Multiple model predictive control for oxygen starvation prevention of fuel cell system

2012 ◽  
Author(s):  
Xuelan Chen ◽  
Hongye Su ◽  
Bo Zhang ◽  
Xiuliang Li ◽  
Zhixing Cao
Keyword(s):  
Fuel Cell ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Cell System ◽  
Multiple Model ◽  
Fuel Cell System ◽  
Oxygen Starvation

On-line nonlinear model predictive control of a PEM fuel cell system

2013 ◽  
Vol 23 (4) ◽  
pp. 483-492 ◽  
Author(s):  
Chrysovalantou Ziogou ◽  
Simira Papadopoulou ◽  
Michael C. Georgiadis ◽  
Spyros Voutetakis
Keyword(s):  
Fuel Cell ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Nonlinear Model ◽  
Pem Fuel Cell ◽  
Cell System ◽  
Nonlinear Model Predictive Control ◽  
Fuel Cell System ◽  
On Line

scholarly journals High-Performance Tracking for Proton Exchange Membrane Fuel Cell System PEMFC Using Model Predictive Control

Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1158
Author(s):  
Mohamed Derbeli ◽  
Asma Charaabi ◽  
Oscar Barambones ◽  
Cristian Napole
Keyword(s):  
Fuel Cell ◽  
Model Predictive Control ◽  
Predictive Control ◽  
High Performance ◽  
Proton Exchange Membrane ◽  
Cell System ◽  
Proton Exchange ◽  
Fuel Cell System ◽  
Performance Tracking ◽  
Exchange Membrane

Proton exchange membrane (PEM) fuel cell has recently attracted broad attention from many researchers due to its cleanliness, high efficiency and soundless operation. The obtention of high-performance output characteristics is required to overcome the market restrictions of the PEMFC technologies. Therefore, the main aim of this work is to maintain the system operating point at an adequate and efficient power stage with high-performance tracking. To this end, a model predictive control (MPC) based on a global minimum cost function for a two-step horizon was designed and implemented in a boost converter integrated with a fuel cell system. An experimental comparative study has been investigated between the MPC and a PI controller to reveal the merits of the proposed technique. Comparative results have indicated that a reduction of 15.65% and 86.9%, respectively, in the overshoot and response time could be achieved using the suggested control structure.

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