A typical approach to the synthesis/design optimization of energy systems is to only use steady state operation and high efficiency (or low total life cycle cost) at full load as the basis for the synthesis/design. Transient operation as reflected by changes in power demand, shut-down, and start-up are left as secondary tasks to be solved by system and control engineers once the synthesis/design is fixed. However, transient regimes may happen quite often and the system response to them is a critical factor in determining the system's feasibility. Therefore, it is important to consider the system dynamics in the creative process of developing the system. A decomposition approach for dynamic optimization developed and applied to the synthesis/design and operation/control optimization of a solid oxide fuel cell (SOFC) based auxiliary power unit (APU) is the focus of this doctoral work. Called DILGO (Dynamic Iterative Local-Global Optimization), this approach allows for the decomposed optimization of the individual units (components, sub-systems or disciplines), while taking into account the intermediate products and feedbacks which couple all of the units which make up the overall system. The approach was developed to support and enhance current engineering synthesis/design practices by making possible dynamic modular concurrent system optimization. In addition, this approach produces improvements in the initial synthesis/design state at all stages of the process and allows any level of complexity in the unit's modeling. DILGO uses dynamic shadow price rates as a basis for measuring the interaction level between units. The dynamic shadow price rate is a representation of the unit's cost rate variation with respect to variations in the unit's coupling functions. The global convergence properties of DILGO are seen to be dependent on the mathematical behavior of the dynamic shadow price rate. The method converges to a "global" (system-level) optimum provided the dynamic shadow price rates are approximately constant or at least monotonic. This is likely to be the case in energy systems where the coupling functions, which represent intermediate products and feedbacks, tend to have a monotonic behavior with respect to the unit's local contribution to the system's overall objective function. Finally, DILGO is a physical decomposition used to solve system-level as well as unit-level optimization problems. The total system considered here is decomposed into three sub-systems as follows: stack sub-system (SS), fuel processing sub-system (FPS), and the work and air recovery sub-system (WRAS). Mixed discrete, continuous, and dynamic operational decision variables are considered. Detailed thermodynamic, kinetic, geometric, physical, and cost models for the dynamic system are formulated and implemented. All of the sub-systems are modeled using advanced state-of-the-art tools. DILGO is then applied to the dynamic synthesis/design and operation/control optimization of the SOFC based APU using the total life cycle cost as objective function. The entire problem has a total of 120 independent variables, some of which are integer valued and dynamic variables. The solution to the problem requires only 6 DILGO iterations. / Ph. D.

Proton exchange membrane fuel cells (PEMFCs) are one of the leading candidates in alternative energy conversion devices for transportation, stationary, and portable power generation applications. PEMFC systems with their own fuel conversion unit typically consist of several subsystems: a fuel processing subsystem, a fuel cell stack subsystem, a work recovery-air supply subsystem, and a power electronics subsystem. Since these subsystems have different physical characteristics, their integration into a single system/subsystem level unit make the problems of dynamic system synthesis/design and operation/control highly complex. Typically, the synthesis/design optimization of energy systems is based on a single full load condition at steady state. However, a more comprehensive synthesis/design and operation/control optimization requires taking into account part as well as full load conditions for satisfying an optimal efficiency/cost/environmental effect objective. Optimal couple of these various aspects of system development requires dynamic system/subsystem/component modeling and a multi-disciplinary approach which results in an integrated set of diverse types of models and highly effective optimization strategies such as decomposition techniques (e.g., Dynamic Iterative Local-Global Optimization: DILGO). In energy system synthesis/design and operation/control problems, system/ component models are typically treated deterministically, even though input values, which include the specific load profile for which the system or subsystem is developed, can have significant uncertainties that inevitably propagate through the system to the outputs. This deficiency can be overcome by treating the inputs and outputs probabilistically. In this work, various uncertainty analysis methodologies are applied; and among these traditional probabilistic approaches (e.g., Monte Carlo simulation) and the response sensitivity analysis (RSA) method are examined to determine their applicability to energy system development. In particular, these methods are used for the probabilistic (non-deterministic) modeling, analysis, and optimization of a residential 5 kWe PEMFC system, and uncertainty effects on the energy system synthesis/design and operation/control optimization have been assessed by taking the uncertainties into account in the objectives and constraints. Optimization results show that there is little effect on the objective (the operating cost and capital cost), while the constraints (e.g., on the CO concentration) can be significantly affected during the synthesis/design and operation/control optimization. / Ph. D.

The typical catalyst layer structure for proton exchange membrane (PEM) fuel cells has changed little over the last two decades. A new electrode design with improved control over factors such as ionic and electrical pathways, porosity, and catalyst placement, could allow the application of less expensive catalyst alternatives. In this work, a novel electrode design based on ionomer-coated carbon nanofibers is proposed and studied. Governing equations for this design were established, and a mathematical model was created and solved using MATLAB to predict the performance of the new electrode design. A parametric study was performed to identify the design variables that had the most significant effect on performance. The best performing catalyst layer design studied with this model produces a current density of 1.1 A cm-2 at 600 mV which is better than state-of-the-art cathode designs. The results offer insight into the performance of ionomer-coated carbon nanofiber catalyst layers and can guide the fabrication and testing of these promising catalyst layer structures. / Master of Science / Proton exchange membrane (PEM) fuel cells have the potential to replace traditional energy conversion systems in many applications, however their widespread adoption is currently limited by their high cost and insufficient durability. PEM fuel cells are expensive because they require the use of platinum as a catalyst. Currently, less expensive non-platinum catalysts, must be used in much higher amounts in the catalyst layer to achieve similar electrochemical activity, creating very thick catalyst layers. Traditional fuel cell catalyst layer structures are designed to be thin and perform poorly when thick enough to accommodate non-platinum catalysts. This work proposes a novel catalyst layer design based on ionomer-coated carbon nanofibers that can allow for thicker catalyst layers and much higher catalyst loadings. A mathematical model was developed for the novel catalyst layer based on first principles. The model was solved using MATLAB to predict the performance of the new catalyst layer design. A parametric study was performed to identify the critical design variables and their effect on catalyst layer performance. The best performing catalyst layer design studied with this model produced a current density of 1.1 A cm-2 at 600mV, which is better than state-of-the-art fuel cell designs. This work is meant to offer insight into the performance of an ionomer-coated nanofiber catalyst layer and to guide future research in the fabrication of high performance fuel cells based on this novel catalyst layer architecture.

With the development of hydrogen fuel cell technology continuing to advance, rapid characterization of membranes is increasingly important for design purposes. Pressurized blister testing has been suggested as an accelerated characterization alternative to traditional relative humidity (RH) cycling tests, and is the focus of this project. Prior efforts to determine the stress state present in the pressurized membrane blister test, however, have required constitutive properties of the membrane (Young's modulus and Poisson's ratio), along with Hencky's classic model for circular membrane stresses. Herein we describe an analysis method and computer vision imaging technique that are capable of determining the stress state in a pressurized circular membrane based solely on simple equilibrium equations and geometric considerations. This analysis method is applied to an image of the blister during testing, and the only additional required data is the pressure at the time the image was taken. By pressurizing circular blisters, an equi-biaxial, mechanical stress state is induced, simulating membrane stresses experienced during fuel cell operation as humidity levels fluctuate. The analysis leverages membrane theory and the axisymmetric geometry to determine the stress state from a profile image of the inflated blister. As a check for the method, an elastomer with known constitutive properties was analyzed using both the previous Hencky's solution method, as well as the new computer vision imaging method. The comparison of stress calculation results show that the two methods agree within 5 percent. A primary mechanism of membrane failure through mechanical stressors is the growth of local defects (usually chemically induced) due to the cyclic equi-biaxial stress state. In order to better understand and characterize the effect of disparate initial defects on CCM, two primary methods to defect membranes were introduced. The first was a compression against sandpaper method meant to simulate GDL compression, and the second was a targeted method using a hypodermic needle to initiate a defect at a central location on the membrane prior to pressurization. Observing the pressure decay in these defected blisters as compared to undefected tests showed that, while undefected samples did not experience pressure decay until failure, defected samples began showing signs of leaking through pressurization cycle profiles and steady state pressures achieved. Pressure data showed that samples tended to lose pressure more quickly with increasing initial defect severity. Undefected samples exhibited no pressure loss until the moment of failure, which was often catastrophic and instantaneous. Sandpaper defected samples exhibited a slow decay in cycle steady state pressure throughout tests, with no increase in cycle pressurization time. Needle samples showed a slow decay in cycle steady state pressure as well as an increase in time for the cycles to reach steady state. The needle defects were the most locally severe and thus the pressure decay indicators were most significant out of all the samples tested. The blister test method rapidly cycles mechanical stresses in a CCM, and elucidates signs of leaking that correlate to flaw development in recorded pressure data. With further development, it might serve as a robust method to quickly test flaw growth rate and development in CCM samples. / Master of Science / Fuel cells are a technology used to supply energy to many sources. In fuel cells, the membrane can limit the lifetime of the entire cell, as the membrane separates the reactant gases allowing the generation of power. If that membrane develops holes or cracks, the fuel cell won't be able to generate as much power, and cell replacement is costly in time and money. Thus, it is important to develop robust membranes to avoid loss in efficiency as much as possible. The research here focuses on rapidly testing how long these membranes last, so that membrane performance can be appropriately ranked, leading to faster technological improvements. We developed two main methods for use in combination with existing blister pressurization equipment; an image-based method that can determine the forces in the membrane, and a novel method to defect membranes before testing. The first method uses a code-based approach to process the image of the blister profile and return stresses. The second method defects the blister before testing so the growth of the defect can be observed over time. Leaking characteristics in the blister were identified in several tests, and the severity of the defects was determined from this information. Thus, the development of the defects can be monitored through these leak characteristics.

The catalyst layer of a proton exchange membrane (PEM) fuel cell is a porous mixture of polymer, carbon, and platinum. The characteristics of the catalyst layer play a critical role in determining the performance of the PEM fuel cell. In this research, sample membrane electrode assemblies (MEAs) are prepared using various combinations of polymer and carbon loadings while the platinum catalyst surface area is held constant. For each MEA, polarization curves are determined at common operating conditions. The polarization curves are compared to assess the effects of the catalyst layer composition. The results show that both Nafion and carbon content significantly affect MEA performance. The physical characteristics of the catalyst layer including porosity, thickness, active platinum surface area, ohmic resistance, and apparent Nafion film thickness are investigated to explain the variation in performance. The results show that for the range of compositions considered in this work, the most important factors are the platinum surface area and the apparent Nafion film thickness. / Master of Science

The development and evaluation of a fuel cell test stand incorporating various methods for controlling the temperature and humidity of fuel cell reactants is described. The test stand is capable of accurately metering gas flows, controlling the temperature and humidity of the gases, and delivering the gases to the fuel cell in a safe manner. Additionally, the test stand can measure the voltage and current produced by the fuel cell during operation. Two test stands were constructed and evaluated, one using steam injection for fuel cell stacks and the other using flash evaporation for individual fuel cells. Both test stands were shown to provide adequate control at the upper end of the design range. The flash evaporation test apparatus was used to investigate the effect of inlet gas humidity on fuel cell performance. The results from this investigation showed that, for a fuel cell and reactant temperature of 75°C, the best performance was achieved with a high relative humidity (90%RH) for the hydrogen and a comparatively low relative humidity (60%) for the air. / Master of Science

A series of steady-state microscopic continuum models of the cathode catalyst layer (active layer) of a proton exchange membrane fuel cell are developed and presented. This model incorporates O₂ species and ion transport while taking a discrete look at the platinum particles within the active layer. The original 2-dimensional axisymmetric Thin Film and Agglomerate Models of Bultel, Ozil, and Durand [8] were initially implemented, validated, and used to generate various results related to the performance of the active layer with changes in the thermodynamic conditions and geometry. The Agglomerate Model was then further developed, implemented, and validated to include among other things pores, flooding, and both humidified air and humidified O₂. All models were implemented and solved using FEMAP™ and a computational fluid dynamics (CFD) solver, developed by Blue Ridge Numerics Inc. (BRNI) called CFDesign™. The use of these models for the discrete modeling of platinum particles is shown to be beneficial for understanding the behavior of a fuel cell. The addition of gas pores is shown to promote high current densities due to increased species transport throughout the agglomerate. Flooding is considered, and its effect on the cathode active layer is evaluated. The model takes various transport and electrochemical kinetic parameters values from the literature in order to do a parametric study showing the degree to which temperature, pressure, and geometry are crucial to overall performance. This parametric study quantifies among a number of other things the degree to which lower porosities for thick active layers and higher porosities for thin active layers are advantageous to fuel cell performance. Cathode active layer performance is shown not to be solely a function of catalyst surface area but discrete catalyst placement within the agglomerate. / Master of Science

A decomposition methodology based on the concept of "thermoeconomic isolation" applied to the synthesis/design and operational optimization of a stationary cogeneration proton exchange membrane fuel cell (PEMFC) based total energy system (TES) for residential/commercial applications is the focus of this work. A number of different configurations for the fuel cell based TES were considered. The most promising set based on an energy integration analysis of candidate configurations was developed and detailed thermodynamic, kinetic, geometric, and economic models at both design and off-design were formulated and implemented. A decomposition strategy called Iterative Local-Global Optimization (ILGO) developed by Muñoz and von Spakovsky was then applied to the synthesis/design and operational optimization of the fuel cell based TES. This decomposition strategy is the first to successfully closely approach the theoretical condition of "thermoeconomic isolation" when applied to highly complex, non-linear systems. This contrasts with past attempts to approach this condition, all of which were applied to very simple systems under very special and restricted conditions such as those requiring linearity in the models and strictly local decision variables. This is a major advance in decomposition and has now been successfully applied to a number of highly complex and dynamic transportation and stationary systems. This thesis work presents the detailed results from one such application. / Master of Science

Electrical shorting through the proton exchange membrane (PEM) is a form of early failure commonly found in PEM fuel cells. In order to improve the durability and thus the commercial potential for PEM fuel cells, this form of failure must be understood and mitigated. This research investigates whether complete penetration is the most likely cause of shorting and establishes general parameters (force, contact pressure, temperature, and time) that lead to shorting in a typical PEM material, Nafion® NRE211. Data was obtained from a novel indentation apparatus that was coupled with an electrical circuit to assess the force and depth of penetration at which shorting occurs in a PEM at temperatures ranging from 70ï °C to 100ï °C. The results show that shorting occurs when full penetration is reached, based on both displacement at shorting, and resistance of the electrical circuit at shorting. In addition, a finite element model was created in a commercial finite element tool (Abaqus) in an attempt to predict time to penetration under loads and geometric configurations typically found in PEM fuel cells. The finite element model was investigated for use with standard Abaqus material modules (e.g. two-layer viscoplastic and hyperelastic-viscoelastic) describing Nafion® behavior. The results suggest that the standard material models do not sufficiently describe Nafion® behavior in this particular application and suggest the need for alternative material models that capture both the viscous and plastic nature of Nafion®. / Master of Science

The goals of the research documented in this thesis were the design, construction, modeling, and validation of a fuel cell hybrid electric vehicle based a conversion of a five-passenger production sedan. Over 60 engineering students working together as the Hybrid Electric Vehicle Team of Virginia Tech (HEVT), integrated a proton exchange membrane fuel cell system into a series hybrid electric vehicle. This design produced an efficient and truly zero-emission vehicle. This 1997 Chevrolet Lumina sedan, renamed ANIMUL H2, carries this advanced powertrain, using an efficient AC induction drivetrain, regenerative braking, compressed hydrogen fuel storage, and an advanced lead-acid battery pack for peak power load leveling. The vehicle weighed 2000 kg (4400 lb) and achieved a combined city/highway fuel economy of 9L/100 km or 26 mpgge (miles per gallon gasoline equivalent, charge depleting, state of charge corrected). A model of the vehicle was developed using ADVISOR, an Advanced Vehicle Simulator that tracks energy flow and fuel usage within the vehicle drivetrain and energy conversion components. The vehicle was tested using the Environmental Protection Agency city and highway driving cycles to provide data for validation of the model. Vehicle data and model results show good correlation at all levels and show that ADVISOR has the capability to model fuel cell hybrid electric vehicles. To make techniques proven by this work more versatile for real world application, VT worked with engineers at the National Renewable Energy Laboratory to develop a 'generic' version of this fuel cell system model that was released to the public in ADVISOR 2.2. This generic model correlates well to test data and incorporates both fuel cell stack and subsystem models. This feature allowed HEVT to predict the benefits of load following subsystem control, showing a 40% fuel economy improvement. / Master of Science