<div>The commercial vehicle sector is an important enabler of the economy and is heavily dependent on fossil fuels. In the fight against climate change, reduction of emissions by improving fuel economy is a key step for the commercial vehicle sector. Improving fuel economy deals with reducing energy losses from fuel to the wheels. This study aims to analyze efficiency improvements for two systems that are important in reducing CO2 emissions - hybrid powertrains and natural gas engines. At first, a prototype series hybrid powertrain was analyzed based on on-highway data collected from its powertrain components. Work done per mile by the electrical components of the powertrain showed inefficient battery operation. The net energy delivery of the battery was close to zero at the end of the runs. This indicated battery was majorly used as an energy storage device. Roughly 15% of losses were observed in the power electronics to supply power from battery and generator to the motor. Ability of the hybrid system to capture regenerative energy and utilize it to propel the vehicle is a primary cause for fuel savings. The ability of this system to capture the regenerative energy was studied by modeling the system. The vehicle model demonstrated that the system was capturing most of the theoretically available regenerative energy. The thesis also demonstrates the possibility of reduction of vehicular level losses for the prototype truck. Drag and rolling resistance coefficients were estimated based on two coast down tests conducted. The ratio of captured regenerative to the drive energy energy for estimated drag and rolling resistant coefficients showed that the current system utilizes 4%-9% of its drive energy from the captured regenerative energy. Whereas a low mileage Peterbilt 579 truck could increase the energy capture ratio to 8%-18% for the same drive profile and route. Decrease in the truck’s aerodynamic drag and rolling resistance can potentially improve the fuel benefits.</div><div>The second study aimed to reduce the engine level pumping losses for a natural gas spark ignition engine by cylinder deactivation (CDA). Spark ignited stoichiometric engines with an intake throttle valve encounter pumping/throttling losses at low speed, low loads due to the restriction of intake air by the throttle body. A simulation study for CDA on a six cylinder natural gas engine model was performed in GT- Power. The simulations were ran for steady state operating points with a torque range 25-560 ftlbs and 1600 rpm. Two , three and four cylinders were deactivated in the simulation study. CDA showed significant fuel benefits with increase in brake thermal efficiency and reduction in brake specific fuel consumption depending on the number of deactivated cylinders. The fuel benefits tend to decrease with increase in torque. Engine cycle efficiencies were analyzed to investigate the efficiency improvements. The open cycle efficiency is the main contributor to the overall increase in the brake thermal efficiency. The work done by the engine to overcome the gas exchange during the intake and exhaust stroke is referred to the pumping losses. The reduction in pumping losses cause an improvement in the open cycle efficiency. By deactivating cylinders, the engine meets its low torque requirements by increase in the intake manifold pressure. Increased intake manifold pressure also resulted in reduction of the pumping loop indicating reduced pumping losses. A major limitation of the CDA strategy was ability to meet EGR fraction requirements. The increase in intake manifold pressure also caused a reduction in the delta pressure across the EGR valve. At higher torques with high EGR requirements CDA strategy was unable to meet the required EGR fraction targets. This limited the benefits of CDA to a specific torque range based on the number of deactivated cylinders. Some variable valve actuation strategies were suggested to overcome this challenge and extend the benefits of CDA for a greater torque range.</div><div><br></div>

[pt] O desempenho de veículos automotivos é um importante atributo a ser avaliado quando motores de combustão interna e novos combustíveis estão sendo desenvolvidos. A previsão desse parâmetro também é de suma importância, uma vez que os testes de desempenho de automóveis em pista requerem prazos de realização e altos custos com equipamentos, aluguel da pista, contratação de pessoas e deslocamento de veículos e combustíveis. Além disso, seus resultados são diretamente afetados por irregularidades na superfície da pista e variações nas condições climáticas, como pressão ambiente, temperatura, umidade do ar e velocidade do vento. Assim, este trabalho tem como objetivo utilizar os dados coletados em testes de bancada com um motor de combustão interna com a finalidade de modelar os testes de retomada de velocidade de um automóvel convencional leve. A metodologia proposta simula a força de tração nas rodas a partir do torque medido no dinamômetro do motor ou a partir das curvas de pressão no interior da câmara de combustão com o auxílio de modelos de atrito para motores de ignição por centelha. Para validar o modelo proposto, foi necessário realizar testes de retomada de velocidade com o carro em um dinamômetro de chassi. Além disso, foram utilizadas sete misturas diferentes de etanol e gasolina, e concluiu-se que o etanol anidro puro promoveu maior capacidade de aceleração na maioria dos experimentos, mas apresentou maior consumo de combustível. Os combustíveis hidratados reduziram o desempenho, mas melhoraram a eficiência global. As simulações demonstraram alta precisão em relação ao experimento, com média da diferença do tempo de recuperação da velocidade de 0,51 segundos e desvio padrão de 0,078. Além disso, as simulações de desempenho de aceleração tiveram erros menores que 5,25 por cento. Além disso, a realização desses testes em laboratório tem a vantagem de um maior controle das condições ambientais da sala e dos parâmetros de operação do motor. / [en] Vehicle performance is an important feature to be evaluated when internal combustion engines and new fuels are being developed. Predicting this parameter is also of great significance, once track testing requires long periods of time to be done and high costs with equipment, rental of the track, hiring people and displacement of vehicles and fuels. In addition, their results are directly affected by track surface irregularities and variations in weather conditions such as ambient pressure, temperature, air humidity and wind speed. Thus, this work aims to use collected data in bench tests with an internal combustion engine in order to modeling an automobile speed recovery time. The proposed methodology simulates the traction force on the wheels based on the measured torque in engine dynamometer or from the pressure curves inside the combustion chamber with the aid of friction models for spark ignition engines. In order to validate the proposed model, it became necessary to perform speed recovery tests with the car on a chassis dynamometer. Also, seven different mixtures of ethanol and gasoline were used, and it was concluded that pure anhydrous ethanol promoted a higher acceleration capacity in most of the experiments but it had higher fuel consumption. Hydrated fuels reduced performance but improved global efficiency. The simulations demonstrated a high precision in relation to the experiment, with a speed recovery time diference average of 0.51 seconds and standard deviation of 0.078. Also, the acceleration performance simulations had errors smaller than 5.25 percent. In addition, doing these tests in laboratory has the advantage of a greater control of the room ambient conditions and the engine operating parameters.

In this thesis, exergy based SI engine model optimisation (EBSIEMO) is studied and evaluated. A four-stroke bi-fuel spark ignition (SI) engine is modelled for optimisation of engine performance based upon exergy analysis. An artificial neural network (ANN) is used as an emulator to speed up the optimisation processes. Constrained particle swarm optimisation (CPSO) is employed to identify parameters such as equivalence ratio and ignition time for optimising of the engine performance, based upon maximising ¿total availability¿. In the optimisation process, the engine exhaust gases standard emission were applied including brake specific CO (BSCO) and brake specific NOx (BSNOx) as the constraints. The engine model is developed in a two-zone model, while considering the chemical synthesis of fuel, including 10 chemical species. A computer code is developed in MATLAB software to solve the equations for the prediction of temperature and pressure of the mixture in each stage (compression stroke, combustion process and expansion stroke). In addition, Intake and exhaust processes are calculated using an approximation method. This model has the ability to simulate turbulent combustion and compared to computational fluid dynamic (CFD) models it is computationally faster and efficient. The selective outputs are cylinder temperature and pressure, heat transfer, brake work, brake thermal and volumetric efficiency, brake torque, brake power (BP), brake specific fuel consumption (BSFC), brake mean effective pressure (BMEP), concentration of CO2, brake specific CO (BSCO) and brake specific NOx (BSNOx). In this model, the effect of engine speed, equivalence ratio and ignition time on performance parameters using gasoline and CNG fuels are analysed. In addition, the model is validated by experimental data using the results obtained from bi-fuel engine tests. Therefore, this engine model was capable to predict, analyse and useful for optimisation of the engine performance parameters. The exergy based four-stroke bi-fuel (CNG and gasoline) spark ignition (SI) engine model (EBSIEM) here is used for analysis of bi-fuel SI engines. Since, the first law of thermodynamic (the FLT), alone is not able to afford an appropriate comprehension into engine operations. Therefore, this thesis concentrates on the SI engine operation investigation using the developed engine model by the second law of thermodynamic (the SLT) or exergy analysis outlook (exergy based SI engine model (EBSIEM)) In this thesis, an efficient approach is presented for the prediction of total availability, brake specific CO (BSCO), brake specific NOx (BSNOx) and brake torque for bi-fuel engine (CNG and gasoline) using an artificial neural network (ANN) model based on exergy based SI engine (EBSIEM) (ANN-EBSIEM) as an emulator to speed up the optimisation processes. In the other words, the use of a well trained an ANN is ordinarily much faster than mathematical models or conventional simulation programs for prediction. The constrained particle swarm optimisation (CPSO)-EBSIEM (EBSIEMO) was capable of optimising the model parameters for the engine performance. The optimisation results based upon availability analysis (the SLT) due to analysing availability terms, specifically availability destruction (that measured engine irreversibilties) are more regarded with higher priority compared to the FLT analysis. In this thesis, exergy based SI engine model optimisation (EBSIEMO) is studied and evaluated. A four-stroke bi-fuel spark ignition (SI) engine is modelled for optimisation of engine performance based upon exergy analysis. An artificial neural network (ANN) is used as an emulator to speed up the optimisation processes. Constrained particle swarm optimisation (CPSO) is employed to identify parameters such as equivalence ratio and ignition time for optimising of the engine performance, based upon maximising ¿total availability¿. In the optimisation process, the engine exhaust gases standard emission were applied including brake specific CO (BSCO) and brake specific NOx (BSNOx) as the constraints. The engine model is developed in a two-zone model, while considering the chemical synthesis of fuel, including 10 chemical species. A computer code is developed in MATLAB software to solve the equations for the prediction of temperature and pressure of the mixture in each stage (compression stroke, combustion process and expansion stroke). In addition, Intake and exhaust processes are calculated using an approximation method. This model has the ability to simulate turbulent combustion and compared to computational fluid dynamic (CFD) models it is computationally faster and efficient. The selective outputs are cylinder temperature and pressure, heat transfer, brake work, brake thermal and volumetric efficiency, brake torque, brake power (BP), brake specific fuel consumption (BSFC), brake mean effective pressure (BMEP), concentration of CO2, brake specific CO (BSCO) and brake specific NOx (BSNOx). In this model, the effect of engine speed, equivalence ratio and ignition time on performance parameters using gasoline and CNG fuels are analysed. In addition, the model is validated by experimental data using the results obtained from bi-fuel engine tests. Therefore, this engine model was capable to predict, analyse and useful for optimisation of the engine performance parameters. The exergy based four-stroke bi-fuel (CNG and gasoline) spark ignition (SI) engine model (EBSIEM) here is used for analysis of bi-fuel SI engines. Since, the first law of thermodynamic (the FLT), alone is not able to afford an appropriate comprehension into engine operations. Therefore, this thesis concentrates on the SI engine operation investigation using the developed engine model by the second law of thermodynamic (the SLT) or exergy analysis outlook (exergy based SI engine model (EBSIEM)) In this thesis, an efficient approach is presented for the prediction of total availability, brake specific CO (BSCO), brake specific NOx (BSNOx) and brake torque for bi-fuel engine (CNG and gasoline) using an artificial neural network (ANN) model based on exergy based SI engine (EBSIEM) (ANN-EBSIEM) as an emulator to speed up the optimisation processes. In the other words, the use of a well trained an ANN is ordinarily much faster than mathematical models or conventional simulation programs for prediction. The constrained particle swarm optimisation (CPSO)-EBSIEM (EBSIEMO) was capable of optimising the model parameters for the engine performance. The optimisation results based upon availability analysis (the SLT) due to analysing availability terms, specifically availability destruction (that measured engine irreversibilties) are more regarded with higher priority compared to the FLT analysis.

Binderless tungsten carbide (BTC) ceramics are inherently difficult to process and very brittle. Most consolidation techniques for processing pure WC powder require long sintering times and intense energy consumption. High-T pressureless and pressure-assisted sintering processes often lead to low-quality and coarsened microstructures, thus limiting the use of WC ceramics to few niche applications. Field-assisted sintering techniques (FAST), like spark plasma sintering (SPS), significantly improve the densification of fine and ultrafine WC powders. However, SPS requires high current outputs and expensive apparatus. SPS ceramics still lack adequate toughness to extend the use of BTC components in heavy-duty applications requiring reliable load-bearing capability and/or resistance against rapid and unexpected impacts or temperature drops. This research work explored a new consolidation route capable of boosting the mass transport phenomena (accelerated sintering) and, simultaneously, introducing new microstructural features. The process called flash sintering (FS) offers great potential in accelerating diffusion phenomena and altering the crystallographic and/or the defect chemistry of the sintered ceramics. Many scientific studies reported structural alterations, enhanced plastic flow and material softening by introducing “out-of-equilibrium” characteristics. Currently, FS technology requires, for its activation, a negative dependence of the electrical resistivity with temperature (NTC) of the material to be sintered. This is a universal requirement for the flash event to occur thus theoretically inhibiting the flash sintering of conductive materials with a positive temperature coefficient for resistivity (PTC), like metals or WC. In the present work, we reported how during electrical resistance sintering (ERS) experiments conducted on pure WC nanopowders, a flash event was triggered during the first seconds of the process. This was demonstrated to occur thanks to the different evolution of the electrical properties of a granular compact with temperature. WC powders possess an initial NTC behaviour which can activate a transitory thermal runaway phenomenon which makes the activation of a flash event in these materials possible, intense enough to allow ultrafast densification in less than 10 s. This breakthrough allows to verify whether and how the flash event modifies the final sintered material. FS and SPS sintered ceramics were compared in their microstructural, physical and mechanical properties, thus pointing out how some peculiar modifications are exclusively present in the flash-sintered material. FS can stabilize the WC1-x metastable phase after cooling to room temperature, and this was demonstrated to alter the high-temperature deformation of WC micropillars during compression. In addition, FS BTC are inherently softer with respect to SPS ones, resulting in higher fracture toughness and slightly lower hardness. Even if not final, the results indicate how the flash sintering of WC can be explored further to process engineered BTC ceramics with an optimized hardness/toughness ratio and an enhanced deformability.

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In order to meet the high demand for power transmission capacity, some power companies have installed series capacitors on power transmission lines. This allows the impedance of the line to be lowered, thus yielding increased transmission capability. The series capacitor makes sense because it's simple and could be installed for 15 to 30% of the cost of installing a new line, and it can provide the benefits of increased system stability, reduced system losses, and better voltage regulation.1 Protective distance relays, which make use of impedance measurements in order to determine the presence and location of faults, are "fooled" by installed series capacitance on the line when the presence or absence of the capacitor in the fault circuit is not known a priori. This is because the capacitance cancels or compensates some of the inductance of the line and therefore the relay may perceive a fault to be in its first zone when the fault is actually in the second or third zone of protection. Similarly, first zone faults can be perceived to be reverse faults! Clearly this can cause some costly operating errors. The general approach of interest is a method leading to the determination of the values of series L and C of the line at the time of the fault. This is done by analyzing the synchronous and subsynchronous content of the V and I signals seperately which provides adequate information to compute the series L and C of the line. / Master of Science

De nombreux phénomènes naturels sont trop complexes pour être pleinement reconnus par un seul instrument de mesure ou par une seule modalité. Par conséquent, le domaine de recherche de la multi-modalité a émergé pour mieux identifier les caractéristiques riches du phénomène naturel de la multi-propriété naturelle, en analysant conjointement les données collectées à partir d’uniques modalités, qui sont en quelque sorte complémentaires. Dans notre étude, le phénomène d’intérêt multi-propriétés est l’activité du cerveau humain et nous nous intéressons à mieux la localiser au moyen de ses propriétés électromagnétiques, mesurables de manière non invasive. En neurophysiologie, l’électroencéphalographie (EEG) et la magnétoencéphalographie (MEG) constituent un moyen courant de mesurer les propriétés électriques et magnétiques de l’activité cérébrale. Notre application dans le monde réel, à savoir le problème de reconstruction de source EEG / MEG, est un problème fondamental en neurosciences, allant des sciences cognitives à la neuropathologie en passant par la planification chirurgicale. Considérant que le problème de reconstruction de source EEG /MEG peut être reformulé en un système d’équations linéaires sous-déterminé, la solution (l’activité estimée de la source cérébrale) doit être suffisamment parcimonieuse pour pouvoir être récupérée de manière unique. La quantité de parcimonie est déterminée par les conditions dites de récupération. Cependant, dans les problèmes de grande dimension, les conditions de récupération conventionnelles sont extrêmement strictes. En regroupant les colonnes cohérentes d’un dictionnaire, on pourrait obtenir une structure plus incohérente. Cette stratégie a été proposée en tant que cadre d’identification de structure de bloc, ce qui aboutit à la segmentation automatique de l’espace source du cerveau, sans utiliser aucune information sur l’activité des sources du cerveau et les signaux EEG / MEG. En dépit du dictionnaire structuré en blocs moins cohérent qui en a résulté, la condition de récupération conventionnelle n’est plus en mesure de calculer la caractérisation de la cohérence. Afin de relever le défi mentionné, le cadre général des conditions de récupération exactes par bloc-parcimonie, comprenant trois conditions théoriques et une condition dépendante de l’algorithme, a été proposé. Enfin, nous avons étudié la multi-modalité EEG et MEG et montré qu’en combinant les deux modalités, des régions cérébrales plus raffinées sont apparues / Three main challenges have been addressed in this thesis, in three chapters.First challenge is about the ineffectiveness of some classic methods in high-dimensional problems. This challenge is partially addressed through the idea of clustering the coherent parts of a dictionary based on the proposed characterisation, in order to create more incoherent atomic entities in the dictionary, which is proposed as a block structure identification framework. The more incoherent atomic entities, the more improvement in the exact recovery conditions. In addition, we applied the mentioned clustering idea to real-world EEG/MEG leadfields to segment the brain source space, without using any information about the brain sources activity and EEG/MEG signals. Second challenge raises when classic recovery conditions cannot be established for the new concept of constraint, i.e., block-sparsity. Therefore, as the second research orientation, we developed a general framework for block-sparse exact recovery conditions, i.e., four theoretical and one algorithmic-dependent conditions, which ensure the uniqueness of the block-sparse solution of corresponding weighted mixed-norm optimisation problem in an underdetermined system of linear equations. The mentioned generality of the framework is in terms of the properties of the underdetermined system of linear equations, extracted dictionary characterisations, optimisation problems, and ultimately the recovery conditions. Finally, the combination of different information of a same phenomenon is the subject of the third challenge, which is addressed in the last part of dissertation with application to brain source space segmentation. More precisely, we showed that by combining the EEG and MEG leadfields and gaining the electromagnetic properties of the head, more refined brain regions appeared.

L'augmentation des températures de fonctionnement est une des évolutions actuelles de l'électronique de puissance. Ce fonctionnement entraine d’une part des changements de la structure des modules de puissance notamment des structures « 3D » pour assurer un refroidissement double face des composants de puissance, et d’autre part l’utilisation de matériaux qui permettent de réduire des contraintes thermomécaniques, liées à la différence de coefficient de dilatation des matériaux, lors d’une montée en température. Le travail réalisé au cours de cette thèse consiste à développer une nouvelle structure « 3D » basée sur une technique de contact par des micropoteaux en cuivre, élaborés par électrodéposition et ensuite assemblés à un substrat céramique métallisé (notamment, un DBC : Direct Bonding Copper). Pour réaliser ce contact, une technique de frittage par SPS (Spark Plasma Sintering) est utilisée. Nous étudions dans un premier temps le collage direct de cuivre sur des massifs, puis effectuons dans un deuxième temps le collage de cuivre entre les micropoteaux et le DBC. Cette technique SPS est aussi utilisée pour la réalisation d’un nouveau substrat céramique métallisé basé sur des matériaux avec des coefficients de dilatation thermique accordés, pour les applications à haute température. / The increase in operating temperature is one of the current trends in power electronics. This operation leads firstly to changes in the structure of power modules such as "3D" structures to provide a double-side cooling of power components, and secondly the use of materials that reduce thermomechanical stresses, related to the difference in coefficient of thermal expansion. The study realized during this thesis consisted in developing a new "3D" structure based on copper microposts prepared by electroplating, which are then assembled to a metallized ceramic substrate (eg, a DBC: Direct Bonding Copper). To realize this contact, a sintering machine (SPS: Spark Plasma Sintering) is used first to study the direct bonding of copper on solid, and second to perform the bonding between the copper microposts and the DBC. This technique is also used for the production of a new metallized ceramic substrate using materials with matching thermal expansion coefficients, for high temperature applications.