-PEMC 2008, September 1, 2008 - September 3, 2008 (pp. 734–739). Poznan, Poland: Inst. of Elec. and Elec. Eng. Computer Society. doi:10.1109/EPEPEMC.2008.4635354
Niroumand, A. M., Merida, W., & Saif, M. (2011). PEM fuel cell low flow FDI. Journal of Process Control, 21(4), 602–612. doi:10.1016/j.jprocont.2010.12.013
O’Hayre, R., Cha, S.-W., Colella, W., & Prinz, F. B. (2009). Fuel Cell Fundamentals (2nd ed.). Wiley.
Pei, P., Ouyang, M., Feng, W., Lu, L., Huang, H., & Zhang, J. (2006). Hydrogen pressure drop characteristics in a fuel cell stack. International Journal of Hydrogen Energy, 31(3), 371–377.
Pukrushpan, J. T., Peng, H., & Stefanopoulou, A. G. (2004). Control-Oriented Modeling and Analysis for Automotive Fuel Cell Systems. Journal of Dynamic Systems, Measurement, and Control, 126(1), 14. doi:10.1115/1.1648308
Steiner, N. Yousfi, Candusso, D., Hissel, D., & Mooteguy, P. (2010). Model-based diagnosis for proton exchange membrane fuel cells (Vol. 81, pp. 158–170). P.O. Box 211, Amsterdam, 1000 AE, Netherlands: Elsevier. doi:10.1016/j.matcom.2010.02.006
Steiner, N.Y., Hissel, D., Mocoteguy, P., & Candusso, D. (2011). Non intrusive diagnosis of polymer electrolyte fuel cells by wavelet packet transform. International Journal of Hydrogen Energy, 36(1), 740–6. doi:10.1016/j.ijhydene.2010.10.033
Vepa, R. (2012). Adaptive State Estimation of a PEM Fuel Cell. IEEE Transactions on Energy Conversion, 27(2), 457–467. doi:10.1109/TEC.2012.2190073
Wan, E., & Merwe, R. (2001). Chapter 7: The Unscented Kalman Filter. In Kalman Filtering and Neural Networks. Wiley Publishing.
Wasterlain, S., Harel, F., Candusso, D., Hissel, D., & Francois, X. (2009). First results obtained with an impedance meter developed for the diagnosis of large Proton-Exchange-Membrane Fuel-Cell stacks. In Advanced Electromechanical Motion Systems & Electric Drives Joint Symposium, 2009. ELECTROMOTION 2009. 8th International Symposium on (pp. 1–6).
Wu, J., Yuan, X. Z., Wang, H., Blanco, M., Martin, J. J., & Zhang, J. (2008). Diagnostic tools in PEM fuel cell research: Part I Electrochemical techniques. International Journal of Hydrogen Energy, 33(6), 1735–1746.
Xiaozi Yuan, Haijiang Wang, Jian Colin Sun, & Jiujun Zhang. (2007). AC impedance technique in PEM fuel cell diagnosis - a review. International Journal of Hydrogen Energy, 32(17), 4365–80. doi:10.1016/j.ijhydene.2007.05.036
Yuan, X., Sun, J. C., Wang, H., & Zhang, J. (2006). AC impedance diagnosis of a 500 W PEM fuel cell stack. Part II: Individual cell impedance. Journal of Power Sources, 161(2), 929–937. doi:10.1016/j.jpowsour.2006.07.020
Zhang, X. (2012). Prognostic and Health-Management Oriented Fuel Cell Modeling and On-line Supervisory System Development (Dissertation). Clemson University.
Zhang, X., & Pisu, P. (2012). An Unscented Kalman Filter Based Approach for the Health-Monitoring and Prognostics of a PEM Fuel Cell (Vol. 3). Presented at the Annual Conference of the Prognostics and Health Management Society 2012, Minneapolis, MN.
Zhang, X., & Pisu, P. (2014). Prognostic-oriented Fuel Cell Aging Modeling and Its Application to Health-Monitoring and Prognostics of a PEM Fuel Cell. International Journal of Prognostics and Health Management 1(5).
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Technical Papers