This study is concentrated on modelling and developing the controller for the light-duty hybrid electric truck. The hybrid electric vehicle has advantages in fuel economy. However, there have been relatively few studies on commercial HEVs, whilst a considerable number of studies on the hybrid electric system have been conducted in the field of passenger cars. So the current status and the methodologies to develop the LD hybrid electric truck model have been studied through the literature review. The modelling process used in this study is divided into three major stages. The first stage is to determine the structure of the hybrid electric truck and define the hardware. The second is the component modelling using the AMESim simulation tool to develop a forward facing model. In order to complete the component modelling, the information and data were collected from various sources including references and ADVISOR. The third stage is concerned with the controller which was written in Simulink. This was run in a co-simulation with the AMESim vehicle model. Through the initial simulation, the charge-sustaining performance of this controller was verified and improved. Finally, the simulations for the complete model were carried out over a number of drive cycles, such as CBDTRUCK, JE05, and TRL LGV drive cycle, to evaluate and analyse the effect on the fuel economy and the vehicle performance by the engine operating zone and the EM power capacity. The report presents a comparison of the fuel efficiency of the conventional vehicle and the LD hybrid electric truck. The results obtained by the simulation show the feasibility to build the complete vehicle with the designed controller.

Many emerging applications call for wideband analog-to-digital converters and some require medium-to-high resolution. Incorporating such ADCs allows for shifting as much of the signal processing tasks as possible to the digital domain, where more flexible and programmable circuits are available. However, realizing such ADCs with the existing single stage architectures is very challenging. Therefore, parallel ADC architectures such as time-interleaved structures are used. Unfortunately, such architectures require high-speed high-precision sample-and-hold (S/H) stages that are challenging to implement. In this thesis, a parallel ADC architecture, namely, the frequency-translating hybrid ADC (FTH-ADC) is proposed to increase the conversion speed of the ADCs, which is also suitable for applications requiring medium-to-high resolution ADCs. This architecture addresses the sampling problem by sampling on narrowband baseband subchannels, i.e., sampling is accomplished after splitting the wideband input signals into narrower subbands and frequency-translating them into baseband where identical narrowband baseband S/Hs can be used. Therefore, lower-speed, lower-precision S/Hs are required and single-chip CMOS implementation of the entire ADC is possible. A proof of concept board-level implementation of the FTH-ADC is used to analyze the effects of major analog non-idealities and errors. Error measurement and compensation methods are presented. Using four 8-bit, 100 MHz subband ADCs, four 25 MHz Butterworth filters, two 64-tap FIR reconstruction filters, and four 10-tap FIR compensation filters, a total system with an effective sample rate of 200 MHz is implemented with an effective number of bits of at least 7 bits over the entire 100 MHz input bandwidth. In addition, one path of an 8-GHz, 4-bit, FTH-ADC system, including a highly-linear mixer and a 5th-order, 1 GHz, Butterworth Gm-C filter, is implemented in a 90 nm CMOS technology. Followed by a 4-bit, 4-GHz subband ADC, the blocks consume a total power of 52 mW from a 1.2 V supply, and occupy an area of 0.05 mm2. The mixer-filter has a THD ≤ 5% (26 dB) over its full 1 GHz bandwidth and provides a signal with a voltage swing of 350 mVpp for the subsequent ADC stage.

Un component important de molts sistemes de distribució és el càlcul de les rutes dels vehicles per servir els clients. El Vehicle Routing Problem (VRP) proporciona el marc teòric per tractar aquest tipus de problemes logístics relacionats amb la distribució física de béns. Per la seva complexitat i aplicabilitat, aquest tipus de problemes logístics es troba entre les línies de recerca més populars en optimització combinatòria. Aquesta tesi de doctorat té com a objectiu la introducció de tres metodologies diferents per resoldre el VRP. Aquestes metodologies han estat especialment dissenyades per ser flexibles, en el sentit que poden ser utilitzades, amb adaptacions menors, per resoldre diferents variants del VRP presents en casos d’aplicació industrial. En les tres metodologies descrites en aquest treball s’utilitzen diferents tècniques per aconseguir la flexibilitat, l’eficiència i la robustesa desitjades. Constraint Programming (CP) ha estat escollit com a paradigma de modelat per descriure les principals restriccions presents en el VRP. CP proporciona la flexibilitat desitjada per les tres metodologies, atès que afegir restriccions addicionals presents en molts casos d’aplicació real només afecta al modelat del problema, però no a la definició dels algorismes de cerca. En les dues primeres metodologies descrites, el model de CP només s’utilitza per comprovar la factibilitat de les solucions durant la cerca. La tercera metodologia presenta un model més ric del VRP que permet tractar diferents variants del problema. En aquest cas, la cerca es realitza i es controla fent servir els mecanismes que CP proporciona. La Relaxació Lagrangiana (LR) i una versió probabilística de l’heurística Clarke and Wright Savings (RCWS) s’utilitzen amb una finalitat molt específica dins de les metodologies. LR s’utilitza per minimitzar la distància total recorreguda pels vehicles, mentre que la RCWS es fa servir per calcular una solució inicial de bona qualitat. Ambdós mètodes proporcionen una aproximació eficient als problemes respectius. A més, la utilització de LR permet reduir la complexitat computacional dels processos de cerca local i, d’aquesta manera, redueix el temps computacional necessari per resoldre el VRP. Totes les metodologies es basen en la metaheurística coneguda com Variable Neighborhood Search (VNS). El VNS està format per una família d’algorismes que aprofiten sistemàticament la idea de canviar el veïnat explorat al voltant d’una solució, tant en el procés de cerca per trobar un mínim local com en el procés de pertorbació, per escapar de la vall corresponent. Malgrat que és un mètode bastant estès, hi ha pocs exemples d’aplicació en el VRP. En tot cas, fins i tot els mètodes VNS més simples han aconseguit bons resultats quan han estat aplicats en aquest problema. Aquesta tesi té com a objectiu contribuir en la recerca de l’aplicació de la metaheurística VNS en el VRP. Aquesta ha estat escollida com a marc en el que integrar les tècniques mencionades. Així, la metaheurística s’utilitza per guiar la cerca, mentre que l’eficiència desitjada s’aconsegueix mitjançant els mètodes que s’hi integren. D’altra banda, utilitzar CP com a paradigma de modelat proporciona la flexibilitat requerida. Aquesta característica és especialment rellevant en el cas de la darrera metodologia descrita. En aquest cas, la cerca de CP es guia mitjançant una combinació de les metaheurístiques VNS i Large Neighborhood Search (LNS). Aquesta metodologia representa una primera aproximació a la resolució eficient de problemes VRP més complexos, similars a casos d’aplicació real. / An important component of many distribution systems is routing vehicles to serve customers. The Vehicle Routing Problem (VRP) provides a theoretical framework for approaching this class of logistics problems dealing with physical distribution. Because of its complexity and applicability, this class of logistics problems is among the most popular research areas in combinatorial optimization. This PhD. Thesis is aimed to introduce three different yet related hybrid methodologies to solve the VRP. These methodologies have been especially designed for being flexible in the sense that they can be used, with minor adaptations, for solving different variants of the VRP present in industrial application cases. In the three methodologies described in this work, different technologies are used to achieve the desired flexibility, efficiency, and robustness. Constraint Programming (CP) has been chosen as the modeling paradigm to describe the main constraints involved in the VRP. CP provides the pursued flexibility for the three methodologies, since adding side constraints present in most real application cases becomes a modeling issue and does not affect the search algorithm definition. In the first two hybrid methodologies, the CP model is used to check solution's feasibility during search. The third methodology presents a richer model for the VRP capable of tackling different problem variants. In this case, the search is performed and controlled from a CP perspective. Lagrangian Relaxation (LR) and a probabilistic version of the Clarke and Wright Savings (CWS) heuristic are used for specific purposes within the proposed methodologies. The former is used for minimizing the total traveled distance and the latter to provide a good initial solution. Both methods provide an efficient approach to the respectively faced problems. Moreover, the use of LR permits reducing the computational complexity of the performed local search processes and therefore reduces the required computational time to solve the VRP. All methodologies are based on the so-called Variable Neighborhood Search (VNS) metaheuristic. The VNS is formed by a family of algorithms that exploits systematically the idea of neighborhood changes both in the search phase to find a local minimum, and in perturbation phase, to escape from the corresponding valley. Although it is an extended method, there are few examples of its application to the VRP. However, interesting results have been obtained even applying the simplest VNS algorithms to this problem. The present thesis is aimed to contribute to the current research on the application of the VNS metaheuristic to the VRP. It has been chosen as the framework where the mentioned techniques are embedded. Hence, the metaheuristic is used to guide the search, while the desired efficiency is provided by the composing methods. On the other hand, using CP as the modeling paradigm provides the required flexibility. This characteristic is enhanced in the last described methodology. In this case, the CP search is guided by a combination of the VNS and the Large Neighborhood Search (LNS) metaheuristics. This methodology represents an initial approach for tackling efficiently more complex and richer VRP, similar to real application cases.

In this sociolinguistic study, qualitative interviews were used in examining discursive identity construction among russlanddeutsche Aussiedler. The interview group was composed of russlanddeutsche university students attending the Universität Mannheim in Germany, differentiating it from much of the previous research. In my analysis, working from a social constructionist perspective, I primarily make use of Positioning Theory and Critical Discourse Analytic techniques to show how the interviewees 1) construct groups; 2) relate to language; and 3) position themselves in relation to existing discourses in contemporary German society, including instances of resistance to those discourses. Ethnically Germans, but living on Russian/Soviet/post-Soviet territory for generations, Aussiedler have special claims to German citizenship and began their return to Germany after suffering mass repression for decades under the Soviet regime. In the aftermath of WWII, their emigration to Germany was initially limited, but reached high levels in the late 1980s and throughout the 1990s, as travel restrictions were relaxed and the Iron Curtain fell. Expecting to find acceptance as Deutsche unter Deutschen [Germans among Germans], the opposite often occurs: they are frequently categorized as ‘the Russians.’ Indeed, one of the most frequent comments made by members of this group is: In Russland waren wir Deutsche, hier sind wir Russen [In Russia we were Germans, here we are Russians]. In many respects, they have a stigmatized identity in both countries, Russia and Germany, and for this reason represent a particularly interesting group for identity research. Recent publications, most notably Reitemeier (2006a), have made mention of this ‘stigmatized identity’ and also of the fact that many Russlanddeutsche possess hybrid identities. These two concepts, stigma and hybridity, are explored throughout the thesis. The work begins by outlining the migratory, legal, and linguistic history of Russlanddeutsche. This is followed by an explanation of theoretical and methodological approaches which used to study the data, including Positioning Theory, stigma theory, a variant of Conversation Analysis, and Critical Discourse Analysis. The bulk of the thesis is then spent on the analysis of the qualitative interview data using those theories and methodologies. I conclude by summarizing my findings and suggesting areas for further research.

As the global economy strives towards clean energy in the face of climate change, the automotive industry is researching into improving the efficiency of automobiles. Hybrid vehicle systems were proposed and have demonstrated the capability of reducing fuel consumption while maintaining vehicle performance. Various hybrid vehicles in the form of parallel and series hybrid have been produced by difference vehicle manufacturers. The purpose of this thesis is to create a hybrid vehicle model in MATLAB and ADAMS to demonstrate its fuel economy improvement over a conventional vehicle system. The hybrid vehicle model utilizes the Honda IMA (Integrated Motor Assist) architecture, where the electric motor acts as a supplement to the engine torque. The motor unit also acts as a generator during regenerative braking to recover the otherwise lost kinetic energy. The powertrain components’ power output calculation and the control logic were modeled in MATLAB/Simulink, while the mechanical inertial components were modeled in ADAMS. The model utilizes a driver input simulation, where the driver control module compares the actual and desired speeds, and applies a throttle or a braking percent to the powertrain components, which in turns applies the driving or the braking torque to the wheels. Communication between MATLAB and ADAMS was established by ADAMS/Controls. In order to evaluate the accuracy of the MATLAB/ADAMS hybrid vehicle model, simulation results were compared to the published data of ADVISOR. The West Virginia University 5 Peaks drive cycle was used to compare the two software models. The results obtained from MATLAB/ADAMS and ADVISOR for the engine and motor/generator correlated well. Minor discrepancies existed, but were deemed insignificant. This validates the MATLAB/ADAMS hybrid vehicle model against the published results of ADVISOR. Fuel economy of hybrid and conventional vehicle models were compared using the EPA New York City Cycle (NYCC) and the Highway Fuel Economy Cycle (HWFET). The hybrid vehicle demonstrated 8.9% and 14.3% fuel economy improvement over the conventional vehicle model for the NYCC and HWFET drive cycles, respectively. In addition, the motor consumed 83.6kJ of electrical energy during the assist mode while regenerative braking recovered 105.5kJ of electrical energy during city driving. For the highway drive cycle, the motor consumed 213.6kJ of electrical energy during the assist mode while the regenerative braking recovered 172.0kJ of energy. The MATLAB/ADAMS vehicle model offers a simulation platform that is modular, flexible, and can be conveniently modified to create different types of vehicle models. In addition, the simulation results clearly demonstrated the fuel economy advantage of the hybrid vehicle over the conventional vehicle model. It is recommended that a more sophisticated power management algorithm be implemented in the model to optimize the efficiencies of the engine and the motor/generator. Furthermore, it is suggested that the ADAMS vehicle model be validated against an actual vehicle, in order to fully utilize the multi-body vehicle dynamics capability which ADAMS has to offer.

The Genetic Algorithm (GA) is a popular global search algorithm. Although it has been used successfully in many fields, there are still performance challenges that prevent GA’s further success. The performance challenges include: difficult to reach optimal solutions for complex problems and take a very long time to solve difficult problems. This dissertation is to research new ways to improve GA’s performance on solution quality and convergence speed. The main focus is to present the concept of shadow price and propose a two-measurement GA. The new algorithm uses the fitness value to measure solutions and shadow price to evaluate components. New shadow price Guided operators are used to achieve good measurable evolutions. Simulation results have shown that the new shadow price Guided genetic algorithm (SGA) is effective in terms of performance and efficient in terms of speed.

After enjoying one week in the Swedish Lapland, the idea of providing energy to one of those isolated cabins in the far landscape caught our attention. Nowadays, there still exist many dwellings, usually located in rural isolated sites, which have no easy access or even no possibility to get connected to the distribution and transport electricity grids. This situation may cause some inconvenience to the owners, therefore, the interest in finding new alternatives for supplying electricity. Such a problem requires specific solutions, including the development of electrification programs in those countryside isolated spots. Thus, the present project intends to perform a study which would provide the proper electric system to a summerhouse in the North of Sweden. Regarding the current European environmental politics and considering the rural location of the dwelling of study, the project will focus on various renewable alternatives to reach the above mentioned goal. In fact, Sweden has the greatest share of renewable energies in all European Union countries with a fixed goal of reaching 50% of its total energy production by renewable sources by the year 2020. For the present moment, Sweden already accounts for 9.4 GWh on solar energy production and 3.5 TWh on wind power production by the end of 2010. Therefore, the study will build on these alternatives as they represent two of the most extensively developed renewable possibilities in the country. Thereby, the first objective of the project was to determine a concrete location considering both our initial idea and the possibility of obtaining the wind speed and solar radiation data. A plot located 20 km to the north of Lulea was finally chosen. Then, once having the necessary baseline data comes the sizing of the different alternative: stand alone wind turbine system, stand alone PV system and a hybrid system combining wind power with the support of an electric generator. No option including grid connection is taken into consideration due to the lack of accessibility. Finally, it is performed an economic study of each alternative that would lead to a clear conclusion of which is the most appropriate choice in the study case. Economic criteria will therefore be the most significant factor when choosing the optimum alternative. However, environmental issues would also be taken into account. As no traditional electrification is studied, the economic analysis will not refer to the obtained monetary savings regarding to the grid connected option but will be performed by comparing initial investments. After all, it is concluded that the studied dwelling will be electrified by a hybrid system combining wind power with an electric generator. The system includes a 20 kW wind turbine and a diesel fueled generator with 8 kW power service. The generator will provide the required energy to the house during those days when the wind resource is not capable to cover the demand. Therefore, the lack of electricity supply will be avoided. Regarding investment costs of the chosen alternative, the hybrid system accounts for 20,729€ investment, which corresponds to about 40% the total price of both solar and wind stand alone systems. . Considering environmental criteria, the hybrid system only requires 23 diesel liters to be burned during the six summer months. Therefore, emissions due to combustion are relatively low and not considered as damaging. So, the chosen alternative meets both economical and environmental requirements.

This thesis set out to investigate the relationship between political regime type, and FDI inflow. The academic field has seen a fair amount of research in recent years, but this is usually limited to the likes of democracies and autocracies. I argue that many countries are neither of these two, but find themselves in a political unstable gray zone in between, called hybrid regimes. This thesis draws on a comprehensive dataset ranging from 1980-2010, and by way of time-series cross-section analysis; it sets out to explore the attractiveness of hybrid regimes in relation to FDI inflow. The findings indicate that unstable political regimes do attract MNCs, but that they usually are dependent on natural resources. Hybrid regimes receive more FDI inflow than autocracies, but less than democracies. The thesis also find that the region Africa is special in that hybrid regimes are the biggest recipient of FDI inflow, with natural resources being the main factor. The findings support the former literature saying that democratic conditions attracts MNCs, but also question the alleged democratic transition taking place in a growing oil-dependent world.

In this sociolinguistic study, qualitative interviews were used in examining discursive identity construction among russlanddeutsche Aussiedler. The interview group was composed of russlanddeutsche university students attending the Universität Mannheim in Germany, differentiating it from much of the previous research. In my analysis, working from a social constructionist perspective, I primarily make use of Positioning Theory and Critical Discourse Analytic techniques to show how the interviewees 1) construct groups; 2) relate to language; and 3) position themselves in relation to existing discourses in contemporary German society, including instances of resistance to those discourses. Ethnically Germans, but living on Russian/Soviet/post-Soviet territory for generations, Aussiedler have special claims to German citizenship and began their return to Germany after suffering mass repression for decades under the Soviet regime. In the aftermath of WWII, their emigration to Germany was initially limited, but reached high levels in the late 1980s and throughout the 1990s, as travel restrictions were relaxed and the Iron Curtain fell. Expecting to find acceptance as Deutsche unter Deutschen [Germans among Germans], the opposite often occurs: they are frequently categorized as ‘the Russians.’ Indeed, one of the most frequent comments made by members of this group is: In Russland waren wir Deutsche, hier sind wir Russen [In Russia we were Germans, here we are Russians]. In many respects, they have a stigmatized identity in both countries, Russia and Germany, and for this reason represent a particularly interesting group for identity research. Recent publications, most notably Reitemeier (2006a), have made mention of this ‘stigmatized identity’ and also of the fact that many Russlanddeutsche possess hybrid identities. These two concepts, stigma and hybridity, are explored throughout the thesis. The work begins by outlining the migratory, legal, and linguistic history of Russlanddeutsche. This is followed by an explanation of theoretical and methodological approaches which used to study the data, including Positioning Theory, stigma theory, a variant of Conversation Analysis, and Critical Discourse Analysis. The bulk of the thesis is then spent on the analysis of the qualitative interview data using those theories and methodologies. I conclude by summarizing my findings and suggesting areas for further research.

As the global economy strives towards clean energy in the face of climate change, the automotive industry is researching into improving the efficiency of automobiles. Hybrid vehicle systems were proposed and have demonstrated the capability of reducing fuel consumption while maintaining vehicle performance. Various hybrid vehicles in the form of parallel and series hybrid have been produced by difference vehicle manufacturers. The purpose of this thesis is to create a hybrid vehicle model in MATLAB and ADAMS to demonstrate its fuel economy improvement over a conventional vehicle system. The hybrid vehicle model utilizes the Honda IMA (Integrated Motor Assist) architecture, where the electric motor acts as a supplement to the engine torque. The motor unit also acts as a generator during regenerative braking to recover the otherwise lost kinetic energy. The powertrain components’ power output calculation and the control logic were modeled in MATLAB/Simulink, while the mechanical inertial components were modeled in ADAMS. The model utilizes a driver input simulation, where the driver control module compares the actual and desired speeds, and applies a throttle or a braking percent to the powertrain components, which in turns applies the driving or the braking torque to the wheels. Communication between MATLAB and ADAMS was established by ADAMS/Controls. In order to evaluate the accuracy of the MATLAB/ADAMS hybrid vehicle model, simulation results were compared to the published data of ADVISOR. The West Virginia University 5 Peaks drive cycle was used to compare the two software models. The results obtained from MATLAB/ADAMS and ADVISOR for the engine and motor/generator correlated well. Minor discrepancies existed, but were deemed insignificant. This validates the MATLAB/ADAMS hybrid vehicle model against the published results of ADVISOR. Fuel economy of hybrid and conventional vehicle models were compared using the EPA New York City Cycle (NYCC) and the Highway Fuel Economy Cycle (HWFET). The hybrid vehicle demonstrated 8.9% and 14.3% fuel economy improvement over the conventional vehicle model for the NYCC and HWFET drive cycles, respectively. In addition, the motor consumed 83.6kJ of electrical energy during the assist mode while regenerative braking recovered 105.5kJ of electrical energy during city driving. For the highway drive cycle, the motor consumed 213.6kJ of electrical energy during the assist mode while the regenerative braking recovered 172.0kJ of energy. The MATLAB/ADAMS vehicle model offers a simulation platform that is modular, flexible, and can be conveniently modified to create different types of vehicle models. In addition, the simulation results clearly demonstrated the fuel economy advantage of the hybrid vehicle over the conventional vehicle model. It is recommended that a more sophisticated power management algorithm be implemented in the model to optimize the efficiencies of the engine and the motor/generator. Furthermore, it is suggested that the ADAMS vehicle model be validated against an actual vehicle, in order to fully utilize the multi-body vehicle dynamics capability which ADAMS has to offer.