The main objective of this research is the development of a flexible test-bench for evaluation of hybrid electric powertrain controllers. As a case study, a real-time near-optimal powertrain controller for a series hybrid electric vehicle (HEV) has been designed and tests. The designed controller, like many other optimal controllers, is based on a simple model. This control-oriented model aims to be as simple as possible in order to minimize the controller computational effort. However, a simple model may not be able to capture the vehicle's dynamics accurately, and the designed controller may fail to deliver the anticipated behavior. Therefore, it is crucial that the controller be tested in a realistic environment. To evaluate the performance of the designed model-based controller, it is first applied to a high-fidelity series HEV model that includes physics-based component models and low-level controllers. After successfully passing this model-in-the-loop test, the controller is programmed into a rapid-prototyping controller unit for hardware-in-the-loop simulations. This type of simulation is mostly intended to consider controller computational resources, as well as the communication issues between the controller and the plant (model solver). As the battery pack is one of the most critical components in a hybrid electric powertrain, the component-in-the-loop simulation setup is used to include a physical battery in the simulations in order to further enhance simulation accuracy. Finally, the driver-in-the-loop setup enables us to receive the inputs from a human driver instead of a fixed drive cycle, which allows us to study the effects of the unpredictable driver behavior. The developed powertrain controller itself is a real-time, drive cycle-independent controller for a series HEV, and is designed using a control-oriented model and Pontryagin's Minimum Principle. Like other proposed controllers in the literature, this controller still requires some information about future driving conditions; however, the amount of information is reduced. Although the controller design procedure is based on a series HEV with NiMH battery as the electric energy storage, the same procedure can be used to obtain the supervisory controller for a series HEV with an ultra-capacitor. By testing the designed optimal controller with the prescribed simulation setups, it is shown that the controller can ensure optimal behavior of the powertrain, as the dominant system behavior is very close to what is being predicted by the control-oriented model. It is also shown that the controller is able to handle small uncertainties in the driver behavior.

There is an increasing interest in sustainability and a growing debate about environmental policy measures aiming at the reduction of green house gas emissions across di erent economic sectors worldwide. The transportation sector is one major greenhouse gas emitter which is heavily regulated to reduce its dependance on oil. These regulations along with the growing customer awareness about global warming has led vehicle manufacturers to seek di erent technologies to improve vehicle e ciencies and reduce the green house gases emissions while at the same time meeting customer's expectation of mobility and exibility. Plug-in hybrid electric vehicles (PHEV) is one major promising solution for a smooth transition from oil dependent transportation sector to a clean electric based sector while not compromising the mobility and exibility of the drivers. In the medium term, plug-in hybrid electric vehicles (PHEV) can lead to signi cant reductions in transportation emissions. These vehicles are equipped with a larger battery than regular hybrid electric vehicles which can be recharged from the grid. For short trips, the PHEV can depend solely on the electric engine while for longer journeys the alternative fuel can assist the electric engine to achieve extended ranges. This is bene cial when the use pattern is mixed such that and short long distances needs to be covered. The plug-in hybrid electric vehicles are well-suited for logistics since they can avoid the possible disruption caused by charge depletion in case of all-electric vehicles with tight time schedules. The use of electricity and fuel gives rise to a new variant of the classical vehicle routing with time windows which we call the plug-in hybrid electric vehicle routing problem with time windows (PHEVRPTW). The objective of the PHEVRPTW is to minimize the routing costs of a eet of PHEVs by minimizing the time they run on gasoline while meeting the demand during the available time windows. As a result, the driver of the PHEV has two decisions to make at each node: (1) recharge the vehicle battery to achieve a longer range using electricity, or (2) continue to the next open time window with the option of using the alternative fuel. In this thesis, we present a mathematical formulation for the plug-in hybrid-electric vehicle routing problem with time windows. We solve this problem using a Lagrangian relaxation and we propose a new tabu search algorithm. We also present the rst results for the full adapted Solomon instances.

This thesis focuses on the feasibility of designing a commercial hybrid electric vehicle (HEV). In this work, relevant system models are developed for the vehicle including powertrain, braking system, electrical machines and battery. Based on these models ten different HEV configurations are assembled for detailed assessment of fuel consumption. This thesis also proposes a smart power management strategy which could be applied to any kind of HEV configuration. The suggested expert system deals with the external information about the driving conditions and modes of the driver as well as the internal states of the internal combustion engine efficiency and the state of charge of the battery, and decides on the power distribution between two different power supplies based on the predefined algorithms. The study illustrates the characteristics of the powertrain components for various HEV configurations. The work also shows the power flow of HEV configurations with the developed smart power management system and therefore, the effectiveness of power management strategies has been evaluated in detail.

Thesis (M.S.) -- Mississippi State University. Department of Electrical and Computer Engineering. / Title from title screen. Includes bibliographical references.

Thesis (M.S.)--University of Texas at El Paso, 2008. / Title from title screen. Vita. CD-ROM. Includes bibliographical references. Also available online.

Thesis (M.S.) -- Mississippi State University. Department of Electrical and Computer Engineering. / Title from title screen. Includes bibliographical references.

abstract: For years the automotive industry has been shifting towards hybridization and electrification of conventional powertrains due to increase in fossil fuel cost and environmental impact due heavy emission of Green House Gases (GHG) and various pollutants into atmosphere by combustion engine powered vehicles. Hybrid Electric Vehicles (HEV) have proved to achieve superior fuel economy and reduced emissions. Supervisory control strategies determining the power split among various onboard power sources are evolving with time, providing better fuel economies. With increasing complexity of control systems driving HEV’s, mathematical modeling and simulation tools have become extremely advanced and have derived whole industry into adopting Model Based Design (MBD) and Hardware-in-the-loop (HIL) techniques to validate the performance of HEV systems in real world. This report will present a systematic mythology where MBD techniques are used to develop hybrid powertrain, supervisory control strategies and control systems. To validate the effectiveness of various energy management strategies for HEV energy management in a real world scenario, Conventional rule-based power split strategies are compared against advanced Equivalent Consumption Minimization Strategy (ECMS), in software and HIL environment. Since effective utilization of the fuel reduction potential of a HEV powertrain requires a careful design of the energy management control methodology, an advanced ECMS strategy involving implementation with Fuzzy Logic to reduce computational overload has been proposed. Conventional real-time implementation of ECMS based strategy is difficult due to the involvement of heavy computation. Methods like Fuzzy Logic based estimation can be used to reduce this computational overload. Real-time energy management is obtained by adding a Fuzzy Logic based on-the-fly algorithm for the estimation of driving profile and adaptive equivalent consumption minimization strategy (A-ECMS) framework. The control strategy is implemented to function without any prior knowledge of the future driving conditions. The idea is to periodically refresh the energy management strategy according to the estimated driving pattern, so that the Battery State of Charge (SOC) is maintained within the boundaries and the equivalent fuel consumption is minimized. The performance of the presented Fuzzy Logic based adaptive control strategy utilizing driving pattern recognition is benchmarked using a Dynamic Programming based global optimization approach. / Dissertation/Thesis / Masters Thesis Engineering 2015

Um problema que as empresas distribuidoras de energia elétrica convivem são as quedas repentinas no fornecimento, causando inúmeros prejuízos tanto para essas empresas quanto para seus consumidores. Essa dissertação apresentará uma ferramenta que utilizará conhecimentos de sistemas de informações geográficas junto com o uso de inferência nebulosa para orientar a disposição de veículos híbridos (elétricos e à combustão) que podem operar como mini-usinas elétricas no abastecimento de localidades que esteja necessitando de energia em um determinado momento. Para isso, será levantada uma base de dados com características dos veículos híbridos e locais necessitados, dados esses que alimentarão um sistema nebuloso agregado à ferramenta MapServer e a um SIG (Sistema de Informações Geográficas) para, dessa forma, mostrar como saída do sistema qual veículo estará mais apto naquele instante para abastecer o local da demanda de energia. / A problem that electric energy companies have to face is the power outage, which causes innumerable damages for both companies and consumers. This dissertation describes a tool that joins Geographic Information Systems knowledge to Fuzzy Logic knowledge to guide the distribution of hybrid vehicles (electric and combustion) that can operate as mini electric power plants to supply places that need electrical power. For this, a database will be built with the characteristics of vehicles and places in need. The data will supply a Fuzzy system joined to a MapServer tool and a GIS (Geographic Information System), showing which vehicle will be more capable in that moment to supply the place in energy demand.

Orientador: Franco Giuseppe Dedini / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica / Made available in DSpace on 2018-08-17T03:50:36Z (GMT). No. of bitstreams: 1 Souza_ReynaldoBarrosde_M.pdf: 4185752 bytes, checksum: ed943a90ea99ae1eba06b60915cb20d9 (MD5) Previous issue date: 2010 / Resumo: Este trabalho tem como objetivo o estudo da tecnologia de veículos híbridos abrangendo os aspectos da propulsão e armazenamento de energia. O desenvolvimento de veículos com maior eficiência energética depende da análise das características de desempenho do veículo, bem como suas condições de utilização. O dimensionamento dos armazenadores de energia é considerado um desafio visto que, o sobredimensionamento da capacidade reduz a eficiência global do veículo, devido ao acréscimo de peso, enquanto que o subdimensionamento resulta numa utilização parcial do potencial de veículos híbridos. Através de um modelo de dinâmica veicular longitudinal serão realizadas simulações em três configurações de veículos e a comparação entre seus resultados. As forças requeridas no movimento de um veículo, resistência ao rolamento, resistência à inclinação e arrasto aerodinâmico, são dependentes do trajeto percorrido pelo usuário. As condições de utilização devem ser representadas em ciclos de condução padrão, utilizados em testes de emissões de poluentes e consumo de combustível, estes serão apresentados e discutidos. A partir das simulações realizadas são analisadas as demandas de potência e energia, provendo uma indicação dos benefícios de um sistema híbrido no desempenho e consumo de combustível. Observa-se uma redução expressiva no consumo energético e conseqüente menor utilização de combustível e menor custo de utilização, embora a tecnologia híbrida agregue um maior custo inicial / Abstract: This paper focus on the study of energy storage and management for hybrid electric vehicles. The development of higher efficiency vehicles depends on the analysis of vehicle performance characteristics and driving conditions. Sizing the energy capacity of the storage system, using batteries or other kinds of electric components, can be considered a big challenge once oversizing means inefficiency due to the increase of weight and undersizing results in partial use of hybrid advantages. The forces involved in a vehicle movement such as aerodynamic drag, rolling resistance and grading resistance, are fully dependent on the conditions of every possible course the driver might run, most situations should be represented on the driving pattern cycle, used for emissions and consumption tests, which will be presented and discussed. Modeling vehicle dynamic to analyze power and energy demand of each vehicle during different test cycles provides an indication of the benefits on hybrid system for performance and fuel consumption. . The results show a significant reduction on energy consumption and consequently also on driving costs / Mestrado / Mecanica dos Sólidos e Projeto Mecanico / Mestre em Engenharia Mecânica

Orientador: Franco Giuseppe Dedini / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica / Made available in DSpace on 2018-08-24T19:38:02Z (GMT). No. of bitstreams: 1 Santiciolli_FabioMazzariol_M.pdf: 3517962 bytes, checksum: dce3e151594966ee424d36ea933a24f9 (MD5) Previous issue date: 2014 / Resumo: Este trabalho tem a intenção de contribuir com o projeto de veículos elétricos híbridos com foco no compromisso entre economia de combustível e custo de rodagem. Com esta finalidade, faz-se uma revisão sobre a modelagem de alguns dos principais subsistemas dos veículos elétricos híbridos, como ultracapacitores, baterias, motores elétricos e motores de combustão interna, bem como sobre as formas de associação destes subsistemas em torno do veículo completo. Também se revisam os fatores que compõe a dinâmica veicular longitudinal como o Arrasto Aerodinâmico, a Resistência à Rolagem e a Resistência ao Aclive. Após o domínio dos subsistemas mais importantes e da dinâmica veicular, montam-se modelos matemáticos de veículos completos e em torno de simulações computacionais. Neste estudo fazem-se quatro tipos de simulações principais, uma relativa a um veículo convencional e outras três versões alternativas hibridizadas, variando-se o modo de associação entre baterias, ultracapacitores, choppers e motores elétricos. Em sequência, para cada versão otimizam-se os armazenadores em função da capacidade de tração elétrica e do ciclo brasileiro normatizado de condução urbana. Por fim faz-se uma análise crítica dos resultados / Abstract: This research intends to contribute to the design of hybrid electric vehicles focusing on compromise between fuel economy and running costs. For this purpose, it contains a review on the modeling of some of the main subsystems of hybrid electric vehicles, such as ultracapacitors, batteries, electric motors and internal combustion engines, as well as the forms of associating these subsystems around the whole vehicle. It also revises the factors that compose the longitudinal vehicle dynamics like Aerodynamic Drag, Rolling Resistance and Uphill Resistance. After the dominance of the main subsystems and vehicle dynamics, it describes the mathematical models of complete vehicles and around computer simulations. This study contains four main types of simulations, relative to a conventional vehicle and three other alternatives hybridized versions, varying the mode of association between batteries, ultracapacitors, choppers and electric motors. In sequence, to the amount of electric traction and the Brazilian standardized urban driving cycle are the parameters that command the optimization of each version is the energy stores. Finally it finishes in a critical analysis of the results / Mestrado / Mecanica dos Sólidos e Projeto Mecanico / Mestre em Engenharia Mecânica