abstract: The environmental impact of the fossil fuels has increased tremendously in the last decade. This impact is one of the most contributing factors of global warming. This research aims to reduce the amount of fuel consumed by vehicles through optimizing the control scheme for the future route information. Taking advantage of more degrees of freedom available within PHEV, HEV, and FCHEV “energy management” allows more margin to maximize efficiency in the propulsion systems. The application focuses on reducing the energy consumption in vehicles by acquiring information about the road grade. Road elevations are obtained by use of Geographic Information System (GIS) maps to optimize the controller. The optimization is then reflected on the powertrain of the vehicle.The approach uses a Model Predictive Control (MPC) algorithm that allows the energy management strategy to leverage road grade to prepare the vehicle for minimizing energy consumption during an uphill and potential energy harvesting during a downhill. The control algorithm will predict future energy/power requirements of the vehicle and optimize the performance by instructing the power split between the internal combustion engine (ICE) and the electric-drive system. Allowing for more efficient operation and higher performance of the PHEV, and HEV. Implementation of different strategies, such as MPC and Dynamic Programming (DP), is considered for optimizing energy management systems. These strategies are utilized to have a low processing time. This approach allows the optimization to be integrated with ADAS applications, using current technology for implementable real time applications. The Thesis presents multiple control strategies designed, implemented, and tested using real-world road elevation data from three different routes. Initial simulation based results show significant energy savings. The savings range between 11.84% and 25.5% for both Rule Based (RB) and DP strategies on the real world tested routes. Future work will take advantage of vehicle connectivity and ADAS systems to utilize Vehicle to Vehicle (V2V), Vehicle to Infrastructure (V2I), traffic information, and sensor fusion to further optimize the PHEV and HEV toward more energy efficient operation. / Dissertation/Thesis / Masters Thesis Mechanical Engineering 2016

In recent years, rules and regulations regarding fuel consumption of vehicles and the amount of emissions produced by them are becoming stricter. This has led the automotive industry to develop more advanced solutions to propel vehicles to meet the legal requirements. The Hybrid Electric Vehicle is one of the solutions that is becoming more popular in the automotive industry. It consists of an electrical driveline combined with a conventional powertrain, propelled by either a diesel or petrol engine. Two power sources create the possibility to choose when and how to use the power sources to propel the vehicle. The strategy that decides how this is done is referred to as an energy management strategy. Today most energy management strategies only try to reduce fuel consumption using models that describe the steady state behaviour of the engine. In other words, no reduction of emissions is achieved and all transient behaviour is considered negligible.  In this thesis, an energy management strategy incorporating engine dynamics to reduce fuel consumption and nitrogen oxide emissions have been designed. First, the models that describe how fuel consumption and nitrogen oxide emissions behave during transient engine operation are developed. Then, an energy management strategy is developed consisting of a model predictive controller that combines the equivalent consumption minimization strategy and convex optimization. Results indicate that by considering engine dynamics in the energy management strategy, both fuel consumption and nitrogen oxide emissions can be reduced. Furthermore, it is also shown that the major reduction in fuel consumption and nitrogen oxide emissions is achieved for short prediction horizons.

The requirements on fuel consumption and emissions for passenger cars are getting stricter every year. This has forced the vehicle industry to look for ways to improve the performance of the driveline. With the increasing focus on electrification, a common method is to combine an electrical driveline with a conventional driveline that uses a petrol or diesel engine, thus creating a hybrid electric vehicle. To fully be able to utilise the potential of the driveline in such a vehicle, an efficient energy management strategy is needed. This thesis describes the development of an efficient route-based energy management strategy. Three different optimisation strategies are combined, deterministic dynamic programming, equivalent consumption minimisation strategy and convex optimisation, together with segmentation of the input data. The developed strategy shows a decrease in computational time with up to more than one hundred times compared to a benchmark algorithm. When implemented in Volvo's simulation tool, VSim, substantial fuel savings of up to ten percent is shown compared to a charge-depleting charge-sustain strategy.

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No. of bitstreams: 2 Tese - Nara Rubia de Freitas - 2017.pdf: 2833609 bytes, checksum: 076cf0403097b47f1822c7d1d4d3972d (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2017-09-14 / Fundação de Amparo à Pesquisa do Estado de Goiás - FAPEG / Hepatitis E, caused by the hepatitis E virus (HEV), is a major public health problem worldwide. However, studies on HEV infection are rare in Central Brazil. This study aimed to estimate the prevalence of this infection, to analyze associated factors, and to detect viral RNA in anti-HEV positive samples in urban (recyclable waste pickers) and rural (residents of settlements) populations, as well as in patients with acute non-A, non- B, non-C hepatitis. A total of 1,274 individuals were studied in the state of Goiás, 431 recyclable waste pickers, 464 individuals living in rural settlements and 379 patients with non-A, non-B, non-C acute hepatitis. All participants were interviewed and blood samples were tested by enzyme-linked immunosorbent assay (ELISA) for the detection of serological markers of hepatitis E (anti-HEV IgG and IgM), and the positive samples were confirmed by immunoblot. The anti-HEV IgM positive samples from recyclable waste pickers were examined for the presence of HEV RNA by nested reverse transcription PCR (RT-PCR), while the other groups by real-time PCR (anti-HEV IgG/IgM positive). In recyclable waste pickers, the prevalences of anti-HEV IgG and IgM markers were 5.1% (95% CI: 3.4-7.6) and 0.7% (95% CI: 0.4-2.4), respectively. After multivariate analysis, age >40 years was associated with the presence of anti-HEV. For rural settlers, the anti- HEV IgG rate was 3.4% (95% CI: 2.0-5.7). None of the samples tested were positive for anti-HEV IgM. Time of dwelling in rural settlement for more than five years was associated with anti-HEV positivity. For patients with non-A, non-B, non-C hepatitis, prevalences of 5.3% (95% CI: 3.3-8.2) and 0.3% (95% CI: 0.0-1.7) were estimated for anti-HEV IgG and IgM, respectively. Low level of schooling was associated with HEV seropositivity, as well as living in rural areas, with borderline p. HEV RNA was not detected in any of the tested samples from the three groups. The seroprevalences found for the anti-HEV IgG marker reveal low exposure to HEV in the three groups analyzed and rare cases of acute infection. These findings suggest that the epidemiological profile of HEV infection observed is similar to that reported in regions with low endemicity. / A hepatite E, causada pelo vírus da hepatite E (HEV), tem uma elevada distribuição mundial e representa um importante problema de saúde pública. No entanto, são raros os estudos sobre a infecção pelo HEV no Brasil Central. Esta investigação teve como objetivos estimar a prevalência dessa infecção, analisar os fatores associados e detectar o RNA viral nas amostras anti-HEV reagentes em populações emergentes urbana (catadores de materiais recicláveis) e rural (moradores de assentamentos), além de pacientes com hepatite aguda não A-C. Um total de 1.274 indivíduos foi estudado no estado de Goiás, sendo 431 catadores de materiais recicláveis, 464 moradores de assentamentos rurais e 379 pacientes com hepatite aguda não A, não B, não C. Todos os participantes foram entrevistados e amostras sanguíneas testadas por ensaio imunoenzimático (ELISA) para a detecção de marcadores sorológicos da hepatite E (anti-HEV IgG e IgM), sendo as reagentes submetidas à confirmação pelo immunoblot. As amostras anti-HEV IgM positivas de catadores de materiais recicláveis foram examinadas quanto à presença do RNA do HEV pela nested PCR pós-transcrição reversa (RT-PCR), enquanto dos demais grupos pela PCR em tempo real (amostras anti-HEV IgG/IgM reagentes). Em catadores de materiais recicláveis, as prevalências para os marcadores anti-HEV IgG e IgM foram de 5,1% (IC 95%: 3,4-7,6) e 0,7% (IC 95%: 0,4-2,4), respectivamente. Pela análise multivariada, idade >40 anos foi associada à presença de anti-HEV. Quanto aos moradores de assentamentos rurais, a taxa de anti-HEV IgG foi de 3,4% (IC 95%: 2,0- 5,7). Nenhuma das amostras testadas foi reagente para o marcador anti-HEV IgM. Tempo de moradia em assentamento rural por mais de cinco anos foi associado à positividade ao anti-HEV. Para pacientes com hepatite não A-C, prevalências de 5,3% (IC 95%: 3,3-8,2) e 0,3% (IC 95%: 0,0-1,7) foram estimadas para marcadores anti-HEV IgG e IgM, respectivamente. Baixo nível de escolaridade foi associado à soropositividade ao HEV, bem como moradia em área rural, com p limítrofe. O RNA viral não foi detectado em nenhuma das amostras testadas dos três grupos. As soroprevalências encontradas para o marcador anti-HEV IgG revelam uma exposição baixa ao HEV nos três grupos analisados e casos raros de infecção aguda. Esses achados sugerem que o perfil epidemiológico da infecção pelo HEV observado é semelhante ao reportado em regiões com baixa endemicidade.

Lead-acid batteries are most used secondary electrochemical power sources. Their basic principle has remained the same for several years; only the operating parameters are in development. Lead-acid batteries are used in hybrid electric vehicles (HEV), which operates in the partial charge PSoC. Sulphation is one of the possible failures lead-acid batteries in the HEV, especially the negative electrode. By adding additives to the negative active mass can reduce the rate of sulphation and increase ability to accept an electrical charge by negative electrode.

In recent years, automotive engineering becomes more challenging and complex than previous years because of the innovation that transformed the cars powertrain system. By the quick developing of the automotive systems and increasing the consumer demand for Hybrid Vehicles (HV), Electric Vehicles (EV) and Autonomous cars, authenticity and security of engine systems are an essential part. The Hybrid Electric Vehicle structure contained several system sections like Electric Motor, Inverter, DC-DC Converter, etc. For testing this device, OEM’s are providing a special automotive standard norm (these norms are individually defining by automotive companies as LV124/123/148) which used for simulates variety of the electrical disturbances and monitoring the system behavior. This standard profile applies, simulates and records by EM Autowave system. Electrical tests have been done for a long time manually. Manual testing takes a huge amount of time, money and human resources. Based on the facts, the thesis purpose is to provide the automated system test for supporting test case execution on the HEV test bench, and offline classification independent of the test bench. This scope of the project will be developed by adapting automation library which is going to equip new features for automation system tool. On the other hand, in order to conform the test simulator and their communication system, a device file is implemented for loading and testing the electrical profiles on the test bench system. In addition, automated classification and evaluation used Matlab functions and the test result will be provided as plots which makes differential discovering very easier.

Efficiency-enhancing measures are evaluated for a serial hybrid fuel cell vehicle over a drive cycle. The regarded powertrain consists of fuel cell system, battery, DC-DC converter, inverter and electrical machine. Within the fuel cell system, the air supply is the largest parasitic load. For the lowest dissipation, different air compression architectures are optimized by a scaling algorithm and compared. Phase switching reduces DC-DC losses. Additionally, a variable DC-link voltage increases efficiency of electrical machine and inverter. Dynamic Programming (DP) is used to evaluate these measures. The DP was extended by start-up and shutdown energy of the fuel cell system to model realistic cycle consumptions. Finally, all these efficiency enhancing measures lead to a reduction of energy consumption by 6.4 % for the serial hybrid fuel cell vehicle over a drive cycle.

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BEVs are a critical pathway towards achieving energy independence and meeting greenhouse and pollutant gas reduction goals in the current and future transportation sector [1]. Automotive manufacturers are increasingly investing in the refinement of electric vehicles as they are becoming an increasingly popular response to the global need for reduced transportation emissions. Therefore, there is a desire to extract the most fuel economy from a vehicle as possible. Some areas that manufacturers spend much effort on include minimizing the vehicle’s mass, body drag coefficient, and drag within the powertrain. When these values are defined or unchangeable, interest is driven to other areas such as investigating the control strategy of the powertrain. If two or more electric motors are present in an electric vehicle, Torque Vectoring (TV) strategies are an option to further increase the fuel economy of electric vehicles. Most of the torque vectoring strategies in literature focus exclusively on enhancing the vehicle stability and dynamics with few approaches that consider efficiency or energy consumption. The limited research on TV that addresses system efficiency have been done on a small number of vehicle architectures, such as four independent motors, and are distributing torque front/rear instead of left/right which would not induce any yaw moment. The proposed research aims to address these deficiencies in the current literature. First, by implementing an efficiency-optimized TV strategy for a rear-wheel drive, dual-motor vehicle under straight-line driving as would be experienced in during the EPA drive cycle tests. Second, by characterizing the yaw moment and implementing strategies to mitigate any undesired yaw motion. The application of the proposed research directly impacts dual-motor architectures in a way that improves overall efficiency which also drives an increase in fuel economy. Increased fuel economy increases the range of electric vehicles and reduces the energy demand from an electrical source that may be of non-renewable origin such as coal.

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