Homogeneous Charge Compression Ignition (HCCI) Engines hold promises of being the next generation of internal combustion engines due to their ability to produce high thermal efficiencies and low emission levels. HCCI combustion is achieved through the auto-ignition of a compressed homogenous fuel-air mixture, thus making it a "fusion" between spark-ignition and compression-ignition engines. The main challenge in developing HCCI engines is the absence of a combustion trigger hence making it difficult to control its combustion timing. The aim of this research project is to model and control a natural gas HCCI engine. Since HCCI depends primarily on temperature and chemical composition of the mixture, Exhaust Gas Recirculation (EGR) is used to control ignition timing. In this research, a thermodynamical, physics-based nonlinear model is developed to capture the main features of the HCCI engine. In addition, the Modified Knock Integral Model (MKIM), used to predict ignition timing, is optimized. To validate the nonlinear model, ignition timing under varying conditions using the MKIM approach is shown to be in accordance with data acquired from a model developed using a sophisticated engine simulation program, GT-Power. Most control strategies are based on a linear model, therefore, the nonlinear model is linearized using the perturbation method. The linear model is validated by comparing its performance with the nonlinear model about a suitable operating point. The control of ignition timing can be defined as a regulation process where the goal is to force the nonlinear model to track a desired ignition timing by controlling the EGR ratio. Parameters from the linear model are used to determine the gains of the LQR controller. The performance of the controller is validated by implementing it on the nonlinear model and observing its ability to track the desired timing with 0.5% error within a certain operating range. To increase the operating range of the controller and reduce steady-state error, an integrator is added to the LQR. Finally, it is shown that the LQR controller is able to successfully reject disturbance, parameter variation, as well as noise.

The low-frequency electromagnetic compatibility (EMC) is an increasingly important aspect in the design of practical systems to ensure the functional safety and reliability of complex products. The opportunities for using numerical techniques to predict and analyze system’s EMC are therefore of considerable interest in many industries. As the first phase of study, a proper model, including all the details of the component, was required. Therefore, the advances in EMC modeling were studied with classifying analytical and numerical models. The selected model was finite element (FE) modeling, coupled with the distributed network method, to generate the model of the converter’s components and obtain the frequency behavioral model of the converter. The method has the ability to reveal the behavior of parasitic elements and higher resonances, which have critical impacts in studying EMI problems. For the EMC and signature studies of the machine drives, the equivalent source modeling was studied. Considering the details of the multi-machine environment, including actual models, some innovation in equivalent source modeling was performed to decrease the simulation time dramatically. Several models were designed in this study and the voltage current cube model and wire model have the best result. The GA-based PSO method is used as the optimization process. Superposition and suppression of the fields in coupling the components were also studied and verified. The simulation time of the equivalent model is 80-100 times lower than the detailed model. All tests were verified experimentally. As the application of EMC and signature study, the fault diagnosis and condition monitoring of an induction motor drive was developed using radiated fields. In addition to experimental tests, the 3DFE analysis was coupled with circuit-based software to implement the incipient fault cases. The identification was implemented using ANN for seventy various faulty cases. The simulation results were verified experimentally. Finally, the identification of the types of power components were implemented. The results show that it is possible to identify the type of components, as well as the faulty components, by comparing the amplitudes of their stray field harmonics. The identification using the stray fields is nondestructive and can be used for the setups that cannot go offline and be dismantled

We propose a new atmospheric model based on first-principles for the simulation of clouds. Our approach is able to simulate the realistic formation of various cloud types, such as cumulus, stratus, stratocumulus, their temporal evolution, and transitions between cloud types. Moreover, we are able to model strongly rotating thunderstorms known as supercells. Our method allows us to simulate cloud formations of up to about 20 km 20 km at interactive rates. For the intuitive exploration, we identified a light-weight parameter set to interactively explore cloud formations. We demonstrate that our model can be coupled with data from real-time weather services to simulate cloud formations in the now. Moreover, we present a novel approach for the simulation of wildfires. Our model is able to realistically capture the combustion process of trees, heat transfer with the environment and fire propagation between trees. We demonstrate that our approach is capable of realistically simulating the propagation of fire through entire ecosystems with varying vegetation occupancy. We integrated our atmospheric model which allows us to simulated clouds emerging from the evaporation of water from burning trees leading to complex so called flammagenitus patterns which are usually observed over wildfires. Our system runs at interactive rates which enables the exploration of wildfires in different environments.

When creating data-based models it is important to include the underlying physical characteristics and constraints of the data. If physical characteristics are not properly included in the model, results may be infeasible or physically impossible. Acoustic environments are better characterized by ensuring that models include the fundamental spatial, spectral, and temporal characteristics of noise sources, or how they change based on location, frequency, and time. When model data are limited, in availability or in reliability, additional care must be taken to ensure models predict feasible results. This dissertation focuses on physics-guided modeling of acoustic environments using limited data, taking into consideration spatial, spectral, and temporal characteristics of noise sources, specifically focused on wind noise and traffic noise. Wind noise contamination in spectral data can be significant, even when using a windscreen. By modeling spectral characteristics of temporally varying wind noise contamination, a method for automatically detecting and reducing wind noise was developed. Reducing non-acoustic wind noise contamination allows for better characterization of outdoor acoustic environments and is useful for accurately measuring other noise sources. Traffic noise varies spatially, spectrally, and temporally, and depends on traffic volume (the number of vehicles per unit time) and traffic class mix (e.g., the relative number of small vehicles compared to large trucks). Using the temporal variation found in reported traffic volume at thousands of locations, a model was developed to represent and predict the spatio-temporal variability of traffic volume nationwide. Further models were created to include dynamic changes in traffic class mix and to predict spectral source traffic noise. The resulting model for predicting source traffic noise is known as VROOM, the Vehicular Reduced-Order Observation-based Model. The physics-guided modeling techniques presented in this dissertation are intended for characterizing acoustic environments, which has applications for such diverse areas as human health and wellness, bioacoustics, wildlife conservation, urban and roadway planning, land development and conservation, noise ordinance legislation, homebuying, and more.

<p>Direct conversion flat panel x-ray image sensors based on using a photoconductor with an active matrix array provide excellent images. These image sensors are suitable for replacing the present day x-ray film/screen cassette to capture an x-ray image electronically, and hence enable a clinical transition to digital radiography. The performance of these sensors depends critically on the selection and design of the photoconductor. This work quantitatively studies the combined effects of the detector geometry (pixel size and detector thickness), operating conditions (x-ray energy and applied electric field) and charge transport properties (e.g., carrier trapping and recombination) of the photoconductor on the detector performance by developing appropriate detector models. In this thesis, the models for calculating the x-ray sensitivity, resolution in terms of the modulation transfer function (MTF), detective quantum efficiency (DQE), and ghosting of x-ray image detectors have been developed. The modeling works are based on the physics of the individual phenomena and the systematic solution of the fundamental physical equations in the photoconductor layer: (1) semiconductor continuity equation (2) Poissons equation (3) trapping rate equations. The general approach of this work is to develop models in normalized coordinates to describe the results of different photoconductive x-ray image detectors. These models are applied to a-Se, polycrystalline HgI_2 and polycrystalline CdZnTe photoconductive detectors for diagnostic medical x-ray imaging applications (e,g., mammography, chest radiography and fluoroscopy). The models show a very good agreement with the experimental results.</p><p>The research presented in this thesis shows that the imaging performances (e.g., sensitivity, MTF, DQE and ghosting) can be improved by insuring that the carrier with higher mobility-lifetime product is drifted towards the pixel electrodes. The carrier schubwegs have to be several times greater, and the absorption depth has to be at least two times smaller than the photoconductor thickness for achieving sufficient sensitivity. Having smaller pixels is advantageous in terms of higher sensitivity by ensuring that the carrier with the higher mobility-lifetime product is drifted towards the pixel electrodes. </p><p>A model for calculating zero spatial frequency detective quantum efficiency, DQE (0), has been developed by including incomplete charge collection and x-ray interaction depth dependent conversion gain. The DQE(0) analyses of a-Se detectors for fluoroscopic applications show that there is an optimum photoconductor thickness, which maximizes the DQE(0) under a constant voltage operation. The application of DQE(0) model to different potential photoconductive detectors for fluoroscopic applications show that, in addition to high quantum efficiency, both high conversion gain and high charge collection efficiency are required to improve the DQE performance of an x-ray image detector.</p><p>An analytical expression of MTF due to distributed carrier trapping in the bulk of the photoconductor has been derived using the trapped charge distribution across the photoconductor. Trapping of the carriers that move towards the pixel electrodes degrades the MTF performance, whereas trapping of the other type of carriers improves the sharpness of the x-ray image.</p><p>The large signal model calculations in this thesis show an upper limit of small signal models of x-ray image detectors. The bimolecular recombination between drifting carriers plays practically no role on charge collection in a-Se detectors up to the total carrier generation rate q0 of 10^18 EHPs/m^2-s. The bimolecular recombination has practically no effect on charge collection in a-Se detectors for diagnostic medical x-ray imaging applications. </p><p>A model for examining the sensitivity fluctuation mechanisms in a-Se detectors has been developed. The comparison of the model with the experimental data reveals that the recombination between trapped and the oppositely charged drifting carriers, electric field dependent charge carrier generation and x-ray induced new deep trap centers are mainly responsible for the sensitivity fluctuation in biased a-Se x-ray detectors. </p><p>The modeling works in this thesis identify the important factors that limit the detector performance, which can ultimately lead to the reduction of patient exposure/dose consistent with better diagnosis for different diagnostic medical x-ray imaging modalities. The quantitative analyses presented in this thesis show that the detector structure is just as important to the overall performance of the detector as the material properties of the photoconductor itself.</p>

<p>Direct conversion flat panel x-ray image sensors based on using a photoconductor with an active matrix array provide excellent images. These image sensors are suitable for replacing the present day x-ray film/screen cassette to capture an x-ray image electronically, and hence enable a clinical transition to digital radiography. The performance of these sensors depends critically on the selection and design of the photoconductor. This work quantitatively studies the combined effects of the detector geometry (pixel size and detector thickness), operating conditions (x-ray energy and applied electric field) and charge transport properties (e.g., carrier trapping and recombination) of the photoconductor on the detector performance by developing appropriate detector models. In this thesis, the models for calculating the x-ray sensitivity, resolution in terms of the modulation transfer function (MTF), detective quantum efficiency (DQE), and ghosting of x-ray image detectors have been developed. The modeling works are based on the physics of the individual phenomena and the systematic solution of the fundamental physical equations in the photoconductor layer: (1) semiconductor continuity equation (2) Poissons equation (3) trapping rate equations. The general approach of this work is to develop models in normalized coordinates to describe the results of different photoconductive x-ray image detectors. These models are applied to a-Se, polycrystalline HgI_2 and polycrystalline CdZnTe photoconductive detectors for diagnostic medical x-ray imaging applications (e,g., mammography, chest radiography and fluoroscopy). The models show a very good agreement with the experimental results.</p><p>The research presented in this thesis shows that the imaging performances (e.g., sensitivity, MTF, DQE and ghosting) can be improved by insuring that the carrier with higher mobility-lifetime product is drifted towards the pixel electrodes. The carrier schubwegs have to be several times greater, and the absorption depth has to be at least two times smaller than the photoconductor thickness for achieving sufficient sensitivity. Having smaller pixels is advantageous in terms of higher sensitivity by ensuring that the carrier with the higher mobility-lifetime product is drifted towards the pixel electrodes. </p><p>A model for calculating zero spatial frequency detective quantum efficiency, DQE (0), has been developed by including incomplete charge collection and x-ray interaction depth dependent conversion gain. The DQE(0) analyses of a-Se detectors for fluoroscopic applications show that there is an optimum photoconductor thickness, which maximizes the DQE(0) under a constant voltage operation. The application of DQE(0) model to different potential photoconductive detectors for fluoroscopic applications show that, in addition to high quantum efficiency, both high conversion gain and high charge collection efficiency are required to improve the DQE performance of an x-ray image detector.</p><p>An analytical expression of MTF due to distributed carrier trapping in the bulk of the photoconductor has been derived using the trapped charge distribution across the photoconductor. Trapping of the carriers that move towards the pixel electrodes degrades the MTF performance, whereas trapping of the other type of carriers improves the sharpness of the x-ray image.</p><p>The large signal model calculations in this thesis show an upper limit of small signal models of x-ray image detectors. The bimolecular recombination between drifting carriers plays practically no role on charge collection in a-Se detectors up to the total carrier generation rate q0 of 10^18 EHPs/m^2-s. The bimolecular recombination has practically no effect on charge collection in a-Se detectors for diagnostic medical x-ray imaging applications. </p><p>A model for examining the sensitivity fluctuation mechanisms in a-Se detectors has been developed. The comparison of the model with the experimental data reveals that the recombination between trapped and the oppositely charged drifting carriers, electric field dependent charge carrier generation and x-ray induced new deep trap centers are mainly responsible for the sensitivity fluctuation in biased a-Se x-ray detectors. </p><p>The modeling works in this thesis identify the important factors that limit the detector performance, which can ultimately lead to the reduction of patient exposure/dose consistent with better diagnosis for different diagnostic medical x-ray imaging modalities. The quantitative analyses presented in this thesis show that the detector structure is just as important to the overall performance of the detector as the material properties of the photoconductor itself.</p>

The main objective for physics based modeling of the power converter components is to design the whole converter with respect to physical and operational constraints. Therefore, all the elements and components of the energy conversion system are modeled numerically and combined together to achieve the whole system behavioral model. Previously proposed high frequency (HF) models of power converters are based on circuit models that are only related to the parasitic inner parameters of the power devices and the connections between the components. This dissertation aims to obtain appropriate physics-based models for power conversion systems, which not only can represent the steady state behavior of the components, but also can predict their high frequency characteristics. The developed physics-based model would represent the physical device with a high level of accuracy in predicting its operating condition. The proposed physics-based model enables us to accurately develop components such as; effective EMI filters, switching algorithms and circuit topologies [7]. One of the applications of the developed modeling technique is design of new sets of topologies for high-frequency, high efficiency converters for variable speed drives. The main advantage of the modeling method, presented in this dissertation, is the practical design of an inverter for high power applications with the ability to overcome the blocking voltage limitations of available power semiconductor devices. Another advantage is selection of the best matching topology with inherent reduction of switching losses which can be utilized to improve the overall efficiency. The physics-based modeling approach, in this dissertation, makes it possible to design any power electronic conversion system to meet electromagnetic standards and design constraints. This includes physical characteristics such as; decreasing the size and weight of the package, optimized interactions with the neighboring components and higher power density. In addition, the electromagnetic behaviors and signatures can be evaluated including the study of conducted and radiated EMI interactions in addition to the design of attenuation measures and enclosures.

The mm-wave frequency range is being increasingly researched to close the gap between 100 to 1000 GHz, the least explored region of the electromagnetic spectrum, often termed as the 'THz Gap'. The ever increasing demand for compact, portable and reliable THz (Terahertz) devices and the huge market potential for THz system have led to an enormous amount of research and development in the area for a number of years. The Gunn Diode is expected to play a significant role in the development of low cost solid state oscillators which will form an essential part of these THz systems.Gunn and mixer diodes will 'power' future THz systems. The THz frequencies generation methodology is based on a two-stage module. The initial frequency source is provided by a high frequency Gunn diode and is the main focus of this work. The output from this diode is then coupled into a multiplier module. The multiplier provides higher frequencies by the generation of harmonics of the input signal by means of a non-linear element, such as Schottky diode Varactor. A realistic Schottky diode model developed in SILVACOTM is presented in this work.This thesis describes the work done to develop predictive models for Gunn Diode devices using SILVACOTM. These physically-based simulations provide the opportunity to increase understanding of the effects of changes to the device's physical structure, theoretical concepts and its general operation. Thorough understanding of device physics was achieved to develop a reliable Gunn diode model. The model development included device physical structure building, material properties specification, physical models definition and using appropriate biasing conditions.The initial goal of the work was to develop a 2D model for a Gunn diode commercially manufactured by e2v Technologies Plc. for use in second harmonic mode 77GHz Intelligent Adaptive Cruise Control (ACC) systems for automobiles. This particular device was chosen as its operation is well understood and a wealth of data is available for validation of the developed physical model. The comparisons of modelled device results with measured results of a manufactured device are discussed in detail. Both the modelled and measured devices yielded similar I-V characteristics and so validated the choice of the physical models selected for the simulations. During the course of this research 2D, 3D rectangular, 3D cylindrical and cylindrical modelled device structures were developed and compared to measured results.The injector doping spike concentration was varied to study its influence on the electric field in the transit region, and was compared with published and measured data.Simulated DC characteristics were also compared with measured results for higher frequency devices. The devices mostly correspond to material previously grown for experimental studies in the development of D-band GaAs Gunn devices. Ambient temperature variations were also included in both simulated and measured data.Transient solutions were used to obtain a time dependent response such as determining the device oscillating frequency under biased condition. These solutions provided modelled device time-domain responses. The time-domain simulations of higher frequency devices which were developed used modelling measured approach are discussed. The studied devices include 77GHz (2nd harmonic), 125 GHz (2nd harmonic) and 100 GHz fundamental devices.During the course of this research, twelve research papers were disseminated. The results obtained have proved that the modelling techniques used, have provided predictive models for novel Transferred Electron Devices (TEDs) operating above 100GHz.

In this thesis, a physics-based single particle modeling is presented to analyze a proposed direct coupled hybrid energy storage modules using lithium-ion battery and ultracapacitor. Firstly, a state of the art for the energy storage system in the electrified vehicles are summarized. Several energy storage elements including lead-acid battery, nickel-metal hydride battery, lithium-ion battery, ultracapacitor, and lithium-ion capacitor are reviewed. Requirements of the energy storage systems in electric, hybrid electric, and plug-in hybrid electric vehicles are generalized. Typical hybrid energy storage system topologies are also reviewed. Moreover, these energy storage elements and hybrid energy storage system topologies are compared to the requirements of the energy storage systems in terms of specific power and specific energy. Secondly, the performance of different battery balancing topologies, including line shunting, ring shunting, synchronous flyback, multi-winding, and dissipative shunting are analyzed based on a linear programming methodology. As a traction battery in an electric or plug-in electric vehicle, high voltage lithium-ion packs are typically configured in a modular fashion, therefore, the analysis considers the balancing topologies at module level and cell level and focuses on minimum balancing time, minimum plug-in charge time, minimum energy loss, and component counts of every balancing topology for the entire battery pack. Thirdly, different modeling techniques for the lithium-ion battery and ultracapacitor are presented. One of the main contributions of this thesis is the development of a physics-based single particle modeling embedded with a solid-electrolyte interface growth model for a lithium-ion battery in battery management system. This development considers the numerical solution of diffusion equation, cell level quantities, parametrization method, effects of number of shells in a spherical particle, SOC-SOH estimation algorithms, and aging effects. The accuracy of the modeling is validated by experimental results of a Panasonic NCR18650A lithium-ion battery cell. Fourthly, the physics-based modeling is applied to analyze the performance of a proposed direct coupled hybrid energy storage module topology based on the Panasonic NCR18650A lithium-ion battery and Maxwell BCAP0350 ultracapacitor. There are many ways to directly connect battery cells and ultracapacitor cells in a module which would influence the performance of the module. The results show that a module has 9 cells in a battery string and 14 cells in an ultracapacitor string can obtain the highest power capability and utilize the most of the energy in an ultracapacitor. More ultracapacitor strings connected in parallel would increase the power density but reduce the energy density. Moreover, the simulation and experimental results indicate that the direct coupled hybrid modules can extend the operating range and slow the capacity fade of lithium-ion battery. An SOC-SOH estimation algorithm for the hybrid module is also developed based on the physics-based modeling. Finally, a pack design methodology is proposed to meet U.S. Advanced Battery Consortium LLC PHEV-40, power-assist, and 48V HEV performance targets for the battery packs or the proposed direct coupled topologies. In order to explore replacement tradeoffs between the battery and ultracapacitor, a case study of the direct coupled topologies is presented. From the case study, ultracapacitors enhance the power capability for short term pulse power and marginally reduce the cost of an entire energy storage system. Moreover, the hybrid module topologies can keep a relatively long all-electric range when the batteries degrade. / Dissertation / Doctor of Philosophy (PhD)

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