Unidades propulsoras híbrido elétricas são uma alternativa em potencial para a redução do consumo de combustível e emissões de poluentes, quando empregadas em veículos de transporte público. A configuração híbrido elétrica de interesse é a série, na qual as fontes de potência, para o motor elétrico de tração, são compostas por um banco de baterias e uma unidade formada pela junção entre um motor à combustão interna e um gerador. Na presente Dissertação foi realizada a modelagem de um veículo elétrico híbrido série na qual diferentes estratégias de gerenciamento de potência foram investigadas. Dentre as estratégias de interesse, duas são fundamentadas em regras e a terceira em sistemas fuzzy. Resultados obtidos comprovaram que a fundamentada em sistemas fuzzy possibilita maior economia de combustível, permitindo que o motor à combustão interna forneça menos potência, face o emprego das baseadas em regras. Dessa forma, a utilização de sistemas fuzzy no gerenciamento de potência do veículo, permite o emprego de um motor à combustão menos potente, de menor custo, sem o comprometimento do desempenho do veículo. As simulações do presente modelo de veículo híbrido foram realizadas no ambiente Matlab/Simulink® 7.3.0. / Hybrid electric propulsion units are a potential alternative to the reduction of fuel consumption and pollutant emissions, when used in public transport vehicles. The electric hybrid configuration of interest is the series, in which the energy supplies to the traction electric motor are composed of batteries and a unit represented by the connection of an internal combustion engine and a generator. This Dissertation presents the modeling of a series hybrid electric vehicle in which different energy management strategies were investigated. Among the strategies of interest, two are based on rules and one on fuzzy systems. The obtained results proved that the strategy based on fuzzy systems improved the fuel economy, allowing the internal combustion engine to supply less power than the use of the strategies based on rules. Therefore, the use of fuzzy systems in the energy management of the vehicle allows for the adoption of a less potent and cheaper internal combustion engine, without compromising the vehicles performance. The simulations of the present model of the hybrid electric vehicle were performed in the Matlab/Simulink® 7.3.0 environment.

Renewable and green energy development is vigorously supported by most countries to suppress the continuously increasing greenhouse gas (GHG) emissions. However, as the total renewable capacity expands, the growth rate of emissions is not effectively restrained. An unforeseen factor contributing to this growth is the regulation service, which aims to mitigate power frequency deviations caused by the intermittent renewable power generation and unbalanced power supply and demand. Regulation services, normally issued by supply-side balancing authorities, leads to inefficient operations of regulating generators, thus directly contributing to the emissions growth. Therefore, it is urged to find solutions that can stabilize the power frequency with an increased energy using efficiency. Demand response (DR) is an ideal candidate to solve this problem. The current smart grid infrastructure enables a high penetration of smart residential electric loads, including heating, ventilation, and air conditioning systems (HVACs), air conditioners (A/Cs), electric water heaters (EWHs), and plug-in hybrid electric vehicles (PHEVs). Beyond simply drawing power from the grid for local electric demand, those loads can also adjust their power consumption patterns by responding to the control signals sent to them. It has been proved that, if appropriately aggregated and controlled, power consumption of demand-side residential loads possesses a huge potential for providing regulation services. The research of DR is pivotal from the the application perspective due to the efficient usage of renewable energy generation and the high power quality. However, many problems remain open in this area due to the load heterogeneity, device physical constraints, and computational and communication restrictions. In order to move one step further toward industry applications, this PhD thesis is concerned with two cruxes in DR program design: Aggregation Modeling and Control; it deals with two main types of terminal loads: Thermostatically Controlled Appliances (TCAs) (Chapters 2-4) and PHEVs (Chapter 5). This thesis proceeds with Chapter 1 by reviewing the state-of-the-art of DR. Then in Chapter 2, the focus is put on modeling and control of TCAs for secondary frequency control. In order to explicitly describe local TCA dynamics and to provide the aggregator a clear global view, TCAs are aggregated by directly stacking their individual dynamics. Terminal TCAs are assumed in a general case that an arbitrary number of TCAs are equipped with varying frequency drives (VFDs). A centralized model predictive control (MPC) scheme is firstly constructed. In the design, to tackle the TCA lockout effect and to facilitate the MPC scheme, a novel approach for converting time-integrated interdependent logic constraints into inequality constraints are proposed. Since a centralized MPC scheme may introduce non-trivial computational load by using this aggregation model, especially when the number of TCAs increases, a distributed MPC (DMPC) scheme is proposed. This DMPC scheme is validated through a more practical case study that all TCAs are subject to pure ON/OFF control. Chapter 3 targets on aggregation modeling and control of TCAs for the provision of primary frequency control. To efficiently reduce the computational load to facilitate the primary frequency control, the explicit monitoring of terminal TCAs must be compromised. To this end, a 2-D population-based model is proposed, in which TCAs are clustered into state bins according to their temperature information and running status. Within the proposed aggregation framework, individual TCA dynamics' evolutions develop into TCA population migration probabilities, thus the computational load of the centralized controller is dramatically reduced. Based on this model, a centralized MPC scheme is proposed for the primary frequency control. The previously proposed population-based model provides a promising direction for the centralized control. However, in traditional population-based model, TCA lockout effect can only be considered when implementing the control signals. This will cause a mismatch between the nominal control signals and the actually implemented ones. To conquer this, in Chapter 4, an improved population-based model is studied to explicitly formulate the TCA lockout effect in the aggregation model. A DMPC scheme is firstly constructed based on this model. Furthermore, since the predictions of regulation signals may not be available or they may include severe disturbances, a control scheme that does not require future regulation signals is urged. To this end, an optimal control scheme, in which a novel penalty is included to maximize the regulation capability, is proposed to facilitate the most practical scenario. Another type of terminal loads that has a huge potential in providing grid services is PHEV. At this point, Chapter 5 presents the aggregation and charging control of heterogeneous PHEVs for the provision of DR. In contrast to using battery state-of-charge (SOC) solely as the system state, a new aggregation model is proposed by introducing a novel concept, i.e., charging requirement index. This index combines the SOC with drivers' specified charging requirements, thus inherently providing the aggregation model with richer information. A centralized MPC scheme is proposed based on this novel model. Both of the model and controller are validated through an overnight valley-filling case study. Finally, the conclusions of the thesis are summarized and future research topics are presented. / Graduate / 0537 / 0544 / 0548 / mingxiliu419@gmail.com

published_or_final_version / abstract / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

Lithium-ion batteries are today finding use in automobiles aiming at reducing fuel consumption and emissions within transportation. The requirements on batteries used in vehicles are high regarding performance and lifetime, and a better understanding of the interior processes that dictate energy and power capabilities is a key to strategic development. This thesis concerns aging in lithium-ion cells using electrochemical tools to characterize electrode and electrolyte properties that affect performance and performance loss in the cells.   A central difficulty regarding battery aging is to manage the coupled effects of temperature and cycling conditions on the various degradation processes that determine the lifetime of a cell. In this thesis, post-mortem analyses on harvested electrode samples from small pouch cells and larger cylindrical cells aged under different conditions form the basis of aging evaluation. The characterization is focused on electrochemical impedance spectroscopy (EIS) measurements and physics-based EIS modeling supported by several material characterization techniques to investigate degradation in terms of properties that directly affect performance. The results suggest that increased temperature alter electrode degradation and limitations relate in several cases to electrolyte transport. Variations in electrode properties sampled from different locations in the cylindrical cells show that temperature and current distributions from cycling cause uneven material utilization and aging, in several dimensions. The correlation between cell performance and localized utilization/degradation is an important aspect in meeting the challenges of battery aging in vehicle applications.   The use of in-situ nuclear magnetic resonance (NMR) imaging to directly capture the development of concentration gradients in a battery electrolyte during operation is successfully demonstrated. The salt diffusion coefficient and transport number for a sample electrolyte are obtained from Li+ concentration profiles using a physics-based mass-transport model. The method allows visualization of performance limitations and can be a useful tool in the study of electrochemical systems. / <p>QC 20140512</p>

One of the benefits of electric vehicles (EVs) and hybrid vehicles (HVs) is their potential to recuperate braking energy. Regenerative braking (RB) will minimize duty levels on the brakes, giving advantages including extended brake rotor and friction material life and, more significantly, reduced brake mass and minimised brake pad wear. In this thesis, a mathematical analysis (MATLAB) has been used to analyse the accessibility of regenerative braking energy during a single-stop braking event. The results have indicated that a friction brake could be downsized while maintaining the same functional requirements of the vehicle braking in the standard brakes, including thermomechanical performance (heat transfer coefficient estimation, temperature distribution, cooling and stress deformation). This would allow lighter brakes to be designed and fitted with confidence in a normal passenger car alongside a hybrid electric drive. An approach has been established and a lightweight brake disc design analysed FEA and experimentally verified is presented in this research. Thermal performance was a key factor which was studied using the 3D model in FEA simulations. Ultimately, a design approach for lightweight brake discs suitable for use in any car-sized hybrid vehicle has been developed and tested. The results from experiments on a prototype lightweight brake disc were shown to illustrate the effects of RBS/friction combination in terms of weight reduction. The design requirement, including reducing the thickness, would affect the temperature distribution and increase stress at the critical area. Based on the relationship obtained between rotor weight, thickness and each performance requirement, criteria have been established for designing lightweight brake discs in a vehicle with regenerative braking.

The fuel usage of a hybrid electric vehicle can be reduced by strategically combining the usage of the combustion engine with the electric motor. One method to determine an optimal split between the two is to use dynamic programming. However, the amount of computations grows exponentially with the amount of states which makes its usage difficult on sequential hardware. This thesis project explores the usage of FPGAs for speeding up the required computations to possibly allow the optimisation to run in real time in the vehicle. A tool to convert a vehicle model to a hardware description language was developed and evaluated. The current version does not run fast enough to run in real time, but some optimisations which would allow that are proposed.

La propulsion hybride (thermique-électrique) constitue une solution pertinente dans la conception de véhicules consommant moins de 2 litres de carburant / 100 km. Néanmoins, ce type de motorisation se heurte à des niveaux de coûts trop élevés pour une large diffusion. Une des raisons de ces coûts importants se situe au niveau des aimants permanents de type terre-rare intégrant la constitution de la machine électrique, et dont le cours des prix est très instable, rendant ce type de machine difficilement compatible avec le marché visé. L'objectif de cette thèse est d’investiguer les structures de machines électriques sans aimant terre-rare et dont les performances massiques peuvent rester comparables à celles des machines à aimants permanents. La première partie des travaux correspond à une vaste étude bibliographique sur les différentes technologies de machines électriques, les différentes architectures et topologies existantes, les matériaux innovants et enfin les techniques et méthode d’analyse et d’optimisation. A la fin de cette phase, il est fait le choix d’étudier les machines synchro-réluctantes à barrières de flux. L’accent est alors mis sur le design de la géométrie du rotor, mais également sur l’impact des matériaux utilisés (matériaux magnétiques classiques ou innovants) sur les performances. La seconde partie de la thèse a pour objectif de mettre en œuvre une stratégie efficace afin de dimensionner de manière optimale l’architecture de la machine choisie. Le choix est fait d’aborder le problème de manière séquentielle : en premier lieu, une optimisation de la topologie seule en s’affranchissant de l’impact de la commande ; dans un deuxième temps, une optimisation de la commande de la géométrie optimisée avec tracé des cartographies de performances ; enfin, une évaluation des différents matériaux au travers de la comparaison de ces performances. Trois configurations de machines sont dimensionnées : une machine synchro-réluctante classique à air (SyRC), une machine synchro-réluctante assistée de d’aimants permanents de type ferrites (SyRA) et enfin une machine synchro-réluctante utilisant le matériau dit « Dual Phase » (SyRDP). Celui-ci présente théoriquement la caractéristique de pourvoir changer localement ses propriétés magnétiques (passage des propriétés magnétiques d’un acier vers celles amagnétiques de l’air dans le cas limite idéal) grâce à un traitement thermique particulier, tout en conservant ses propriétés mécaniques. Cette étude permet de conclure que la machine synchro-réluctante assistée de ferrites montre les meilleures aptitudes, tant pour ce qui est de la puissance crête que du défluxage potentiel. Cependant, la machine synchro-réluctante dans cette configuration est sur le plan mécanique plus fragile que la SyRC et la SyRDP. En effet, avec l’ajout des ferrites, les ponts fer (magnétiques) permettant d’assurer l’intégrité mécanique du rotor à vitesse élevée sont d’autant plus sollicités. En phase de conception, l’optimisation électromagnétique tend à les réduire car ce sont des courts-circuits magnétiques entrainant une réduction des performances, alors que les considérations mécaniques tendent plutôt à augmenter leur épaisseur. La troisième partie de cette thèse porte sur la prise en compte des contraintes mécaniques lors du dimensionnement électromagnétique du rotor. Etant donné que la modélisation et l’optimisation électromagnétiques sont basées sur des modèles éléments finis, et afin de ne pas alourdir davantage le dimensionnement, il est décidé de mettre en place un modèle analytique des contraintes mécaniques particulièrement critiques dans les ponts magnétiques. Les équations de calcul sont inspirées de la théorie des poutres et le modèle est recalibré grâce à des simulations éléments finis. / Hybrid propulsion (electric thermal) is a relevant solution in the search for vehicles consuming less than 2 liters of fuel / 100 km. Nevertheless, this type of motorization comes up against cost levels that are too high for widespread distribution. One of the reasons for these high costs is the level of permanent magnets integrating the constitution of the electric machine. In addition, the "material cost" of these permanent magnets has soared in recent years making this type of machine difficult to match the target market. The aim of the thesis is to propose a magnetless electrical machine structure whose mass performances are comparable to those of permanent magnet machines. This increase in performance can be achieved by high rotation speeds or thermal sizing different from those usually used. The works proposed as part of this thesis will be as follows: - In-depth bibliographic analysis to propose a structure and a principle most adapted to the envisaged constraints- Proposal of a multi physical model (magnetic, thermal, mechanical) of the selected structure. - Use of the multi-physical model for optimal sizing- Follow-up of the realization of the prototype - Experimental validation of the prototype. This work will be conducted as part of a consortium integrating academics, manufacturers and automotive suppliers of the highest order.

"To satisfy the global energy demand while accommodating the rapidly increasing consumption rate in its domestic market, Saudi Arabia must develop and implement fuel efficiency programs in many sectors. Since transportation is a major contributor to fuel consumption and emission levels, introducing Hybrid Electric Vehicles (HEV) provides a viable solution to mitigate the current problems. However, existing studies on the diffusion of innovative vehicle technologies as well as on the understanding of the vehicle ownership and consumer behavior in Saudi Arabia are sparse. To fill this knowledge gap, I have aimed at developing an in-depth knowledgebase about general vehicle ownership and HEV ownership potential in particular for Saudi Arabia in my dissertation. I have achieved the research goal through a comprehensive online questionnaire that contains three different perspectives with each contributing a chapter in my dissertation. The first perspective provides a general understanding of the vehicle owners’ behaviors by analyzing over 600 questionnaire responses. It sheds light on the vehicle ownership determinants of the respondents that currently own vehicles as well as on respondents’ future vehicle purchase plans. This research perspective reveals the importance of vehicle price and seating capacity and points out that seating capacity is not necessarily defined by the household size in Saudi Arabia. As HEV is not yet available in the Saudi market, the next perspective applies the Theory of Reasoned Action (TRA) by analyzing 847 questionnaire responses to identify factors that might drive Saudis’ intention to adopt such technology. The results indicate that, while both subjective norm and attitude are significant in explaining the intention, subjective norm has three times stronger effect on adopting HEV than attitude. The last perspective contains a three-stage analysis to help identify the profiles of the most potential HEV early adopters and increase the chance for the relevant stakeholders to reach out to an effective range of consumers. Three characteristics of such adopters are identified: at least 35 years old, part of a larger household (more than 6 people), and owning more than one vehicle. "

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.

Long haulage of heavy-duty trucks weighing over 15-ton stands for nearly 50% of the fuelconsumption among trucks, making them the most fuel consuming category. This indicatesthe potential benefits in improving the fuel efficiency for said category. Hybridization is onepossible solution.Hybrid vehicles are vehicles with two or more power sources in the powertrain. Differentpowertrain configurations, hybridization levels and hybrid concepts are best suitedfor different applications. With prices for fossil fuels constantly rising hybridization is animportant technology to improve fuel efficiency.Different variations of configurations and concepts enables many choices when decidingon a hybrid driveline. A simulation tool for efficiently comparing various hybrid drivelineswould be a great asset when deciding on a configuration for a certain vehicle application. Forthis thesis the application in focus is the previously mentioned category, a heavy duty longhauler weighing 36-ton.The modeling approach used for the simulation tool is called quasistatic modeling or"backward modeling". This name comes from, based on a chosen drive cycle, the resistingforces which act on the vehicle can statically be calculated at each step from the velocityprofile. The required power to drive along the drive cycle can then be calculated backwardswithin the powertrain resulting in a fuel consumption for the combustion engine. For thisthe free QSS-toolbox for Matlab Simulink has been used as a base and modified when needed.The configuration chosen to be implemented is a parallel electric hybrid and was chosenfor its good characteristics for the type of driving highways provide. For this configurationtwo types of controllers are used, one being an Equivalent Consumption Minimization Strategycontroller and the other a simple, rule based heuristic controller.The results for both controllers show small benefits with hybridization of the longhauler compared with the conventional which in the long run would make bigger differencebecause of the large consumption in whole. A sensitivity analysis was also done showingthat improving conventional vehicle parameters can be as beneficial as hybridization.