Model predictive control to ensure high quality hydrogen production for fuel cells

In this work, a conventional plant wide control of a hydrogen production process from bioethanol is analyzed. The objective is to determine if the carbon monoxide (CO), in the produced hydrogen, exceeds the Proton Exchange Membrane Fuel Cell quality requirement of 10 ppm. Commercial sensors that meet those process conditions at high temperature are not easily available. Then, the development of two soft sensors, based on neural network, for online estimation of CO concentration in the H2 stream is presented. Higher CO concentration than allowed is detected in the fuel cell feeding. Strong interaction effects among the control loops around the last reactor, are found. Based on this, two model predictive control technologies are tested and compared in this interacted zone, in order to improve the disturbance rejection and satisfy the H2 expected quality. An exigent disturbance profile was used for simulating dynamically the complete process behavior.

[1]  Douglas J. Cooper,et al.  A novel tuning strategy for multivariable model predictive control , 1997 .

[2]  David Zumoffen,et al.  A New Systematic Approach to Fi nd Plantwide Control Structures , 2009 .

[3]  Minggao Ouyang,et al.  Modeling and control of air stream and hydrogen flow with recirculation in a PEM fuel cell system - II. Linear and adaptive nonlinear control , 2006 .

[4]  E. Bristol.  On a new measure of interaction for multivariable process control , 1966 .

[5]  Mohammad Bagher Menhaj,et al.  Training feedforward networks with the Marquardt algorithm , 1994, IEEE Trans. Neural Networks.

[6]  Marta Basualdo,et al.  A rigorous computational model for hydrogen production from bio-ethanol to feed a fuel cell stack , 2012 .

[7]  Michel Cabassud,et al.  Predictive functional control for the temperature control of a chemical batch reactor , 2006, Comput. Chem. Eng..

[8]  Tien Ho,et al.  An investigation of engine performance parameters and artificial intelligent emission prediction of hydrogen powered car , 2008 .

[9]  Kevin W. Kirby,et al.  Detection of low level carbon monoxide in hydrogen-rich gas streams , 2003 .

[10]  Philippe Poignet,et al.  Predictive functional control of a parallel robot , 2005 .

[11]  David Zumoffen,et al.  Plant-wide control design for fuel processor system with PEMFC , 2012 .

[12]  M. Ternan,et al.  Experimental and modelling studies of CO poisoning in PEM fuel cells , 2007 .

[13]  D. A. R. Zumoffen,et al.  Decentralized plantwide control strategy for large-scale processes. Case study: Pulp mill benchmark problem , 2013, Comput. Chem. Eng..

[14]  Daniel Eduardo Rivera Flores.  UNA METODOLOGÍA PARA LA IDENTIFICACIÓN INTEGRADA CON EL DISEÑO DE CONTROLADORES IMC-PID , 2007 .

[15]  Donal O'Donovan,et al.  Predictive Functional Control: Principles and Industrial Applications , 2009 .

[16]  Thomas F. Edgar,et al.  Process Dynamics and Control , 1989 .

[17]  David Zumoffen,et al.  Optimal Sensor Location for Chemical Process Accounting the Best Control Configuration , 2009 .

[18]  M. Basualdo,et al.  Analysis of the control structures for an integrated ethanol processor for proton exchange membrane fuel cell systems , 2009 .

[19]  Carlos Ocampo-Martinez,et al.  Design of optimization-based controllers applied to an ethanol steam reformer for hydrogen production , 2012 .

[20]  Alex Arenas,et al.  Neural virtual sensor for the inferential prediction of product quality from process variables , 2002 .

[21]  Soteris A. Kalogirou,et al.  Artificial neural networks in renewable energy systems applications: a review , 2001 .

[22]  Abdellatif Miraoui,et al.  Methanol fuel processor and PEM fuel cell modeling for mobile application , 2010 .

[23]  Saleh M. Al-Alawi,et al.  Predictive control of an integrated PV-diesel water and power supply system using an artificial neural network , 2007 .

[24]  M. Soroush,et al.  Model Predictive Control Tuning Methods: A Review , 2010 .

[25]  J. Ackermann,et al.  Analysis and Design , 1993 .

[26]  Carlos Bordons,et al.  Real-Time Implementation of a Constrained MPC for Efficient Airflow Control in a PEM Fuel Cell , 2010, IEEE Transactions on Industrial Electronics.

[27]  Carlos Bordons,et al.  Design and experimental validation of a constrained MPC for the air feed of a fuel cell , 2009 .

[28]  C. E. Thomas.  Transportation options in a carbon-constrained world: Hybrids, plug-in hybrids, biofuels, fuel cell electric vehicles, and battery electric vehicles , 2009 .

[29]  M. A. Laborde,et al.  Hydrogen production by the steam reforming of ethanol: Thermodynamic analysis , 1991 .

[30]  S. Joe Qin,et al.  A survey of industrial model predictive control technology , 2003 .

[31]  Jay H. Lee,et al.  Model predictive control: past, present and future , 1999 .

[32]  David Zumoffen,et al.  Testing PFC Controller On A Well Validated In Silico Model of a Type I Diabetic Patient , 2010 .

[33]  Diego Feroldi,et al.  Performance improvement of a PEMFC system controlling the cathode outlet air flow , 2007 .

[34]  Alireza Behroozsarand,et al.  Application of artificial neural networks (ANN) for modeling of industrial hydrogen plant , 2013 .

[35]  M. A. Abdelghani-Idrissi,et al.  Predictive functional control of a counter current heat exchanger using convexity property , 2001 .

[36]  Eduardo López,et al.  Dynamic modeling and controllability analysis of an ethanol reformer for fuel cell application , 2010 .

[37]  Wai Kean Yap,et al.  Exhaust emissions control and engine parameters optimization using artificial neural network virtual sensors for a hydrogen-powered vehicle , 2012 .

[38]  J. Pukrushpan.  Modeling and control of fuel cell systems and fuel processors , 2003 .

[39]  David Zumoffen,et al.  Plant-wide control strategy applied to the Tennessee Eastman process at two operating points , 2011, Comput. Chem. Eng..

[40]  V. Gnazzo,et al.  Glyphosate-based herbicides produce teratogenic effects on vertebrates by impairing retinoic acid signaling. , 2010, Chemical research in toxicology.

[41]  M. Altieri.  Los impactos ecológicos de los sistemas de producción de biocombustibles a base de monocultivos a gran escala en América , 2009 .

[42]  Jordi Llorca,et al.  Design of linear controllers applied to an ethanol steam reformer for PEM fuel cell applications , 2013 .

[43]  Ian Postlethwaite,et al.  Multivariable Feedback Control: Analysis and Design , 1996 .