Empirical Mode Decomposition Applied to Proton Exchange Membrane Electrolyzer for Non-Intrusive Diagnosis

Abstract

The water electrolysis based on Polymeric Electrolyte Membrane technology (E-PEM) is an interesting solution for efficient carbon-free hydrogen production. By the end of the 21st century, the contribution of hydrogen will continue to achieve significant rate in the energy mix. As there have been advances of efficient end-use technologies, hydrogen could even become the main energy carrier [1]. Regarding diagnosis purposes, Empirical Model Decomposition (EMD) method has proven to be a versatile and efficient tool to analyze non-stationary signals and extract features from them [2].As a starting point of its decomposition, oscillations are considered, at a local level, as the sum of a specified number of high and low frequency contributions called Intrinsic Mode Functions (IMFs). IMFs represent the natural oscillatory mode embedded in the signal and work as the basis functions, which makes EMD a self-adaptive method. fig.1 shows the decomposition of the E-PEM current into a finite set of intrinsic mode functions.This study presents a non-intrusive tool designed to fulfill on-line diagnosis requirements. Indeed, the proposed method does not require any excitation signal or stabilization period as Electrochemical Impedance Spectroscopy-based approaches [3]. Therefore, the electrolyzer remains continuously available, even while the diagnosis is being performed. Besides, it only requires measurement of current and has a low computational costs, which are significant economic and technical advantages. Here, EMD has been used to study the anode flow rate dynamics. Several experiments have been conducted and experimental results have demonstrated the effectiveness of the proposed diagnosis tool and its advantages compared to other methods. Acknowledgements This project has received funding from the Reunion Island Region and the European Commission – ERDF References Barbir, “PEM electrolysis for production of hydrogen from renewable energy sources,” Solar Energy, vol. 78, no. 5, pp. 661–669, May 2005, doi: 10.1016/j.solener.2004.09.003. Damour, M. Benne, B. Grondin-Perez, M. Bessafi, D. Hissel, and J.-P. Chabriat, “Polymer electrolyte membrane fuel cell fault diagnosis based on empirical mode decomposition,” Journal of Power Sources, vol. 299, pp. 596–603, Dec. 2015, doi: 10.1016/j.jpowsour.2015.09.041. C. Garcia-Navarro, M. Schulze, and K. A. Friedrich, “Measuring and modeling mass transport losses in proton exchange membrane water electrolyzers using electrochemical impedance spectroscopy,” Journal of Power Sources, vol. 431, pp. 189–204, Aug. 2019, doi: 10.1016/j.jpowsour.2019.05.027. Figure 1: Intrinsic mode functions decomposition for operating conditions of 1.6 V and 0.5 ml.min-1 Figure 1