Development of mathematical transfer functions correlating Solid Oxide Fuel Cell degradation to operating conditions for Accelerated Stress Test protocols design

Abstract

This work presents an innovative model-based approach for the development of mathematical transfer functions capable of correlating Solid Oxide Fuel Cells (SOFCs) degradation rate to the applied operating conditions. Such functions can be used for fuel cell lifetime prediction and Accelerated Stress Test (AST) protocols design. The proposed approach relies on multiscale modelling methodology and links local degradation to high level performance models to evaluate the key operating variables accelerating voltage decay over time. A thorough simulation analysis is performed to convey the correlation among operating variables and degradation rate into mathematical transfer functions. To better illustrate the overall design and application process of such functions, a case study accounting for Ni agglomeration is addressed. The multiscale modelling framework is applied to correlate microscale (i.e., Ni particles size change) and macroscale (i.e., SOFC voltage reduction) levels through the most affected mesoscale parameters. The model is then used to simulate voltage decay over time and link degradation rates to the applied operating conditions. Afterwards, a parametric analysis is performed to investigate the influence exerted by each operating variable on the degradation rate and derive the transfer functions. An example of application for Accelerated Stress Test (AST) protocols design is then given.