Altmann, F. (2022). On multiphase flow and the dynamic temperature distribution in proton exchange membrane fuel cells [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2022.96214
E322 - Institut für Strömungsmechanik und Wärmeübertragung
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Date (published):
2022
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Number of Pages:
69
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Keywords:
Mehrskalenmodellierung; Spektralverfahren
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multi scale modeling; spectral methods
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Abstract:
Proton Exchange Membrane Fuel Cells (PEMFCs) are a promising alternative power source for mobile and stationary devices. Their dynamic operation, however, is still very challenging, since unmeant destructive states reduce durability and uncontrolled formation of liquid water in the porous electrodes affects fuel cell performance. The prediction of the spatio-temporal temperatureand gas distribution within the PEMFC is crucial in both cases. Therefore, a dynamic multiphase flow extension to the linearised in time (LIT) model by Murschenhofer, Kuzdas, Braun and Jakubek [Energy Conversion and Management 162, pp. 159-175 (2018)], is proposed in this work. For each domain the governing differential equations are derived from 3D integral conservation laws following a quasi-2D approach. Effects such as convective and diffusive transport of mass, heat and enthalpy, as well as heat generation by electrochemical half-reactions, finite proton conductivity in the membrane and phase change are considered.The non-isothermal single phase case of the model is further implemented in Matlab. Application of a Chebyshev spectral collocation method, linearisation of the nonlinear governing equations with respect to the previous time step, and using adaptive time stepping, assures fast computation. The extended model is validated in terms of predicted temperature distributions versus 3Dsteady-state simulations from existing literature. The dynamic thermal behavior due to prescribed steep time gradients in current density and relative humidity is found to be in good qualitative agreement with results published by other authors. With its very low computational cost, thepresented model is especially developed for comprehensive parameter studies, control unit adjustments or state predicitons.
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