Performance indicators for the dynamics modeling and control of PEMFC systems

Society is gradually becoming aware that the current energy industry, based on the use of fossil fuels, is inefficient, highly polluting and has a finite supply. Within the scientific community, there are indications that hydrogen (H2) as an energy vector, obtained from renewable energy sources, can represent a viable option to mitigate the problems associated with hydrocarbon combustion. In this context, the change from the current energy industry to a new structure with a significant involvement of H2 facilitates the introduction of fuel cells as elements of energy conversion. Polymer Electrolyte Membrane Fuel Cells (PEMFC) are gaining increased attention as viable energy conversion devices for a wide range of applications from automotive, stationary to portable. In order to optimize performance, these systems require active control and thus in-depth knowledge of the system dynamics which include fluid mechanics, thermal dynamics and reaction kinetics. One of the main issues, with respect to proper control of these systems, is the understanding of the water transport mechanisms through the membrane and the liquid water distribution. The thesis is based on the publication of nine international journal articles that are divided into 4 sub-topics: Dynamic fuel cell modeling, fuel cell system control-oriented analysis, identification of parameters and performance indicators and finally, fault and failure detection and system diagnosis. In the sub-topic of Dynamic Fuel cell modeling, experimentally validated Computational Fluid Dynamics (CFD) modeling is used to relate the effects of the physical phenomena associated with fluid mechanics and thermal dynamics, that occur inside the fuel cell [Alonso, 2009][Strahl, 2011], to water distribution. However, since these CFD models cannot be directly used for control, control-oriented models [Kunusch, 2008][Kunusch, 2011] have been developed in parallel. As well, another study is done in [Serra, 2006] which includes a controllability analysis of the system for future development and application of efficient controllers. The results of the above mentioned studies are limited because either they do not incorporate an electrochemical model or the model is not experimentally validated. Moreover, these models do not take into account the voltage losses due to liquid water inside the fuel cell. Therefore, there is a need to properly relate the relevant effects of fluid mechanics and thermal dynamics, including liquid water, to the fuel cell voltage. Primarily, methodologies are needed to determine the relevant indicators associated to the effect of water on the fuel cell performance. The works published in [Husar, 2008] and [Husar, 2011] treats experimental parameter identification, mainly focused on water transport through the membrane and fuel cell voltage loss indicators respectively. The implementation of the indicators indirect measurement methodology provides an experimental way for the isolation of three main types of voltage losses in the fuel cell: activation, mass transport and ohmic losses. Additionally since these voltage loss indicators relate the fuel cell operating conditions to the fuel cell voltage, they can be utilized to calibrate and validate CFD models as well as employed in novel control strategies. On the other hand, to develop reliable systems, the controller should not only take into account performance variables during standard operation but should also be able to detect failures and take the appropriate actions. A preliminary study on failure indicators is presented in [Husar 2007] and fault detection methodologies are described in [de Lira 2011]. As a whole, the compilation of articles represented in this thesis applies a comprehensive experimental approach which describes the implementation of novel methodologies and experimental procedures to characterize and model the PEMFC and their associated systems taking into consideration control oriented goals.La societat s'està adonant que la indústria energètica actual, basada en l'ús de combustibles fòssils, és ineficient, molt contaminant i té un subministrament limitat. Dins de la comunitat científica, hi ha indicis que el hidrogen (H2) com vector energètic, obtingut a partir de fonts d'energia renovables, pot representar una opció viable per a mitigar els problemes associats amb la combustió d'hidrocarburs. En aquest context, el canvi de la indústria energètica actual a una nova estructura amb una important participació de el hidrogen exigeix la introducció de les piles de combustible com elements de conversió d'energia. Les piles de combustible de membrana polimèrica (PEMFC) estan tenint cada vegada més atenció com a dispositius viables de conversió d'energia per a una àmplia gamma d'aplicacions com automoció, estacionàries o portàtils. Amb la finalitat d'optimitzar el seu rendiment, les piles PEM requereixen un control actiu i per tant un coneixement profund de la dinàmica del sistema, que inclou la mecànica de fluids, la dinàmica tèrmica i la cinètica de les reaccions. Un dels temes principals relacionat amb el control adequat d'aquests sistemes és la comprensió dels mecanismes de transport d'aigua a través de la membrana i la distribució d'aigua líquida. Aquesta tesi es basa en nou articles publicats en revistes internacionals que es divideixen en 4 subtemes: la modelització dinàmica de piles de combustible, l'anàlisi orientada al control del sistema, la identificació de paràmetres i d’indicadors de funcionament i, finalment, la detecció de fallades i la diagnosi dels sistemes. En el sub-tema de la modelització dinàmica de piles PEM, la modelització basada en la Dinàmica de Fluids Computacional (CFD) amb validació experimental s'ha utilitzat per a relacionar els efectes dels fenòmens físics de la mecànica de fluids i de la dinàmica tèrmica que es produeixen dintre de la pila [Alonso, 2009] [ Strahl, 2011] amb la distribució d'aigua. No obstant això, com aquests models CFD no poden ser utilitzats directament per al control, s'han desenvolupat models orientats a control [Kunusch, 2008] [Kunusch, 2011] en paral·lel. A més, en un altre estudi [Serra, 2006] s'inclou una anàlisi de control·labilitat del sistema per al desenvolupament i aplicació futurs de controladors eficaços. Però els resultats dels estudis esmentats anteriorment són limitats, ja sigui perquè no incorporen un model electroquímic o bé perquè no han estat validats experimentalment. A més, cap dels models té en compte les pèrdues de tensió degudes a l'aigua líquida dins de la pila de combustible. Per tant, hi ha una necessitat de relacionar adequadament els efectes rellevants de la mecànica de fluids i de la dinàmica tèrmica, incloent l'aigua líquida, amb el voltatge de la pila de combustible. Principalment, són necessàries metodologies per a determinar els indicadors rellevants associats a aquest efecte de l'aigua sobre el rendiment de la pila de combustible. Els treballs publicats en [Husar, 2008] i [Husar, 2011] tracten la identificació experimental de paràmetres, centrada en el transport d'aigua a través de la membrana i els indicadors de pèrdua de tensió, respectivament. L'aplicació d'una proposta de metodologia de mesura indirecte dels indicadors permet l'aïllament dels tres tipus principals de pèrdues de voltatge en la pila de combustible: l'activació, el transport de massa i les pèrdues ohmiques. Aquests indicadors de pèrdua de tensió relacionen les condicions d'operació amb el voltatge de la pila de combustible i per tant poden ser utilitzats per a calibrar i validar models CFD, així com per a definir noves estratègies de control. D'altra banda, per a aconseguir sistemes fiables, el controlador no només ha de considerar els indicadors de funcionament de l'operació normal, sinó que també ha de detectar possibles fallades per a poder prendre les accions adequades en cas de fallada. Un estudi preliminar sobre indicadors de fallades es presenta en [Husar 2007] i una metodologia de detecció de fallades completa es descriu en [Lira de 2011]. En el seu conjunt, el compendi d'articles que formen aquesta tesi segueix un enfocament experimental i descriu la implementació de noves metodologies i procediments experimentals per a la caracterització i el modelatge de piles PEM i els sistemes associats amb objectius orientats al control eficient d'aquests sistemes.La sociedad se ésta dando cuenta de que la industria energética actual, basada en el uso de combustibles fósiles, es ineficiente, muy contaminante y tiene un suministro limitado. Dentro de la comunidad científica, hay indicios de que el hidrógeno (H2) como vector energético, obtenido a partir de fuentes de energía renovables, puede representar una opción viable para mitigar los problemas asociados con la combustión de hidrocarburos. En este contexto, el cambio de la industria energética actual a una nueva estructura con una importante participación de H2 exige la introducción de pilas de combustible como elementos de conversión de energía. Las pilas de combustible de membrana polimérica (PEMFC) están ganando cada vez más atención como dispositivos viables de conversión de energía para una amplia gama de aplicaciones como automoción, estacionarias o portátiles. Con el fin de optimizar su rendimiento, las pilas PEM requieren un control activo y por lo tanto un conocimiento profundo de la dinámica del sistema, que incluye la mecánica de fluidos, la dinámica térmica y la cinética de las reacciones. Uno de los temas principales relacionado con el control adecuado de estos sistemas, es la comprensión de los mecanismos de transporte de agua a través de la membrana y la distribución de agua líquida. Esta tesis se basa en la publicación de nueve artículos en revistas internacionales que se dividen en 4 sub-temas: el modelado dinámico de pilas de combustible, el análisis orientado a control del sistema, la identificación de parámetros e indicadores de desempeño y, por último, la detección de fallos y la diagnosis. En el sub-tema de la modelización dinámica de pilas PEM, el modelado basado en Dinámica de Fluidos Computacional (CFD) con validación experimental se ha utilizado para relacionar los efectos de los fenómenos físicos de la mecánica de fluidos y la dinámica térmica que se producen dentro de la pila [Alonso, 2009] [ Strahl, 2011] con la distribución de agua. Sin embargo, como estos modelos CFD no pueden ser utilizados directamente para el control, modelos orientados a control [Kunusch, 2008] [Kunusch, 2011] se han desarrollado en paralelo. Además, en otro estudio [Serra, 2006] se incluye un análisis de controlabilidad del sistema para el futuro desarrollo y aplicación de controladores eficaces. Pero los resultados de los estudios mencionados anteriormente son limitados, ya sea porque no incorporan un modelo electroquímico o bien porque no son validados experimentalmente. Además, ninguno de los modelos tiene en cuenta las pérdidas de tensión debidas al agua líquida dentro de la pila de combustible. Por lo tanto, hay una necesidad de relacionar adecuadamente los efectos relevantes de la mecánica de fluidos y la dinámica térmica, incluyendo el agua líquida, con la tensión de la pila de combustible. Principalmente, son necesarias metodologías para determinar los indicadores relevantes asociados al efecto del agua sobre el rendimiento de la pila de combustible. Los trabajos publicados en [Husar, 2008] y [Husar, 2011] tratan la identificación experimental de parámetros, centrada en el transporte de agua a través de la membrana y los indicadores de pérdida de tensió, respectivamente. La aplicación de una metodología propuesta de medición indirecta de los indicadores permite el aislamiento de los tres tipos principales de pérdidas de tensión en la pila de combustible: la activación, el transporte de masa y las pérdidas óhmicas. Éstos indicadores de pérdida de tensión relacionan las condiciones de operación con la tensión de la pila de combustible y por lo tanto pueden ser utilizados para calibrar y validar modelos CFD, así como para definir nuevas estrategias de control. Por otro lado, para conseguir sistemas fiables, el controlador no sólo debe considerar los indicadores de desempeño de la operación regular, sino que también debe detectar posibles fallos para poder tomar las acciones adecuadas en caso de fallo. Un estudio preliminar sobre indicadores de fallos se presenta en [Husar 2007] y una metodología de detección de fallos completa se describe en [Lira de 2011]. En su conjunto, el compendio de artículos que forman esta tesis sigue un enfoque experimental y describe la implementación de nuevas metodologías y procedimientos experimentales para la caracterización y el modelado de pilas PEM y los sistemas asociados con objetivos orientados al control eficiente de estos sistemas

SYSTEM IDENTIFICATION AND MODEL PREDICTIVE CONTROL FOR INTERACTING SERIES PROCESS WITH NONLINEAR DYNAMICS

This thesis discusses the empirical modeling using system identification technique and the implementation of a linear model predictive control with focus on interacting series processes. In general, a structure involving a series of systems occurs often in process plants that include processing sequences such as feed heat exchanger, chemical reactor, product cooling, and product separation. The study is carried out by experimental works using the gaseous pilot plant as the process. The gaseous pilot plant exhibits the typical dynamic of an interacting series process, where the strong interaction between upstream and downstream properties occurs in both ways. The subspace system identification method is used to estimate the linear model parameters. The developed model is designed to be robust against plant nonlinearities. The plant dynamics is first derived from mass and momentum balances of an ideal gas. To provide good estimations, two kinds of input signals are considered, and three methods are taken into account to determine the model order. Two model structures are examined. The model validation is conducted in open-loop and in closed-loop control system. Real-time implementation of a linear model predictive control is also studied. Rapid prototyping of such controller is developed using the available equipments and software tools. The study includes the tuning of the controller in a heuristic way and the strategy to combine two kinds of control algorithm in the control system. A simple set of guidelines for tuning the model predictive controller is proposed. Several important issues in the identification process and real-time implementation of model predictive control algorithm are also discussed. The proposed method has been successfully demonstrated on a pilot plant and a number of key results obtained in the development process are presented

Optimal air and fuel-path control of a diesel engine

The work reported in this thesis explores innovative control structures and controller design for a heavy duty Caterpillar C6.6 diesel engine. The aim of the work is not only to demonstrate the optimisation of engine performance in terms of fuel consumption, NOx and soot emissions, but also to explore ways to reduce lengthy calibration time and its associated high costs. The test engine is equipped with high pressure exhaust gas recirculation (EGR) and a variable geometry turbocharger (VGT). Consequently, there are two principal inputs in the air-path: EGR valve position and VGT vane position. The fuel injection system is common rail, with injectors electrically actuated and includes a multi-pulse injection mode. With two-pulse injection mode, there are as many as five control variables in the fuel-path needing to be adjusted for different engine operating conditions. [Continues.

Fault detection for the Benfield process using a closed-loop subspace re-identification approach

Closed-loop system identification and fault detection and isolation are the two fundamental building blocks of process monitoring. Efficient and accurate process monitoring increases plant availability and utilisation. This dissertation investigates a subspace system identification and fault detection methodology for the Benfield process, used by Sasol, Synfuels in Secunda, South Africa, to remove CO2 from CO2-rich tail gas. Subspace identification methods originated between system theory, geometry and numerical linear algebra which makes it a computationally efficient tool to estimate system parameters. Subspace identification methods are classified as Black-Box identification techniques, where it does not rely on a-priori process information and estimates the process model structure and order automatically. Typical subspace identification algorithms use non-parsimonious model formulation, with extra terms in the model that appear to be non-causal (stochastic noise components). These extra terms are included to conveniently perform subspace projection, but are the cause for inflated variance in the estimates, and partially responsible for the loss of closed-loop identifiably. The subspace identification methodology proposed in this dissertation incorporates two successive LQ decompositions to remove stochastic components and obtain state-space models of the plant respectively. The stability of the identified plant is further guaranteed by using the shift invariant property of the extended observability matrix by appending the shifted extended observability matrix by a block of zeros. It is shown that the spectral radius of the identified system matrices all lies within a unit boundary, when the system matrices are derived from the newly appended extended observability matrix. The proposed subspace identification methodology is validated and verified by re-identifying the Benfield process operating in closed-loop, with an RMPCT controller, using measured closed-loop process data. Models that have been identified from data measured from the Benfield process operating in closed-loop with an RMPCT controller produced validation data fits of 65% and higher. From residual analysis results, it was concluded that the proposed subspace identification method produce models that are accurate in predicting future outputs and represent a wide variety of process inputs. A parametric fault detection methodology is proposed that monitors the estimated system parameters as identified from the subspace identification methodology. The fault detection methodology is based on the monitoring of parameter discrepancies, where sporadic parameter deviations will be detected as faults. Extended Kalman filter theory is implemented to estimate system parameters, instead of system states, as new process data becomes readily available. The extended Kalman filter needs accurate initial parameter estimates and is thus periodically updated by the subspace identification methodology, as a new set of more accurate parameters have been identified. The proposed fault detection methodology is validated and verified by monitoring process behaviour of the Benfield process. Faults that were monitored for, and detected include foaming, flooding and sensor faults. Initial process parameters as identified from the subspace method can be tracked efficiently by using an extended Kalman filter. This enables the fault detection methodology to identify process parameter deviations, with a process parameter deviation sensitivity of 2% or higher. This means that a 2% parameter deviation will be detected which greatly enhances the fault detection efficiency and sensitivity.Dissertation (MEng)--University of Pretoria, 2008.Electrical, Electronic and Computer Engineeringunrestricte

SYSTEM IDENTIFICATION AND MODEL PREDICTIVE CONTROL FOR INTERACTING SERIES PROCESS WITH NONLINEAR DYNAMICS

This thesis discusses the empirical modeling using system identification technique and the implementation of a linear model predictive control with focus on interacting series processes. In general, a structure involving a series of systems occurs often in process plants that include processing sequences such as feed heat exchanger, chemical reactor, product cooling, and product separation. The study is carried out by experimental works using the gaseous pilot plant as the process. The gaseous pilot plant exhibits the typical dynamic of an interacting series process, where the strong interaction between upstream and downstream properties occurs in both ways. The subspace system identification method is used to estimate the linear model parameters. The developed model is designed to be robust against plant nonlinearities. The plant dynamics is first derived from mass and momentum balances of an ideal gas. To provide good estimations, two kinds of input signals are considered, and three methods are taken into account to determine the model order. Two model structures are examined. The model validation is conducted in open-loop and in closed-loop control system. Real-time implementation of a linear model predictive control is also studied. Rapid prototyping of such controller is developed using the available equipments and software tools. The study includes the tuning of the controller in a heuristic way and the strategy to combine two kinds of control algorithm in the control system. A simple set of guidelines for tuning the model predictive controller is proposed. Several important issues in the identification process and real-time implementation of model predictive control algorithm are also discussed. The proposed method has been successfully demonstrated on a pilot plant and a number of key results obtained in the development process are presented

Modeling, Analysis, and Control of a Mobile Robot for \u3ci\u3eIn Vivo\u3c/i\u3e Fluoroscopy of Human Joints during Natural Movements

In this dissertation, the modeling, analysis and control of a multi-degree of freedom (mdof) robotic fluoroscope was investigated. A prototype robotic fluoroscope exists, and consists of a 3 dof mobile platform with two 2 dof Cartesian manipulators mounted symmetrically on opposite sides of the platform. One Cartesian manipulator positions the x-ray generator and the other Cartesian manipulator positions the x-ray imaging device. The robotic fluoroscope is used to x-ray skeletal joints of interest of human subjects performing natural movement activities. In order to collect the data, the Cartesian manipulators must keep the x-ray generation and imaging devices accurately aligned while dynamically tracking the desired skeletal joint of interest. In addition to the joint tracking, this also requires the robotic platform to move along with the subject, allowing the manipulators to operate within their ranges of motion. A comprehensive dynamic model of the robotic fluoroscope prototype was created, incorporating the dynamic coupling of the system. Empirical data collected from an RGB-D camera were used to create a human kinematic model that can be used to simulate the joint of interest target dynamics. This model was incorporated into a computer simulation that was validated by comparing the simulation results with actual prototype experiments using the same human kinematic model inputs. The computer simulation was used in a comprehensive dynamic analysis of the prototype and in the development and evaluation of sensing, control, and signal processing approaches that optimize the subject and joint tracking performance characteristics. The modeling and simulation results were used to develop real-time control strategies, including decoupling techniques that reduce tracking error on the prototype. For a normal walking activity, the joint tracking error was less than 20 mm, and the subject tracking error was less than 140 mm