NONLINEAR CONTROL DESIGN FOR SOLID OXIDE FUEL CELLS

Ever increasing energy consumption, rising public awareness for environmental protection and higher prices of fossil fuels have motivated many to look for renewable energy sources. SOFC is one of the best alternative energy source but it is a highly nonlinear system. One of the main goals of this research is designing a nonlinear control. In this thesis, non-isothermal model of solid oxide fuel cell has been developed under the general condition of unchoked outlet flow. For isothermal dynamic model of SOFC, a controller based on on full state feedback linearization is designed and compared with controller based on linearization and gain scheduling. Analysis of controllability and observability is also given for the nonlinear isothermal model

Parameter Estimation and Model Order Identification of LTI Systems

In this paper, a sparsity seeking optimization method for estimating the parameters along with the order of output error models of single-input and single output (SISO), linear time invariant (LH) system is proposed. It is demonstrated with the help of simulations that the proposed algorithm gives accurate parameter and order estimates on a variety of systems

Continuous Time Identification in Laplace Domain

We give a simple and accurate method for estimating the paramters of continuous time systems under the constraint that all the poles of the system lie to the left of the line s = -1. The method relies on the simple solution of a linear system of equations in the complex domain. We demonstrate by the use of simulation that the proposed methods gives accruate estimates when compared to existing methods. Methods for obtaining sparse solutions, which help in determining the order of the system are also give

Impedance Analysis of Polymer Electrolyte Membrane Fuel cell

Electrochemical Impedance Spectroscopy can be used as a diagnostic tool for fuel cells. In this thesis, a model based impedance analysis of Polymer Electrolyte Membrane Fuel cells is given. The impedance of Cathode Gas Diffusion Layer (GDL) and Cathod Catalyst Layer (CCL) is obtained using physical models from existing literature. The change in the oxygen concentraion at the GDL j CCL interface with respect to a perturbation in the current density is obtained from existing models and shown numerically. Similarly, the change in the activation overpotential at the CCL j membrane interface with respect to a perturbation in the current is again calculated from existing models and calculated numerically

A region growing method for detecting interfaces in X-ray view cell images

X-ray transmission videography is used to observe the thermodynamic phase behavior of heavy oil mixtures of industrial interest that are opaque to visible light. The knowledge of the volumes of various phases provide important information for enhancing oil refining technology. Phase boundaries are usually marked by visual examination based upon which the volumes and densities of the phases are computed. Typically, phase behavior is computed at various temperatures and pressures to generate the phase diagram. This paper presents an image processing algorithm, which automates the task of detecting phase boundaries in the generated images. The interface and region models are first obtained from the image generation process. Using these models, a new method for interface detection based on the Mumford-Shah model is presented. Results are presented to show that the algorithm detects the phase boundaries to subpixel accurac

On the existence of equivalence class of RIP-compliant matrices

In Compressed Sensing (CS), the matrices that satisfy the Restricted Isometry Property (RIP) play an important role. But it is known that the RIP properties of a matrix Φ and its `weighted matrix' GΦ (G being a non-singular matrix) vary drastically in terms of RIP constant. In this paper, we consider the opposite question: Given a matrix Φ, can we find a non-singular matrix G such that GΦ has compliance with RIP? We show that, under some conditions, a class of non-singular matrices (G) exists such that GΦ has RIP-compliance with better RIP constant. We also provide a relationship between the Unique Representation Property (URP) and Restricted Isometry Property (RIP), and a direct relationship between RIP and sparsest solution of a linear system of equations

Construction of Structured Incoherent Unit Norm Tight Frames

The exact recovery property of Basis pursuit (BP) and Orthogonal Matching Pursuit (OMP) has a relation with the coherence of the underlying frame. A frame with low coherence provides better guarantees for exact recovery. In particular, Incoherent Unit Norm Tight Frames (IUNTFs) play a significant role in sparse representations. IUNTFs with special structure, in particular those given by a union of several orthonormal bases, are known to satisfy better theoretical guarantees for recovering sparse signals. In the present work, we propose to construct structured IUNTFs consisting of large number of orthonormal bases. For a given r,k,m with k being less than or equal to the smallest prime power factor of m and r<k, we construct a CS matrix of size mk×(mk×mr) with coherence at most rk, which consists of mr number of orthonormal bases and with density 1m. We also present numerical results of recovery performance of union of orthonormal bases as against their Gaussian counterparts

State Estimation in Solid Oxide Fuel Cell(SOFC)System

Solid oxide fuel cells (SOFCs) oer a clean, low pollution technology to electrochemically generate electricity at high eciency. An SOFC consists of a dense solid electrolyte and two porous electrodes in contact with an interconnect on either side. The control of an SOFC stack becomes important in order to ensure adequate and disturbance free electric power. As several controlled/constrained variables are not directly measured in a stack, state estimators can be used in order to study the dynamic behaviour of SOFC stacks as well as to design eective SOFC controllers. In this thesis, A zero dimensional model represented by a set of ordinary dierential equations is derived for dynamic modeling. The model consists of molar balances and an energy balance coupled with a simplied description of the fuel cell electrochemistry. The chemical species considered are H2 and H2O for fuel side (anode side) and O2 and N2 for air side (cathode side) and the electrochemical model accounts for ohmic, concentration and activation losses. Considering the estimation part, the state vector which is to be estimated consists of partial pressure of chemical species and temperature, with voltage as the measurement. Estimation of states for linear systems can be done by Kalman Filter. States of nonlinear systems can be estimated using Extended Kalman Filter(EKF), Unscented Kalman Filter (UKF). We choose UKF for non linear state estimation. UKF is a derivative free state estimator for non linear systems. This work investigates the use of non linear state estimator UKF to estimate the states of SOFC system. This method can be applied to estimate states in any type of fuel cells (PEMFC, AFC etc.) by very slight modications

Composition of Binary Compressed Sensing Matrices

In the recent past, various methods have been proposed to construct deterministic compressed sensing (CS) matrices. Of interest has been the construction of binary sensing matrices as they are useful for multiplierless and faster dimensionality reduction. In most of these binary constructions, the matrix size depends on primes or their powers. In this study, we propose a composition rule which exploits sparsity and block structure of existing binary CS matrices to construct matrices of general size. We also show that these matrices satisfy optimal theoretical guarantees and have similar density compared to matrices obtained using Kronecker product. Simulation work shows that the synthesized matrices provide comparable results against Gaussian random matrices

A Distributed Parameter Model for a Solid Oxide Fuel Cell: Simulating Realistic Operating Conditions

We present a detailed multiphysics model capable of simulating the dyn amic behavior of a solid oxide fuel cell (SOFC). This model includes a description of a ll the important physical and chemical processes in a fuel cell: fluid flow, mass and heat trans fer, electronic and ionic potential fields, as well as the chemical and electrochemical react ions. The resulting highly nonlinear, coupled system of differential equations is solved using a fi nite volume discretization. Our interest lies in simulating realistic operating conditions with the obj ective of high efficiency operation at high fuel utilization. While there are a number of studies in the literature that present multiphysics models for SOFCs, few have focused on simulat ing operating conditions that are necessary if SOFC systems are to realize their promise of h igh efficiency conversion of chemical energy to electrical energy. In this report we present s imulation results at operating conditions that approach the required ranges of power density an d overall efficiency. Our results include a) the temperature and composition profiles along a typical f uel cell in a SOFC stack, b) the dynamic response of the cell to step changes in the available inpu t variables. Since models such as the one presented here are fairly expensive computationa lly and cannot be directly used for online model predictive control, one generally looks to use simplifie d reduced order models for control. We briefly discuss the implications of our model results o n the validity of using reduced models for the control of SOFC stacks to show that avoid ing operating regions where well-known degradation modes are activated is non-trivial without u sing detailed multiphysics models