Water electrolysis under dynamic conditions: diagnosis and process enhancement

Proton exchange membrane water electrolysis (PEMWE) is a key technology for storing excess electrical energy produced by renewable sources in form of hydrogen (Fig. 1). To achieve the high productivity of hydrogen, operation at high current density is necessary. However, for this operating condition, high performance losses appear. Currently, a significant part of voltage losses at high current densities is assigned to mass transfer resistances in the anode porous transport layer. In addition to the mass transport, ohmic and kinetic resistances are present in the system. The contributions of different resistances to the total losses, as well as the influence of the operating and design parameters on the individual losses, are not understood yet.


Fig. 1: Water electrolysis is a key technology for storing excess electrical energy produced by renewable sources in form of hydrogen
 

In this work, we aim to employ a close combination of modeling and dynamic experiments for the discrimination of processes occurring in PEMWE. A complex combination of the processes occurring at different scales requires the implementation of the multiscale model for describing the operation of the PEMWE. Therefore, the macroscopic model describing the electrolyzer performance will be combined with the pore network model (PNM). PNM was shown to be a suitable approach for the systematic optimization and understanding of the PTLs, and in this work, it is used to parametrize the macro-scale model. Secondly, the experimental analysis will allow for the validation of the developed multiscale model. On one hand, neutron and optical imaging experiments will be used to study the two-phase transport in the electrolyzer, especially within anode PTL. Furthermore, dynamic methods will be developed and employed for the electrochemical analysis of the water electrolyzer. The most common dynamical method used in electrochemistry is electrochemical impedance spectroscopy (EIS). However, the major drawback of the EIS is that it can not differentiate between the processes happening at similar time scales. To overcome this, we will apply nonlinear frequency response (NFR) analysis. NFR analysis can be regarded as a generalization of the traditional EIS by expansion to the nonlinear domain or/and non-electrical variables. Thus, it can give additional information about the analyzed system. Additionally, the possibility of process improvement through the forced periodic operation will be investigated.

The final goal of this work is to understand different processes occurring in the PEMWE and to determine operating and design conditions that would lead to process improvement.

Funding: IMPRS

Collaborations:

Prof. Tsotsas & Dr. Vorhauer-Huget, OVGU Magdeburg

Selected recent publications:

[1] Vorhauer, N., Altaf, H., Tsotsas, E., Vidakovic-Koch, T., Pore Network Simulations of Gas-Liquid Distribution in Porous Transport Layers, Processes 2019, 7 p. 558
[2] Altaf, H., Vorhauer, N., Tsotsas, E., Vidakovic-Koch, T., Steady-State Water Drainage by Oxygen in Anodic Porous Transport Layer of Electrolyzers: A 2D Pore Network Simulation, Processes, 2020, 3, p.362
[3] Vorhauer-Huget, N., Altaf, H., Dürr, R., Tsotsas, E., Vidakovic-Koch, T., Computational Optimization of Porous Structures for Electrochemical Processes. Processes, 2020. 8: p. 1205

 

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