Currently, wide bandgap semiconductor devices feature increased efficiency, higher current handling capabilities, and higher reverse blocking voltages than silicon devices while recent fabrication advances have them drawing near to the marketplace. However these new semiconductors are in need of new packaging that will allow for their application in several important uses including hybrid electrical vehicles, new and existing energy sources, and increased efficiency in multiple new and existing technologies. Also, current power module designs for silicon devices are rife with problems that must be enhanced to improve reliability. This thesis introduces new packaging that is thermally resilient and has reduced mechanical stress from temperature rise that also provides increased circuit lifetime and greater reliability for continued use to 300°C which is within operation ratings of these new semiconductors. The new module is also without problematic wirebonds that lead to a majority of traditional module failures which also introduce parasitic inductance and increase thermal resistance. Resultantly, the module also features a severely reduced form factor in mass and volume.

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The Hybrid Electric Vehicle Team (HEVT) of Virginia Tech is participating in the EcoCAR 3 Advanced Vehicle Technology Competition series organized by Argonne National Labs (ANL), and sponsored by General Motors (GM) and the U.S. Department of Energy (DOE). EcoCAR 3 is a 4-year collegiate competition that challenges student with redesigning a 2016 Chevrolet Camaro into a hybrid. The five main goals of EcoCAR 3 are to reduce petroleum energy use (PEU) and green house gas (GHG) emissions while maintaining safety, consumer acceptability, and performance, with an increased focus on cost and innovation. HEVT selected a P3 Plug-in Parallel hybrid electric vehicle (PHEV) to meet design goals and competition requirements. This study presents different stages of the vehicle development process (VDP) followed to integrate the HEVT Camaro. This work documents the control system development process up to Year 2 of EcoCAR 3. The modeling process to select a powertrain is the first stage in this research. Several viable powertrains and the respective vehicle technical specifications (VTS) are evaluated. The P3 parallel configuration with a V8 engine is chosen because it generated the set of VTS that best meet design goals and EcoCAR 3 requirements. The V8 engine also preserves the heritage of the Camaro, which is attractive to the established target market. In addition, E85 is chosen as the fuel for the powertrain because of the increased impact it has on GHG emissions compared to E10 and gasoline. The use of advanced methods and techniques like model based design (MBD), and rapid control prototyping (RCP) allow for faster development of engineering products in industry. Using advanced engineering techniques has a tremendous educational value, and these techniques can assist the development of a functional and safe hybrid control system. HEVT has developed models of the selected hybrid powertrain to test the control code developed in software. The strategy developed is a Fuzzy controller for torque management in charge depleting (CD) and charge sustaining (CS) modes. The developed strategy proves to be functional without having a negative impact of the energy consumption characteristics of the hybrid powertrain. Bench testing activities with the V8 engine, a low voltage (LV) motor, and high voltage (HV) battery facilitated learning about communication, safety, and functionality requirements for the three components. Finally, the process for parallel development of models and control code is presented as a way to implement more effective team dynamics. / Master of Science

Defining key parameters for a charge sustaining supervisory (torque split) control strategy as well as an engine and catalyst warm-up strategy for a Split Parallel Architecture Extended-Range Electric Vehicle (SPA E-REV) is accomplished through empirically and experimentally measuring vehicle tailpipe emissions and energy consumption for two distinct control strategies. The results of the experimental testing and analysis define how the vehicle reduces fuel consumption, petroleum energy use and greenhouse gas emissions while maintaining low tailpipe emissions. For a SPA E-REV operating in charge sustaining mode with the engine providing net propulsive energy, simply operating the engine in regions of highest efficiency does not equate to the most efficient operation of the vehicle as a system and can have adverse effects on tailpipe emissions. Engine and catalyst warm-up during the transition from all-electric charge depleting to engine-dominant charge sustaining modes is experimentally analyzed to evaluate tailpipe emissions. The results presented are meant to define key parameters for a high-level torque-split strategy and to provide an understanding of the tradeoffs between low energy consumption and low tailpipe emissions. The literature review gives a background of hybrid and plug-in hybrid vehicle control publications including tailpipe emissions studies, but does not include experimental results and comparisons of supervisory strategies designed for low fuel consumption and low tailpipe emissions the SPA E-REV architecture. This paper details the high-level control strategy chosen for balancing low energy consumption and low tailpipe emissions while the engine is operating. Vehicle testing data from a chassis dynamometer is presented in support of the research. / Master of Science

For years the trend in the automotive industry has been toward more complex electronic control systems. The number of electronic control units (ECUs) in vehicles is ever increasing as is the complexity of communication networks among the ECUs. Increasing fuel economy standards and the increasing cost of fuel is driving hybridization and electrification of the automobile. Achieving superior fuel economy with a hybrid powertrain requires an effective and optimized control system. On the other hand, mathematical modeling and simulation tools have become extremely advanced and have turned simulation into a powerful design tool. The combination of increasing control system complexity and simulation technology has led to an industry wide trend toward model based control design. Rather than using models to analyze and validate real world testing data, simulation is now the primary tool used in the design process long before real world testing is possible. Modeling is used in every step from architecture selection to control system validation before on-road testing begins. The Hybrid Electric Vehicle Team (HEVT) of Virginia Tech is participating in the 2011-2014 EcoCAR 2 competition in which the team is tasked with re-engineering the powertrain of a GM donated vehicle. The primary goals of the competition are to reduce well to wheels (WTW) petroleum energy use (PEU) and reduce WTW greenhouse gas (GHG) and criteria emissions while maintaining performance, safety, and consumer acceptability. This paper will present systematic methodology for using model based design techniques for architecture selection, control system design, control strategy optimization, and controller validation to meet the goals of the competition. Simple energy management and efficiency analysis will form the primary basis of architecture selection. Using a novel method, a series-parallel powertrain architecture is selected. The control system architecture and requirements is defined using a systematic approach based around the interactions between control units. Vehicle communication networks are designed to facilitate efficient data flow. Software-in-the-loop (SIL) simulation with Mathworks Simulink is used to refine a control strategy to maximize fuel economy. Finally hardware-in-the-loop (HIL) testing on a dSPACE HIL simulator is demonstrated for performance improvements, as well as for safety critical controller validation. The end product of this design study is a control system that has reached a high level of parameter optimization and validation ready for on-road testing in a vehicle. / Master of Science

With increasing costs of fossil fuels and intensified environmental awareness, low carbon vehicles, including hybrid electric vehicles (HEVs), are becoming more popular for car buyers due to their lower running costs. HEVs are sensitive to the driving conditions under which they are used however, and real-world driving can be very different to the legislative test cycles. On the road there are higher speeds, faster accelerations and more changes in speed, plus additional factors that are not taken into account in laboratory tests, all leading to poorer fuel economy. Future trends in the automotive industry are predicted to include a large focus on increased hybridisation of passenger cars in the coming years, so this is an important current research area. The aims of this project were to determine the energy consumption of a HEV in real-world driving, and investigate the differences in this compared to other standard drive cycles, and also compared to testing in laboratory conditions. A second generation Toyota Prius equipped with a GPS (Global Positioning System) data logging system collected driving data while in use by Loughborough University Security over a period of 9 months. The journey data was used for the development of a drive cycle, the Loughborough University Urban Drive Cycle 2 (LUUDC2), representing urban driving around the university campus and local town roads. It will also have a likeness to other similar driving routines. Vehicle testing was carried out on a chassis dynamometer on the real-world LUUDC2 and other existing drive cycles for comparison, including ECE-15, UDDS (Urban Dynamometer Driving Schedule) and Artemis Urban. Comparisons were made between real-world driving test results and chassis dynamometer real-world cycle test results. Comparison was also made with a pure electric vehicle (EV) that was tested in a similar way. To verify the test results and investigate the energy consumption inside the system, a Prius model in Autonomie vehicle simulation software was used. There were two main areas of results outcomes; the first of which was higher fuel consumption on the LUUDC2 compared to other cycles due to cycle effects, with the former having greater accelerations and a more transient speed profile. In a drive cycle acceleration effect study, for the cycle with 80% higher average acceleration than the other the difference in fuel consumption was about 32%, of which around half of this was discovered to be as a result of an increased average acceleration and deceleration rate. Compared to the standard ECE-15 urban drive cycle, fuel consumption was 20% higher on the LUUDC2. The second main area of outcomes is the factors that give greater energy consumption in real-world driving compared to in a laboratory and in simulations being determined and quantified. There was found to be a significant difference in fuel consumption for the HEV of over a third between on-road real-world driving and chassis dynamometer testing on the developed real-world cycle. Contributors to the difference were identified and explored further to quantify their impact. Firstly, validation of the drive cycle accuracy by statistical comparison to the original dataset using acceleration magnitude distributions highlighted that the cycle could be better matched. Chassis dynamometer testing of a new refined cycle showed that this had a significant impact, contributing approximately 16% of the difference to the real-world driving, bringing this gap down to 21%. This showed how important accurate cycle production from the data set is to give a representative and meaningful output. Road gradient was investigated as a possible contributor to the difference. The Prius was driven on repeated circuits of the campus to produce a simplified real-world driving cycle that could be directly linked with the corresponding gradients, which were obtained by surveying the land. This cycle was run on the chassis dynamometer and Autonomie was also used to simulate driving this cycle with and without its gradients. This study showed that gradient had a negligible contribution to fuel consumption of the HEV in the case of a circular route where returning to the start point. A main factor in the difference to real-world driving was found to be the use of climate control auxiliaries with associated ambient temperature. Investigation found this element is estimated to contribute over 15% to the difference in real-world fuel consumption, by running the heater in low temperatures and the air conditioning in high temperatures. This leaves a 6% remainder made up of a collection of other small real-world factors. Equivalent tests carried out in simulations to those carried out on the chassis dynamometer gave 20% lower fuel consumption. This is accounted for by degradation of the test vehicle at approximately 7%, and the other part by inaccuracy of the simulation model. Laboratory testing of the high voltage battery pack found it constituted around 2% of the vehicle degradation factor, plus an additional 5% due to imbalance of the battery cell voltages, on top of the 7% stated above. From this investigation it can be concluded that the driving cycle and environment have a substantial impact of the energy use of a HEV. Therefore they could be better designed by incorporating real-world driving into the development process, for example by basing control strategies on real-world drive cycles. Vehicles would also benefit from being developed for use in a particular application to improve their fuel consumption. Alternatively, factors for each of the contributing elements of real-world driving could be included in published fuel economy figures to give prospective users more representative values.

Optimal control of energy flows in a Hybrid Electric Vehicle (HEV) is crucial to maximising the benefits of hybridisation. The problem is complex because the optimal solution depends on future power demands, which are often unknown. Stochastic Dynamic Programming (SDP) is among the most advanced control optimisation algorithms proposed and incorporates a stochastic representation of the future. The potential of a fully developed SDP controller has not yet been demonstrated on a real vehicle; this work presents what is believed to be the most concerted and complete attempt to do so. In characterising typical driving patterns of the target vehicles this work included the development and trial of an eco-driving driver assistance system; this aims to reduce fuel consumption by encouraging reduced rates of acceleration and efficient use of the gears via visual and audible feedback. Field trials were undertaken using 15 light commercial vehicles over four weeks covering a total of 39,300 km. Average fuel savings of 7.6% and up to 12% were demonstrated. Data from the trials were used to assess the degree to which various legislative test cycles represent the vehicles’ real-world use and the LA92 cycle was found to be the closest statistical match. Various practical considerations in SDP controller development are addressed such as the choice of discount factor and how charge sustaining characteristics of the policy can be examined and adjusted. These contributions are collated into a method for robust implementation of the SDP algorithm. Most reported HEV controllers neglect the significant complications resulting from extensive use of the electrical powertrain at high power, such as increased heat generation and battery stress. In this work a novel cost function incorporates the square of battery C-rate as an indicator of electric powertrain stress, with the aim of lessening the affliction of real-world concerns such as temperatures and battery health. Controllers were tested in simulation and then implemented on a test vehicle; the challenges encountered in doing so are discussed. Testing was performed on a chassis dynamometer using the LA92 test cycle and the novel cost function was found to enable the SDP algorithm to reduce electrical powertrain stress by 13% without sacrificing any fuel savings, which is likely to be beneficial to battery health.

Depuis une dizaine d’années, les constructeurs et les grands groupesdu secteur de l’automobile se sont mobilisés autour de la recherche et dudéveloppement de nouveaux prototypes de véhicules économes (moins consommateursd’énergie) et propres (moins de rejets de polluants) tels queles véhicules hybrides et tout électriques. C’est une nouvelle mutation. Ellefait profondément évoluer l’automobile, d’une architecture de propulsionthermique, devenue maîtrisée mais fortement polluante, vers une tractionélectrique ou hybride plus complexe et peu, voire pas du tout, maîtrisée ;le nombre de composants (sources d’énergie, actionneurs, contrôleurs, calculateurs,...) devient important, de nature multidisciplinaire et possédantbeaucoup de non linéarités. De plus, faute de maturité dans ce domaine, àce jour l’industrie de l’automobile ne possède pas encore les connaissancessuffisantes nécessaires à la modélisation, à la simulation et à la conceptionde ces nouveaux véhicules et plus particulièrement les dispositifs relatifs auxsources d’énergie et aux différents actionneurs de propulsion.Les travaux de cette thèse visent à donner des méthodes de conceptiond’une chaine de traction hybride et d’en gérer la gestion de l’énergie. Lathèse s’appuie sur l’exemple de la conception et la gestion de l’énergie d’unvéhicule hybride basé sur une pile à combustible et des batteries.Dans un premier temps, un méthode de dimensionnement des composantsde la chaine de traction est présentée : Elle consiste en l’étude statistique decycle de conduite générés pseudo aléatoirement représentatif de la conduiteen condition réelle de véhicule. Un générateur de cycle de conduite à été créeet est présenté, et la méthode de dimensionnement de la source primaire, iciune pile a combustible, ainsi que le source secondaire de puissance, ici desbatteries, est détaillée. Un exemple est pris pour illustrer cette méthode avecla conception d’un véhicule de type camion poubelle décrivant des cycles deconduites urbains à arrêts fréquents.Dans un second temps, la gestion de l’énergie de la chaine de traction hybridesérie est étudiée : une gestion de l’énergie “offline” est présentée, basé surl’optimisation par programmation dynamique. Cette optimisation permetd’avoir le découpage de la puissance par les deux sources de la chaine detraction de manière optimal pour un cycle précis. De part l’aspect déterministede la programmation dynamique, les résultats servent de référence quant aufuturs développements de gestion temps réel.Un contrôleur temps réel basé sur la logique floue est ainsi exposé et lesrésultats sont comparés par rapport à la gestion “offline”. Le contrôleurest ensuite optimisé et rendu adaptatif par un algorithme génétique et unalgorithme de reconnaissance de type de profil routier.Enfin, une introduction à la gestion de l’énergie dans les véhicules hybrides de type : “plug in” est présentée : Elle repose sur le principe de la déterminationde la distance restante à parcourir par la reconnaissance de la destination àl’aide d’une matrice de probabilité de Markov. / Hybrid electric vehicle have known a quickly grow in the last 10 years.Between conventional vehicles which are criticized for their CO2 emissionand electric vehicles which have a big issue about autonomy, hybrid electricones seems to be a good trade of. No standard has been set yet, and the architecturesresulting of theses productions vary between brands. Nevertheless,all of them are design as a thermal vehicle with battery added which leadsto bad sizing of the component, specially internal combustion engine andbattery capacity. Consequently, the control strategy applied to its componentshas a lot of constraints and cannot be optimal.This thesis investigate a new methodology to design and control a hybridelectric vehicle. Based on statistical description of driving cycle and the generationof random cycle, a new way of sizing component is presented. Thecontrol associate is then determined and apply for different scenarios : firstlya heavy vehicle : A truck and then a lightweight vehicle. An offline controlbased on the optimization of the power split via a dynamic programmingalgorithm is presented to get the optimal results for a given driving cycle.A real time control strategy is then define with its optimization for a givenpatterns and compared to the offline results. Finally, a new control of plug inhybrid electric vehicle based on destination predictions is presented.

This thesis deals with thermal management aspects of electric machinery used in high-performance  applications  with  particular  focus put  on electric machines designed for hybrid electric vehicle applications. In the first part of this thesis,  new thermal models of liquid (water and oil) cooled electric machines are proposed.  The proposed thermal models are based on a combination of lumped parameter (LP)  and numerical methods. As  a first  case study,  a permanent-magnet  assisted  synchronous reluctance machine (PMaSRM) equipped with a housing water jacket is considered.  Particular focus is put on the stator winding and a thermal model is proposed that divides the stator slot into a number of elliptical copper and impregna- tion layers.  Additionally, an analysis, using results from a proposed simplified thermal finite element (FE)  model representing only a single slot of the sta- tor and its corresponding end winding, is presented in which the number of layers and the proper connection between the parts of the LP thermal model representing the end winding and the active part of winding are determined. The approach is attractive due to its simplicity  and the fact  that it closely models the actual temperature distribution for common slot geometries.  An oil-cooled induction machine where the oil is in direct contact with the stator laminations  is also considered.  Here, a multi-segment structure is proposed that  divides  the  stator,  winding and cooling  system  into  a number  of an- gular  segments.   Thereby,  the  circumferential  temperature  variation  due to the  nonuniform distribution  of the  coolant  in the  cooling  channels  can be predicted. In the  second part  of this  thesis,  the  thermal  impact  of using  different winding impregnation  and steel  lamination  materials  is  studied.   Conven- tional varnish, epoxy and a silicone based thermally conductive impregnation material are investigated and the resulting temperature distributions in three small induction machines are compared. The thermal impact of using different steel lamination materials is investigated by simulations using the developed thermal  model  of the water  cooled  PMaSRM. The  differences  in alloy con- tents and steel lamination thickness are studied separately and a comparison between the produced iron losses and the resulting hot-spot temperatures is presented. Finally, FE-based approaches  for  estimating  the  induced  magnet  eddycurrent losses in the rotor of the considered PMaSRM are reviewed and compared in the  form  of a case  study  based on simulations.   A  simplified three-dimensional  FE model  and an analytical  model,  both  combined  with time-domain 2D FE analysis, are shown to predict the induced eddy current losses with a relatively good accuracy compared to a complete 3D FE based model.  Hence, the two simplified approaches are promising which motivates a possible future experimental verification. / <p>QC 20130528</p>