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• Data driven method is used for Fuel Cell prognostics under a stationary load profile. • The parameters of the Echo State Network are optimized via an optimization algorithm. • Cycle repetetion and markov chains are used to generate the stationary load profile. • The remaining useful lifetime is estimated using the developed approach. • The prognostics performance is validated using experimental data. Improving Proton Exchange Membrane Fuel Cell durability is a key that paves the way to its large scale industrial deployment. During the last five years, the prognostics discipline emerged as an interesting field for Proton Exchange Membrane Fuel Cell state of health prediction and lifetime estimation. The information provided by the prognostic module is crucial for optimizing the control strategy to extend the fuel cell lifetime. In this paper, an approach based on Echo State Network for fuel cell prognostics under a variable load is developed. The novelty of this paper is to perform prognostics under a variable load profile without prior knowledge of this latter. Two solutions are developed in this work. The first one consists of evaluating the remaining useful lifetime under a repeated load cycle. The second one is based on using Markov chains to generate estimations of the future load profile, allowing thus to overcome the need of real future load profile prior knowledge. Both proposed solutions give accurate prediction results of proton exchange membrane fuel cell remaining useful lifetime, with low uncertainties. [ABSTRACT FROM AUTHOR]

Abstract: No abstract. [ABSTRACT FROM AUTHOR]

In this work, a nonlinear model predictive control (NMPC) strategy is proposed to improve the efficiency and enhance the durability of a proton exchange membrane fuel cell (PEMFC) power system. The PEMFC controller is based on a distributed parameters model that describes the nonlinear dynamics of the system, considering spatial variations along the gas channels. Parasitic power from different system auxiliaries is considered, including the main parasitic losses which are those of the compressor. A nonlinear observer is implemented, based on the discretised model of the PEMFC, to estimate the internal states. This information is included in the cost function of the controller to enhance the durability of the system by means of avoiding local starvation and inappropriate water vapour concentrations. Simulation results are presented to show the performance of the proposed controller over a given case study in an automotive application (New European Driving Cycle). With the aim of representing the most relevant phenomena that affects the PEMFC voltage, the simulation model includes a two-phase water model and the effects of liquid water on the catalyst active area. The control model is a simplified version that does not consider two-phase water dynamics. [ABSTRACT FROM AUTHOR]