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- W2510033915 abstract "Polymer electrolyte membrane (PEM) fuel cell (FC) systems convert chemical energy from hydrogen into electrical energy via a reaction with oxygen. FCs are highly efficient, nearly noiseless, and locally emission-free. An efficient and safe operation demands several variables in certain ranges. However, the electrical characteristic of a FC systems shows a nonlinear behavior and an exact control of the electrical power using a model-based approach requires an accurate model. Due to assumptions and simplifications the model differs from the plant which leads to steady state errors. This paper deals with offset-free Nonlinear Model Predictive Control (NMPC) of electrical power of a PEMFC using an Extended Kalman Filter (EKF). The NMPC allows direct use of nonlinear models with respect to constraints whereas an EKF allows a model correction and thus an exact control without steady state error. All experiments were verified on a test bench with a 4.4kW PEMFC." @default.
- W2510033915 created "2016-09-16" @default.
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- W2510033915 date "2016-06-01" @default.
- W2510033915 modified "2023-09-25" @default.
- W2510033915 title "Offset-free nonlinear model predictive control of electrical power of a PEM fuel cell system using an Extended Kalman Filter" @default.
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- W2510033915 doi "https://doi.org/10.1109/med.2016.7535896" @default.
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