Yes / The single-stage flyback Photovoltaic (PV) micro-inverter is considered as a simple and small in size topology but requires expensive digital microcontrollers such as Field-Programmable Gate Array (FPGA) or Digital Signal Processor (DSP) to increase the system efficiency, this would increase the cost of the overall system. To solve this problem, based on a single-stage flyback structure, this paper proposed a low cost and simple analog-digital control scheme. This control scheme is implemented using a low cost ATMega microcontroller built in the Arduino Uno board and some analog operational amplifiers. First, the single-stage flyback topology is analyzed theoretically and then the design consideration is obtained. Second, a 120 W prototype was developed in the laboratory to validate the proposed control. To prove the effectiveness of this control, we compared the cost price, overall system efficiency, and THD values of the proposed results with the results obtained by the literature. So, a low system component, single power stage, cheap control scheme, and decent efficiency are achieved by the proposed system. Finally, the experimental results present that the proposed system has a maximum efficiency of 91%, with good values of the total harmonic distortion (THD) compared to the results of other authors / This work was supported in-part by Innovate UK GCRF Energy Catalyst PiCREST project under Grant number 41358, in-part by British Academy GCRF COMPENSE project under Grant GCRFNGR3\1541

The rise in overall powertrain complexity and the stringent performance requirements of a hybrid electric vehicle (HEV) have elevated the role of its powertrain control strategy to considerable importance. Iterative modeling and simulation form an integral part of the control strategy design process and industry engineers rely on proprietary ?legacy? models to rapidly develop and implement control strategies. However, others must initiate new algorithms and models in order to develop production-capable control systems. This thesis demonstrates the development and validation of a charge-sustaining control algorithm for a through-the-road (TTR) parallel hybrid (diesel-electric) powertrain. Some unique approaches used in powertrain-level control of other commercial and prototype vehicles have been adopted to incrementally develop this control strategy. The real-time performance of the control strategy has been analyzed through on-road and chassis dynamometer tests over several standard drive cycles. Substantial quantitative improvements in the overall HEV performance over the stock configuration, including better acceleration and fuel-economy have been achieved.

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In a world with a growing population there is a trend toward higher and higher energy usage. Because of the cost involved in producing extra energy, there is a need for more efficient usage of the energy that is already available. The issue of efficiency rings home especially clear with electric motors. Although induction motors are used in many different applications, the motors used in electric vehicles must be able to generate a large starting torque as well as operate over a wide speed range. This work analyzes the restrictions placed on the motor and inverter drive system. It also looks at the best method for controlling the drive in order to achieve the highest efficiency out of the drive. While other works have shown methods of achieve high efficiency out of the motor, it is the assertion of this work that the efficiency of the total drive is more important. It is to that end that this work analyzes the performance of an induction motor under low torque and speed where a traction drive utilizes the most energy. / Master of Science

In the past few years, the price of petroleum based fuels, especially vehicle fuels such as gasoline and diesel, has been increasing at a significant rate. Consequently, there is much more consumer interest related to reducing fuel consumption for conventional vehicles and hybrid electric vehicles (HEVs) than in the past. The goal of many competitions and challenges held in North America and Europe is to achieve extremely low fuel consumption. A possible strategy to reduce fuel consumption is to use the vehicle's fuel converter such as an engine to accelerate the vehicle to a high speed and coast to a lower speed with the engine off. This method will reduce fuel flow to zero during the coast phase. Also, the vehicle uses higher power engine load to accelerate to the upper vehicle speed in a limited time, thus increasing the engine brake thermal efficiency. This strategy is known as "pulse and glide" or "burn and coast" in some references. In this study, the "pulse and glide" (PnG) method is first applied to a conventional vehicle to quantify the fuel consumption benefits when compared to steady speed conditions over the same distance. After that, an HEV is used as well to investigate if a hybrid system can further reduce fuel consumption with the proposed strategy. Note that the HEV used in this study has the advantage that the engine can be automatically shut off below a certain speed (~40 mph) at low loads, however a driver must shut off the engine manually in a conventional vehicle to apply this driving strategy. In this document, three preliminary results of the PnG driving strategy are presented; (1) improved fuel economy for a conventional vehicle from a simple spread sheet model, (2) improved fuel economy for an HEV from a dynamic vehicle simulation model (the Powertrain Analysis Toolkit (PSAT)) and (3) improved fuel economy for an HEV from vehicle testing at Argonne National Laboratory (ANL), all compared to steady speed conditions. The preliminary results show that the impact of engine load and kinetic energy stored in vehicle inertia is significant for fuel consumption using a PnG driving strategy compared to steady speed driving at the same average speed case. Especially, fuel economy can be improved at low speed range and higher acceleration because the aerodynamic drag force is smaller at low speed and the engine is running in a more efficient region for a short period of time respectively. In the last section, proposed directions of research are addressed based on the preliminary results. / Ph. D.

Managing traffic during oversaturated conditions is a current challenge for practitioners due to the lack of adequate tools that can handle such situations. Unlike under-saturated conditions, operation of traffic signal systems during congestion requires careful consideration and analysis of the underlying causes of the congestion before developing mitigation strategies. The objectives of this research are to provide a practical guidance for practitioners to identify oversaturated scenarios and to develop a multi-objective methodology for selecting and evaluating mitigation strategy/ or combinations of strategies based on a guiding principles. The research focused on traffic control strategies that can be implemented by traffic signal systems. The research did not considered strategies that deals with demand reduction or seek to influence departure time choice, or route choice. The proposed timing methodology starts by detecting network's critical routes as a necessary step to identify the traffic patterns and potential problematic scenarios. A wide array of control strategies are defined and categorized to address oversaturation problematic scenarios. A timing procedure was then developed using the principles of oversaturation timing in cycle selection, split allocation, offset design, demand overflow, and queue allocation in non-critical links. Three regimes of operation were defined and considered in oversaturation timing: (1) loading, (2) processing, and (3) recovery. The research also provides a closed-form formula for switching control plans during the oversaturation regimes. The selection of optimal control plan is formulated as linear integer programming problem. Microscopic simulation results of two arterial test cases revealed that traffic control strategies developed using the proposed framework led to tangible performance improvements when compared to signal control strategies designed for operations in under-saturated conditions. The generated control plans successfully manage to allocate queues in network links. / Ph. D.

O principal objetivo dos veículos híbridos é diminuir o consumo de combustível em relação a veículos convencionais. Para isso, existe a necessidade de realizar a integração dos diferentes sistemas do trem-de-força e coordenar o seu funcionamento através de estratégias de controle. Tais estratégias são desenvolvidas e simuladas em conjunto com um modelo computacional da planta do veículo antes de serem aplicadas em uma unidade de controle eletrônica. O presente estudo tem como objetivo analisar o gerenciamento de energia em um veículo híbrido elétrico não-plugin do tipo série-paralelo visando à diminuição de consumo de combustível. O método de otimização global é utilizado para encontrar as variáveis de controle que resultam no mínimo consumo de combustível em um determinado ciclo de condução. Na primeira etapa, um modelo computacional da planta do veículo e da estratégia de controle não-ótima são criados. Os resultados obtidos da simulação são então comparados com dados experimentais do veículo operando em dinamômetro de chassis. A seguir, o método de otimização global é aplicado ao modelo computacional utilizando programação dinâmica e tendo como objetivo a minimização do consumo de combustível total ao final do ciclo. Os resultados mostram considerável redução do consumo de combustível utilizando otimização global e tendo como variável de controle não só a razão de distribuição de torque mas também os pontos de operação do motor de combustão. Os modelos computacionais criados nesse trabalho são disponibilizados e podem ser usados para o estudo de diferentes estratégias de controle para veículos híbridos. / The main goal of hybrid electric vehicles is to decrease engine emission and fuel consumption levels. In order to realize this, one must perform the powertrain system integration and coordinate its operation through supervisory control strategies. These control strategies are developed in a simulation environment containing the plant model of the powertrain before they can be implemented in a real-time control unit. The goal of this work is to analyze the energy management strategy which minimizes the fuel consumption in a series-parallel non-plugin hybrid electric vehicle. Global optimization is used for finding the control variables that result in the minimum fuel consumption for a specific driving cycle. In a first stage, a computational model of vehicle plant and non-optimal control strategy are created. The results from the simulation are compared against experimental data from chassis dynamometer tests. Next, a global optimization strategy is applied using dynamic programming in order to minimize total fuel consumption at the end of the driving cycle. The results from the optimization show a considerable fuel consumption reduction having as control variables not only the torque-split strategy but also the engine operating points. As contribution from this work, the computational models are made available and can be used for analyzing different control strategies for hybrid vehicles.

Le travail présenté traite la question quelle architecture hybride est la plus adapté pour quel type de véhicule. Une approche multi-architecture/multi-application capable d’identifier l’architecture hybride plus efficace en énergie qui considère à la fois les components clés (batterie, moteur électrique, moteur à combustion interne) et la commande optimale, est présenté. La base de cette modélisation est la représentation énergétique macroscopique (REM), qui est combiné avec la programmation orienté objet (POO) afin d’améliorer la modularité et la réutilisation. Les résultats obtenus montrent que des architectures hybrides différents sont le plus adaptés pour différentes applications. De plus, la robustesse des résultats en utilisant des approches de contrôle en temps réel sont étudiés, montrant l’importance de la stratégie de commande. Les résultats obtenus contribuent à la simplification et l’harmonisation de la conception des solutions hybrides pour des applications multiples. / The presented work deals with the question which hybrid architecture is most adapted for which type of vehicle. Therefore, a multi-architecture/multi-application approach capable to identify the most energy efficient hybrid architecture considering both the dimensions of key components (battery, electric motor, internal combustion engine) and the optimal control is presented. Basis of the model is the energetic macroscopic representation (EMR), which has been combined with object oriented programming (OOP) in order to enhance its modularity and reuse capabilities. The obtained results show, that different hybrid architectures are most adapted for different applications. Moreover, the robustness of the results using real time control algorithms are studied, showing that control strategy matters. The obtained results contribute to simplify and harmonize the design of hybrid solutions for multiple applications.

Submitted by Sandra Pereira (srpereira@ufrrj.br) on 2017-08-18T13:57:44Z No. of bitstreams: 1 2010 - Diego Dias Carneiro.pdf: 2540734 bytes, checksum: 49c9a669764fa3f9360256c27d7f24e7 (MD5) / Made available in DSpace on 2017-08-18T13:57:44Z (GMT). No. of bitstreams: 1 2010 - Diego Dias Carneiro.pdf: 2540734 bytes, checksum: 49c9a669764fa3f9360256c27d7f24e7 (MD5) Previous issue date: 2010-03-05 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior, CAPES, Brasil. / Beer is the oldest alcoholic beverage in the world, and its processing has been evolving along the time. Nowadays, beer trading occupies an important position in the economic market since it is the most consumed beverage in Brazil and around the world. Due to this economic significance, the search for more efficient processes that are able to keep the sensorial attributes to the final product represents a great interest for breweries. Fermentation is an important stage of the beer process since in this stage the products and by-products resulted from the yeast metabolism are formed. The detailed study of the fermentative stage of the beer production allows analyzing how the main process variables influence the fermentation and the way they interact each other. To reach this goal, mathematical modeling and computational simulation, were used in this work as a tool for studying the fermentative process. The goals of this study were: i) Select and reproduce through computational simulation, phenomenological models that describe the brewing process; ii) Investigate the effect of manipulate process variables (temperature, pressure and/or flows) over the dynamic behavior of the products and by-products of interest, and; iii) Propose a control strategy that be able to implement optimal temperature profiles in the beer fermentation process. A few dynamics mathematical models that describe the fermentation process were found in the literature. Based on the experimental validation and on the process variables considered, three phenomenological models were selected for the development of this work. It was observed that the manipulate process variables usually affect the dynamic of the fermentation temperature and, as a consequence, the dynamic of the other process variables. A simple control strategy, capable to heat up and refrigerate the fermentation vessel according to the process needs, was proposed in this work to better drive the fermentative process. The proposed control strategy shows very efficient, providing to the process operator facilities to the application of optimal temperature profiles in order to obtain a satisfactory fermentation and leading to a final product with appropriate sensorial attributes for the customer. / A cerveja ? a bebida alco?lica mais antiga do mundo e seu processamento vem evoluindo ao longo do tempo. Atualmente, a comercializa??o da cerveja ocupa uma posi??o de destaque no mercado econ?mico, pois ? a bebida alco?lica mais consumida no Brasil e no mundo. Devido a esta import?ncia econ?mica, a busca por processos mais eficientes e com capacidade de manter a qualidade sensorial do produto final ? de grande interesse para as cervejarias. A fermenta??o ? uma etapa importante do processo cervejeiro, pois ? nessa fase que se formam os produtos e sub-produtos do metabolismo das leveduras. O estudo detalhado sobre a etapa fermentativa da produ??o de cerveja permite analisar como as principais vari?veis de processo influenciam a fermenta??o e o modo como elas interagem. Para atingir esta meta, a modelagem matem?tica, aliada ? simula??o computacional, foi utilizada nessa disserta??o como ferramenta de estudo do processo fermentativo. Os objetivos desta disserta??o foram: i) Selecionar e reproduzir atrav?s de simula??o computacional modelos matem?ticos fenomenol?gicos da etapa de fermenta??o do processo de produ??o cervejeira; ii) Investigar o efeito das vari?veis manipul?veis de processo (temperatura, press?o e/ou vaz?es) sobre o comportamento din?mico dos produtos e subprodutos de interesse, e; iii) Propor uma estrat?gia de controle que seja capaz de implementar de modo eficiente perfis ?timos de temperatura no processo cervejeiro. Foram encontrados poucos modelos din?micos na literatura que representam a etapa fermentativa da produ??o da cerveja. Para o desenvolvimento dessa disserta??o foram utilizados tr?s modelos fenomenol?gicos escolhidos com base em sua valida??o experimental e nas vari?veis de processo consideradas. Observou-se que as vari?veis manipul?veis de processo normalmente influenciam a din?mica da temperatura da fermenta??o e, consequentemente, a din?mica das demais vari?veis do processo. Para a melhor condu??o do processo fermentativo uma estrat?gia de controle simples, capaz de aquecer e refrigerar o tanque de fermenta??o conforme a necessidade do processo, foi proposta nessa disserta??o. A estrat?gia de controle proposta se mostrou bastante eficiente, proporcionando ao operador a possibilidade da aplica??o de perfis ?timos de temperatura que proporcionem a condu??o satisfat?ria da fermenta??o cervejeira, levando a um produto final com os atributos sensoriais adequados para o consumidor.