For efficient operation, as well as to avoid operating conditions that can cause damage, fuel cells require a control system to balance fuel and air supply and electrical load. The need to maintain signal constraints during operation, combined with importance of unmeasured variables such as internal stack temperature or fuel utilization, indicate the need for control-oriented models that can be used for estimation and model predictive control. In this paper, we discuss the development of a control-oriented dynamic model of a solid oxide fuel cell stack. Using a detailed physical model as a starting point, we demonstrate the utility of a linear parameter varying (LPV) model structure as a mechanism for model reduction. A novel feature is a non-parametric method for determining the scheduling functions in this model.

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