SciELO - Scientific Electronic Library Online

 
vol.19 issue37Spectral analysis through filter banks aplied to preprocessing oriented to thresholding of pulse oximetry signalAC transmission network expansion planning considering circuits repowering and location of capacitors author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

Related links

  • On index processCited by Google
  • Have no similar articlesSimilars in SciELO
  • On index processSimilars in Google

Share


TecnoLógicas

Print version ISSN 0123-7799On-line version ISSN 2256-5337

Abstract

RIOS, Richard; RAMOS-PAJA, Carlos A.  and  ESPINOSA, Jairo J.. A control system for reducing the hydrogen consumption of PEM fuel cells under parametric uncertainties. TecnoL. [online]. 2016, vol.19, n.37, pp.45-59. ISSN 0123-7799.

This paper presents a control system for reducing the hydrogen consumption for a Polymer Electrolyte Membrane fuel cell, also considering parametric uncertainties. The control system is based on a non-linear state space model of the fuel cell, a Kalman filter/estimator, a linear state feedback controller and a Maximum Power Point (MPP) tracking algorithm. The control objective is to supply the requested load power, avoiding oxygen starvation with minimum fuel consumption using a Perturb and Observe (P&O) algorithm. The performance of the control system was assessed under parametric uncertainties by simulating a performance degradation of the compressor due to aging. Thus, two cases were simulated: first, a mismatch between the system and the linear model in the (open-loop) air compressor gain; and second, a mismatch between the system and the linear model in the current compressor and losses. The simulation results showed that the Kalman filter/estimator overcome the uncertainties produced by the parametrical variations. Besides, the P&O algorithm accomplished to provide the suitable compressor voltage without identifying an optimal profile under ideal operating conditions and empirical data.

Keywords : .

        · abstract in Spanish     · text in Spanish     · Spanish ( pdf )

 

Creative Commons License All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License