PEM fuel cell modeling and simulation via the Takagi-Sugeno Fuzzy model

Abstract

International audienceIn this paper, a dynamic model of the PEMFC(polyelectrolyte membrane fuel cell) based on physical principles is built, in the form of a nonlinear statespace model. The Fuel Cell System (FCS) is a nonlinear system which is characterized by multiple variables and a strong coupling with profound dynamics. Therefore, it is difficult to apply control theory methods. For this reason, we have approximated the model of FCS by a Takagi-Sugeno Fuzzy model with fuzzy defined regions where the nonlinear system is locally linearized. The dynamics considered are: air compressor, supply and return manifold, anode and cathode flow, humidifier, cooler and stack voltage. Simulation results show that nonlinear system of PEM fuel cell can be approximated by a TS fuzzy model based on nonlinear sectors. The simulations show also that the supply and return manifold pressures and temperatures have significant effects on the dynamics of the PEMFC

PEM fuel cell fault diagnosis via a hybrid methodology based on fuzzy and pattern recognition techniques

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Robust fault diagnosis of proton exchange membrane fuel cells using a Takagi-Sugeno interval observer approach

“…Recently, the complex and non-linear dynamics of the power generation systems based on fuel cell technology, described in detail in [14], led to the use of linear models that include parameters varying with the operating point (known as linear parameter varying or LPV models) not only for advanced control [17] but also for model-based fault diagnosis [18] purposes. The use of Takagi-Sugeno (TS) models [19] is an alternative to LPV models as a linearlike modeling framework that allows extending control [20] and FDI methods to non-linear systems [21]. Thus, this paper will consider TS models and observers for FDI in PEM fuel cells.…”

Fault tolerant control of a proton exchange membrane fuel cell using Takagi–Sugeno virtual actuators

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