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Enhancing the efficiency and lifetime of a proton exchange membrane fuel cell using nonlinear model-predictive control with nonlinear observation

Author
Luna, J.; Usai, E.; Husar, A.; Serra, M.
Type of activity
Journal article
Journal
IEEE transactions on industrial electronics
Date of publication
2017-08-01
Volume
64
Number
8
First page
6649
Last page
6659
DOI
https://doi.org/10.1109/TIE.2017.2682787 Open in new window
Project funding
Innovative cost improvements for balance of plant components of automotive PEMFC systems
MICAPEM: Parameter estimation, diagnosis and control for the improvement of efficiency and durability of PEM fuel cells
Repository
http://hdl.handle.net/2117/116537 Open in new window
URL
http://ieeexplore.ieee.org/document/7880649/ Open in new window
Abstract
The aim of this research is to develop and test in a simulation environment an advanced model-based control solution for a proton exchange membrane fuel cell (PEMFC) system. A nonlinear model-predictive control (NMPC) strategy is proposed to maximize the active catalytic surface area at the cathode catalyst layer to increase the available reaction area of the stack and to avoid starvation at the catalyst sites. The PEMFC stack model includes a spatial discretization that permits the control stra...
Citation
Luna, J., Usai, E., Husar, A., Serra, M. Enhancing the efficiency and lifetime of a proton exchange membrane fuel cell using nonlinear model-predictive control with nonlinear observation. "IEEE transactions on industrial electronics", 1 Agost 2017, vol. 64, núm. 8, p. 6649-6659.
Keywords
Control nonlinearities, Degradation; electrochemically active surface area; nonlinear model-predictive control (NMPC); nonlinear observation; proton exchange membrane fuel cells (PEMFCs); starvation, degradation, electrochemically active surface area, nonlinear model predictive control, nonlinear observation, observability, power system control, predictive control, proton exchange membrane fuel cells, starvation
Group of research
CS2AC-UPC - Supervision, Safety and Automatic Control
SAC - Advanced Control Systems

Participants