|
| Title: | A reduced-order model of a solid oxide fuel cell stack for model predictive control | | | Authors: | L. van Biert, P. Segovia Castillo, A. Haseltalab, R.R. Negenborn |
| | Conference: | International Ship Control Systems Symposium 2022 (ISCSS 2022) | | Address: | Delft, The Netherlands | | Date: | November 2022 |
| | Abstract: | The maritime industry is actively exploring alternative fuels and drivetrain 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. Another challenge is the slow response to load transients. This is a result of conservative thermal management strategies needed to avoid excessive thermal stresses in the stack. Model predictive control may be used to enhance transient load response while ensuring sufficient thermal management, but require models that can be evaluated in real-time. Therefore, a reduced-order SOFC stack model is developed in this work and verified with a high fidelity model from previous work. In addition, a preliminary framework is provided for its application in model predictive control. 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. |
| | Reference: | A reduced-order model of a solid oxide fuel cell stack for model predictive control. L. van Biert, P. Segovia Castillo, A. Haseltalab, R.R. Negenborn. Accepted for the International Ship Control Systems Symposium 2022 (ISCSS 2022), Delft, The Netherlands, November 2022. | | | Request: | A
copy of this publication. |
|
|
