Abstract
For fuel cell system, linear models cannot provide essential information of the system performance since the nonlinear and time-varying behaviors cannot be ignored. Moreover, the detailed knowledge of the fuel cell structure may not be available. Besides, the detailed model of the fuel cell is complex to be useful for control design. To enhance the model accuracy for the control-oriented nonlinear model, the model identification method can be applied to tune the dominating structural model errors. However, the nonlinearity leads to some difficulties of obtaining transfer functions and state-space equations through the simple linear model identification method. Motivated by this fact, the nonlinear system identification is mainly considered in order to understand how the fuel cell system works and to deal with tuning the dominating structural model errors.
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Xing, Y. (2023). Model Tuning and Validation. In: Modeling and Control Strategies for a Fuel Cell System. Springer Theses. Springer, Cham. https://doi.org/10.1007/978-3-031-15112-5_3
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DOI: https://doi.org/10.1007/978-3-031-15112-5_3
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