A reduced-order model of a solid oxide fuel cell stack for model predictive control

Abstract

The maritime industry is actively exploring alternative fuels and drive train technology to reduce the emissions of hazardous air pollutants and greenhouse gases. High temperature solid oxide fuel cells (SOFCs) represent a promising technology to generate electric power on ships from a variety of renewable fuels with high efficiencies and no hazardous emissions. However, application in ships is still impeded by a number of challenges, such as low power density and high capital cost. A slow response to load transients is another challenges, which is typically a result of the conservative thermal management strategies used to ensure that excessive thermal stresses in the stack are avoided. Therefore, a reduced order SOFC stack model is developed in this work for model-based control. The model is subsequently verified with a high fidelity model developed in previous work. In addition, a preliminary framework for its use for model predictive SOFC control is provided. The reduced order model and control framework will be used in future work to optimise thermal management of SOFC stacks for improved transient response while respecting physical and operational constraints.