Prediction of SOFC Performance with or without Experiments: A Study on Minimum Requirements for Experimental Data

Thursday, 30 July 2015: 16:00
Lomond Auditorium (Scottish Exhibition and Conference Centre)
T. Yang, H. Sezer, I. B. Celik (MAE Department, West Virginia University, Morgantown WV, U.S. DOE, National Energy Technology Laboratory), H. O. Finklea (Chemistry Department, West Virginia University, USA, U.S. DOE, National Energy Technology Laboratory), and K. Gerdes (U.S. DOE, National Energy Technology Laboratory)
A comprehensive analysis of solid oxide fuel cells (SOFCs) should consider polarization curve and impedance behavior simultaneously, as well as the cell performances at different air/fuel utilization cases and operating conditions. In the present study, a physics based protocol, combining experiments and multi-physics numerical simulations, is developed for overall analysis of SOFCs operational diagnostics and performance predictions.  In this protocol, essential information for the fuel cell is extracted first by utilizing empirical polarization analysis in conjunction with experiments and refined by multi-physics numerical simulations via simultaneous analysis and calibration of polarization curve and impedance behavior. The performance at different utilization cases and operating currents is also predicted to confirm the accuracy of the proposed model.  Furthermore, we also propose the requirements to determine the cell properties and model parameters with less uncertainty. It is demonstrated that, with the present electrochemical model, three air/fuel flow conditions are needed to produce a set of complete data for better understanding of the processes occurring within SOFCs. The detailed calibration procedure and performance prediction at different conditions of button cells are presented. It is also demonstrated that the methodology can be used to assess performance of planar cell without further calibration. The proposed methodology would accelerate the calibration process and improve the efficiency of design and diagnostics analysis.