A multi-objective optimisation model for a general polymer electrolyte membrane fuel cell system

This paper presents an optimisation model for a general polymer electrolyte membrane (PEM) fuel cell system Suitable for efficiency and size trade-offs investigation. Simulation of the model for a base case shows that for a given output power, a more efficient system is bigger and vice versa. Using the weighting method to perform a multi-objective optimisation, the Pareto sets were generated for different stack output powers. A Pareto set, presented as a plot of the optimal efficiency and area of the membrane electrode assembly (MEA), gives a quantitative description of the compromise between efficiency and size. Overall, our results indicate that, to make the most of the size-efficiency trade-off behaviour, the system must be operated at an efficiency of at least 40% but not more than 47%. Furthermore, the MEA area should be at least 3 cm(2) W-1 for the efficiency to be practically useful. Subject to the constraints imposed on the model, which are based on technical practicalities, a PEM fuel cell system such as the one presented in this work cannot operate at an efficiency above 54%. The results of this work, specifically the multi-objective model, will form a useful and practical basis for subsequent techno-economic studies for specific applications. (C) 2009 Elsevier B.V. All rights reserved

On the origin and application of the Bruggeman correlation for analysing transport phenomena in electrochemical systems

The widely used Bruggeman equations correlate tortuosity factors of porous media with their porosity. Finding diverse application from optics to bubble formation, it received considerable attention in fuel cell and battery research, recently. The ability to estimate tortuous mass transport resistance based on porosity alone is attractive, because direct access to the tortuosity factors is notoriously difficult. The correlation, however, has limitations, which are not widely appreciated owing to the limited accessibility of the original manuscript. We retrace Bruggeman's derivation, together with its initial assumptions, and comment on validity and limitations apparent from the original work to offer some guidance on its use

X-ray attenuation properties of commonly employed solid oxide fuel cell materials

X-ray nano CT has been vastly applied to study the microstructure of solid oxide fuel cell (SOFC) electrodes. One widely accepted indicator of electrochemical performance is the triple phase boundary (TPB): a location where the three materials responsible for ionic, electronic and gas-phase reactant transport are in contact. X-ray absorption tomography has been used extensively in the characterisation of these TPBs, utilising the different attenuation properties of the constituent materials. Here we present a quantitative comparison of the attenuation properties for elements commonly employed in solid oxide fuel cell materials

Tortuosity in electrochemical devices: a review of calculation approaches

The tortuosity of a structure plays a vital role in the transport of mass and charge in electrochemical devices. Concentration polarisation losses at high current densities are caused by mass transport limitations and are thus a function of microstructural characteristics. As tortuosity is notoriously difficult to ascertain, a wide and diverse range of methods have been developed to extract the tortuosity of a structure. These methods differ significantly in terms of calculation approach and data preparation techniques. Here, a review of tortuosity calculation procedures applied in the field of electrochemical devices is presented to better understand the resulting values presented in the literature. Visible differences between calculation methods are observed, especially when using porosity–tortuosity relationships and when comparing geometric and flux-based tortuosity calculation approaches

Machine learning as an online diagnostic tool for proton exchange membrane fuel cells

Proton exchange membrane fuel cells are considered a promising power supply system with high efficiency and zero emissions. They typically work within a relatively narrow range of temperature and humidity to achieve optimal performance; however, this makes the system difficult to control, leading to faults and accelerated degradation. Two main approaches can be used for diagnosis, limited data input which provides an unintrusive, rapid but limited analysis, or advanced characterisation that provides a more accurate diagnosis but often requires invasive or slow measurements. To provide an accurate diagnosis with rapid data acquisition, machine learning methods have shown great potential. However, there is a broad approach to the diagnostic algorithms and signals used in the field. This article provides a critical view of the current approaches and suggests recommendations for future methodologies of machine learning in fuel cell diagnostic applications

Progress and Perspectives of Organosulfur for Lithium-Sulfur Batteries

Lithium–sulfur batteries (LSBs) with high theoretical capacity are regarded as the most promising candidates for next-generation energy storage systems. However, the low conductivity, high volume change, and shuttle effect need to be addressed before the commercialization of LSBs. Organosulfur with covalent CS bonds can solve these problems when applied as different components of LSBs. Recent advances of application of organosulfur as cathodes, electrolytes, interlayers, and binders in LSBs are reviewed. Finally, the prospects for organosulfur are proposed from both the perspectives of mechanism understanding and practical applications

Understanding transport phenomena in electrochemical energy devices via X-ray nano CT

Porous support layers in electrochemical devices ensure mechanical stability of membrane assemblies such as solid oxide fuel cells and oxygen transport membranes (OTMs). At the same time, porous layers affect diffusive mass transport of gaseous reactants and contribute to performance losses at high fuel utilisation and conversion ratios. Microstructural characteristics are vital to calculate mass transport phenomena, where tortuosity remains notoriously difficult to determine. Here, the tortuosity of tubular porous support layers of OTMs is evaluated via high resolution X-ray nano computed tomography. The high resolution reveals the complex microstructure of the samples to then execute a selection of image-based tortuosity calculation algorithms. Visible differences between geometric and flux-based algorithms are observed and have thus to be applied with caution

Life cycle assessment of a polymer electrolyte membrane fuel cell system for passenger vehicles

In moving towards a more sustainable society, hydrogen fueled polymer electrolyte membrane (PEM) fuel cell technology is seen as a great opportunity to reduce the environmental impact of the transport sector. However, decision makers have the challenge of understanding the real environmental consequences of producing fuel cell vehicles (FCVs) compared to alternative green cars, such as battery electric vehicles (BEVs). and more conventional internal combustion engine vehicles (ICEVs). In this work, we presented a comprehensive life cycle assessment (LCA) of a FCV focused on its manufacturing phase and compared with the production of a BEV and an ICEV. For the manufacturing phase, the FCV inventories started from the catalyst layer to the glider, including the hydrogen tank. A sensitivity analysis on some of the key components of the fuel cell stack and the FC system (such as balance-of-plant and hydrogen tank) was carried out to account for different assumptions on materials and inventory models. The production process of the fuel cell vehicle showed a higher environmental impact compared to the production of the other two vehicles power sources. This is mainly due to the hydrogen tank and the fuel cell stack. However, by combining the results of the sensitivity analysis for each component - a best-case scenario showed that there is the potential for a 25% reduction in the climate change impact category for the FCV compared to a baseline FCV scenario. Reducing the environmental impact associated with the manufacture of fuel cell vehicles represents an important challenge. The entire life cycle has also been considered and the manufacturing, use and disposal of FCV, electric vehicle and conventional diesel vehicle were compared. Overall, the ICEV showed the highest GWP and this was mainly due to the use phase and the fossil carbon emissions associated to the use of diesel