Optimizing Solid Oxide Fuel Cell Performance to Re-evaluate Its Role in the Mobility Sector.

A sustainable, interconnected, and smart energy network in which hydrogen plays a major role cannot be dismissed as a utopia anymore. There are vast international and industrial ambitions to reach the envisioned system transformation, and the decarbonization of the mobility sector is a central pillar comprising a huge economic share. Solid oxide fuel cells (SOFCs) are one of the most promising technologies in the brigade of clean energy devices and have potentially wide applicability for transportation, due to their high efficiencies and impurity tolerance. To uncover future pathways to boost the cell's performance, we propose a detailed multiscale modeling methodology to evaluate the direct impact of cell materials and morphologies on commercial-scale system performance. After acquiring intrinsic electrokinetics decoupled from mass and charge transport of different anode and cathode materials via a half-cell model, a full cell model is employed to identify the most promising electrode combination. Subsequently, a scale-up to the system level is performed by coupling a 3-D kW-stack model to the balance of plant components while focusing on morphological optimization of the membrane electrode assembly (MEA). On optimally tailoring the MEA, model results demonstrate that an advanced cell design comprising a Ni fiber-CGO matrix structured anode and a LSCF-infiltrated CGO cathode could reach a stack power density of 1.85 kW L and a net system efficiency of 52.2% for operation at <700 °C, with manageable stack temperature gradients of <14 K cm. The model-optimized power density is substantially higher than those of commercial stacks and surpasses industrial targets for SOFC-based range extenders. Thus, with further cell and stack development targeting the performance limiting processes elucidated in the paper, commercial SOFCs could, alongside range extenders, also act as prime movers in larger scale transport applications such as trucks, trains, and ships.