Day 2 :
University of Padua, Italy
Keynote: A selective hybrid stochastic approach to proton exchange membrane fuel cells multi parameter identification
Time : 09:00-09:40
Massimo Guarnieri completed his MS degree in Electrical Engineering at University of Padua, Italy, in 1979 and his PhD degree in Electrical Science in Rome in 1987. He joined Italian National Council of Research in 1982 and University of Padua in 1983, where he has been Full Professor of Electrical Engineering since 2000. Initially, he worked on devices for thermonuclear fusion research. He later centered his research interests on electromagnetic computation. In the last ten years, he has been involved in modeling and designing electrochemical storage devices. He is interested in the history of technology and science. He is a Columnist and a member of the Editorial Board of IEEE Industrial Electronics Magazine.
The characterization of fuel cells involves a number of physical parameters which are important for quantifying and comparing the performance of the materials and for trimming analytical and numerical models. Careful ex situ measurements of such parameters can be performed by means of a number of diagnostic techniques, whose results are however not completely consistent with fuel cell operation due to several side effect. Conversely, in situ measurements can provide meaningful operational values, but a very few techniques are available to determine a limited number of parameters. An alternative consists in multiple parameter identification from multiple fundamental measurements performed in different conditions, e.g., at different temperature, pressure, concentration, and humidification. If there is only one unknown parameter, the solution is easy, requiring just a statistical interpolating technique. In the case of multiple unknown parameters, the problem becomes increasingly challenging with the number of parameters, as duplicity problem emerges, i.e., several groups of parameters may lead to the same performance (e.g. polarization curve). A number of numerical tools have been proposed to face this kind of problems. Stochastic mathematical models have been applied to the analysis of fuel cells for more than ten years, but typically to specific problems and by means of semi-empirical models, with an increased number of articles published in the last years. We present an original formulation that makes use of an accurate zero-dimensional multi-physical model of a polymer electrolyte membrane fuel cell and of two cooperating stochastic algorithms, particle swarm optimization (PSO) and differential evolution (DE), that proved to be successful in extracting multiple material parameters (exchange current density, mass transfer coefficient, diffusivity, conductivity, and activation barriers) from the experimental data of multiple polarization curves (i.e., in situ measurements) under controlled temperature, gas back pressure and humidification. The method is suitable for application in other fields where fitting of multiphysics nonlinear models is involved.
1. Alotto P., Guarnieri M., Moro F., “Redox Flow Batteries for the storage of renewable energy: a review”, Renewable & Sustainable Energy Reviews 29 (2014): 325-335.
2. Guarnieri M., Alotto P., Moro F., “Modeling the Performance of Hydrogen-Oxygen Unitized Regenerative Proton Exchange Membrane Fuel Cells for Energy Storage”, Journal of Power Sources 297, (11), (2015): 23-32.
3. Guarnieri M., Negro E., Di Noto V., Alotto P., “A Selective Hybrid Stochastic Strategy for Fuel-Cell Multi-Parameter Identification”, Journal of Power Sources 332 (2016): 249–264.
4. Spagnuolo G., Petrone G., Mattavelli P., Guarnieri M., “Vanadium Redox Flow Batteries: Potentials and Challenges of an Emerging Storage Technology”, IEEE Industrial Electronics Magazine 10 (4), (2016): 20-31.
5. Maggiolo D., Picano F., Guarnieri M., “Flow and dispersion in anisotropic porous media: a Lattice-Boltzmann study”, Physics of Fluids, 28 (10), (2016): 102001.
6. Moro F., Trovò A., Bortolin S., Del Col D., Guarnieri M., “An alternative low-loss stack architecture for vanadium redox flow battery: comparative assessment”, Journal of Power Sources, 340 (2017)
Auckland University of Technology, New Zealand
Keynote: Measurement techniques and related challenges involved in the gas diffusion electrode characterization of PEM fuel cell stack
Time : 09:40-10:20
Arunkumar Jayakumar is a Research Fellow at Auckland University of Technology, New Zealand. He has 10 years of experience in PEM fuel cell stacks and systems. He has worked with wide range of Ballard’s stack namely, Nexa, 1020 ACS and 1310 WCS. His research activities include PEM fuel cell stacks and systems, sensor, electric vehicles, material characterization and hydrogen energy. His research is currently funded by the IBTec, AUT. He is a member of the IPENZ, IEEE and ASME.
Proton Exchange Membrane (PEM) fuel cells are emerging as a commercially viable alternative for the production of clean and reliable energy. The Membrane Electrode Assembly (MEA) is the principal component of a PEM fuel cell. The operation of the fuel cell involves the hydrogen (fuel) being supplied to the anode and oxygen/air being fed to the cathode. At the anode region, the hydrogen is oxidized to protons and electrons the membrane allows protons to pass through it while the electrons are forced to travel through the external circuit. At the cathode, the oxidant is reduced and in this way, electricity is drawn from the cell. Figure 1 illustrates a single PEM cell, indicating various sub-components and the charge transfer. PEM fuel cell performance is meticulously correlated to the gas diffusion electrodes (GDE). GDE in a PEM fuel cell stack usually comprises of the catalyst layer and the gas diffusion layer and the present paper provides a comprehensive measurement issues pertaining to the characterization of GDE. The various GDE characterizations (in situ and ex situ) and the corresponding instrument involved in the present paper is listed as follows in the table 1. Gas diffusion electrode characterization is complex, which involves the existence of both solid and fluid phases, and due to the random morphology of the diffusion electrode. However, these characteristics are very much significant to validate its role in the PEM fuel cell stack. The measuring instrument play a significant role in maximizing the efficiency and durability of the PEM fuel cell stack components; because it is impossible to control the operating parameters without proper measurement. However, the measurement strategies involved in the GDE components is highly complex due to the non-linear behaviour during the PEM fuel cell operation. In the present paper, a holistic insight on all these measurement instruments and related challenges will be comprehensively dealt.
Figure 1: A plan of PEMFC single cell, indicating electron and ion transfer
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