Solid Oxide Fuel Cell (SOFC) has a high energy conversion efficiency and emits a low level of pollutants in the environment. One of the crucial elements is an anode which typically is a composite of nickel and yttria-stabilized zirconia (Ni-YSZ). The microstructure morphology of an anode plays a important role in determining the electrochemical performances of a single cell and consequently a stack of cells. Therefore, microstructure optimization design should be included in the development of a system at the very early stage. The anode material microstructure can be tailored to fulfill the role it has at the particular location in the stack. This paper presents a novel approach of using an evolutionary algorithm to optimize the microstructure of a solid oxide fuel cell’s anode. The optimization problem consists of sixteen microstructural parameters connected by the mesh of the dependencies. One group of algorithms that can face this challenge is an evolutionary algorithm family. In the presented paper a Genetic Algorithm and a Particle Swarm Optimization are employed to optimize cell microstructure and to help to improve the performance of a solid oxide fuel cell. The developed mathematical model can correctly predict the performance of the SOFC anode and is employed in the evolutionary algorithms to select the optimal microstructure. The results show that the optimal microstructure leads to the better cell performance than the conventional one.

The models of solid oxide fuel cells (SOFCs), which are available in the open literature, may be categorized into two non-overlapping groups: microscale or macroscale. Recent progress in computational power makes it possible to formulate a model which combines both approaches, the so-called multiscale model. The novelty of this modeling approach lies in the combination of the microscale description of the transport phenomena and electrochemical reactions’ with the computational fluid dynamics model of the heat and mass transfer in an SOFC. In this work, the mathematical model of a solid oxide fuel cell which takes into account the averaged microstructure parameters of electrodes is developed and tested. To gain experimental data, which are used to confirm the proposed model, the electrochemical tests and the direct observation of the microstructure with the use of the focused ion beam combined with the scanning electron microscope technique (FIB-SEM) were conducted. The numerical results are compared with the experimental data from the short stack examination and a fair agreement is found, which shows that the proposed model can predict the cell behavior accurately. The mechanism of the power generation inside the SOFC is discussed and it is found that the current is produced primarily near the electrolyte–electrode interface. Simulations with an artificially changed microstructure does not lead to the correct prediction of the cell characteristics, which indicates that the microstructure is a crucial factor in the solid oxide fuel cell modeling.

Plug-flow reactors are very common in methane/steam reforming applications. Their operation presents many challenges, such as a strong dependence on temperature and inlet composition distribution. The strong endothermic steam reforming reaction might result in a temperature drop at the inlet of the reactor. The strong non-uniform temperature distribution due to an endothermic chemical reaction can have tremendous consequences on the operation of the reactor, such as catalyst degradation, undesired side reactions and thermal stresses. One of the possibilities to avoid such unfavorable conditions and control thermal circumstances inside the reforming reactor is to use it as a fuel processor in the solid oxide fuel cell (SOFC) system. The heat generated by exothermic electrochemical SOFC reactions can support the endothermic reforming reaction. Furthermore, the thermal effects of electrochemical reactions help to shape the uniform temperature distribution. To examine thermal management issues, a detailed modeling and corresponding numerical analyses of the phenomena occurring inside the internal reforming system is required. This paper presents experimental and numerical studies on the methane/steam reforming process inside a plug-flow reactor. Measurements including different thermal boundary conditions, the fuel flow rate and the steam-to-methane ratios were performed. The reforming rate equation derived from experimental data was used in the numerical model to predict gas composition and temperature distribution along the steam reforming reactor. Finally, an attempt was made to control the temperature distribution by adopting locally controlled heating zones and non-uniform catalyst density distributions.