We use a mathematical model of a solid oxide fuel cell (SOFC) unit for stress analyses. The model comprises a thermoelectrochemical-chemical performance model that calculates the temperature field in the solid part which is then used as input for the thermo-mechanical stress model. The level of detail allow system analyses with computational efficiency. Displacement is used as primary variable for stress calculations and thermo-mechanical failure probabilities. The operation envelope of the SOFC unit is defined through design and operational constraints. The applied multi-physics approach combines the disciplines of process design, material science as well as control engineering, and also emphasises the importance of using advanced mathematical modeling and simulation techniques to address problems of practical relevance.
We investigate failure incidents of a solid oxide fuel cell (SOFC) system during start-up from ambient conditions as well as during operation around the design point, using numerical simulation with a view to performance and thermo-mechanical stresses. During start-up, which comprises heating and load ramping phases, the system's trajectory moves through a relatively large temperature range. The simulated failure scenarios include reversible operational discontinuities in terms of input parameters and irreversible hardware failures. Furthermore, we also present results for a complete power cut. A multiphysics modeling approach is used to couple thermal, electrochemical, chemical, and thermo-mechanical phenomena by means of time-dependent partial differential, algebraic, and integral equations. Simulations revealed that the system can smooth out thermal discontinuities that are within a few minutes, that is, within the range of its thermal inertia. However, during the initial phase of the start-up procedure, thermo-mechanical stresses are relatively high due to larger differences between the sintering (manufacturing) and operation temperature, which makes the system more susceptible to failure. This work demonstrates that a multiphysics approach with control-and reliability-relevant aspects leads to a realistic problem formulation and analysis for practical applications.
PurposeA reliability analysis of a solid oxide fuel cell (SOFC) system is presented for applications with strict constant power supply requirements, such as data centers. The purpose is to demonstrate the effect when moving from a module-level to a system-level in terms of reliability, also considering effects during start-up and degradation.Design/methodology/approachIn-house experimental data on a system-level are used to capture the behavior during start-up and normal operation, including drifts of the operation point due to degradation. The system is assumed to allow replacement of stacks during operation, but a minimum number of stacks in operation is needed to avoid complete shutdown. Experimental data are used in conjunction with a physics-based performance model to construct the failure probability function. A dynamic program then solves the optimization problem in terms of time and replacement requirements to minimize the total negative deviation from a given target reliability.FindingsResults show that multi-stack SOFC systems face challenges which are only revealed on a system- and not on a module-level. The main finding is that the reliability of multi-stack SOFC systems is not sufficient to serve as sole power source for critical applications such as data center.Practical implicationsThe principal methodology may be applicable to other modular systems which include multiple critical components (of the same kind). These systems comprise other electrochemical systems such as further fuel cell types.Originality/valueThe novelty of this work is the combination of mathematical modeling to solve a real-world problem, rather than assuming idealized input which lead to more benign system conditions. Furthermore, the necessity to use a mathematical model, which captures sufficient physics of the SOFC system as well as stochasticity elements of its environment, is of critical importance. Some simplifications are, however, necessary because the use of a detailed model directly in the dynamic program would have led to a combinatorial explosion of the numerical solution space.
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