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<p>In this study, the effect of HEVs on traffic related pollution was assessed in the Hamilton CMA. This thesis aimed to combine findings from these two fields in a traffic simulation procedure. By introducing the HEVs in incremental levels to the vehicle travel pattern of more than 700,000 people in the study area, changes occurring in traffic related pollution at different levels were modeled.</p> <p>The hypothetical HEV spatial distribution patterns models were derived through negative binomial regression modeling based on 2006 census data and 2008 vehicle registration data. The distribution of predetermined number of HEVs throughout the Hamilton CMA was completed through these models and results were used to modify input OD matrices for the TRAFFIC program. The link-based emissions were calculated in combination with traffic emission factors for HEV.</p> <p>The results indicated that converting 10% of the total fleet into HEVs was needed to make significant reductions to the HC and CO aggregate emissions in all five models. An important finding with the incremental HEV penetration levels was the approximately linear trend between the percent reduction in the traffic emissions and the percent of HEVs in the total fleet. This trend allows calculations of approximate traffic emission reduction expected with any HEV level. The results illustrating links with more than 10% reduction in traffic emissions indicated that HEV technology as an effective method in dealing with environmental concerns.</p> / Master of Arts (MA)

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

Résumé : Depuis la fin du XXème siècle, l’augmentation du prix du pétrole brut et les problématiques environnementales poussent l’industrie automobile à développer des technologies plus économes en carburant et générant moins d’émissions de gaz à effet de serre. Parmi ces technologies, les véhicules électriques hybrides constituent une solution viable et performante. En alliant un moteur électrique et un moteur à combustion, ces véhicules possèdent un fort potentiel de réduction de la consommation de carburant sans sacrifier son autonomie. La présence de deux moteurs et de deux sources d’énergie requiert un contrôleur, appelé système de gestion d’énergie, responsable de la commande simultanée des deux moteurs. Les performances du véhicule en matière de consommation dépendent en partie de la conception de ce contrôleur. Les véhicules électriques hybrides rechargeables, plus récents que leur équivalent non rechargeable, se distinguent par l’ajout d’un chargeur interne permettant la recharge de la batterie pendant l’arrêt du véhicule et par conséquent la décharge de celle-ci au cours d’un trajet. Cette particularité ajoute un degré de complexité pour ce qui est de la conception du système de gestion d’énergie. Dans cette thèse, nous proposons un modèle complet du véhicule dédié à la conception du contrôleur. Nous étudions ensuite la dépendance de la commande optimale des deux moteurs par rapport au profil de vitesse suivi au cours d’un trajet ainsi qu’à la quantité d’énergie électrique disponible au début d’un trajet. Cela nous amène à proposer une technique d’auto-apprentissage visant l’amélioration de la stratégie de gestion d’énergie en exploitant un certain nombre de données enregistrées sur les trajets antérieurs. La technique proposée permet l’adaptation de la stratégie de contrôle vis-à-vis du trajet en cours en se basant sur une pseudo-prédiction de la totalité du profil de vitesse. Nous évaluerons les performances de la technique proposée en matière de consommation de carburant en la comparant avec une stratégie optimale bénéficiant de la connaissance exacte du profil de vitesse ainsi qu’avec une stratégie de base utilisée couramment dans l’industrie. // Abstract : Since the end of the XXth century, the increase in crude oil price and the environmental concerns lead the automotive industry to develop technologies that can improve fuel savings and decrease greenhouse gases emissions. Among these technologies, the hybrid electric vehicles stand as a reliable and efficient solution. By combining an electrical motor and an internal combustion engine, these vehicles can bring a noticeable improvement in terms of fuel consumption without sacrificing the vehicle autonomy. The two motors and the two energy storage systems require a control unit, called energy management system, which is responsible for the command decision of both motors. The vehicle performances in terms of fuel consumption greatly depend on this control unit. The plug-in hybrid electric vehicles are a more recent technology compared to their non plug-in counterparts. They have an extra internal battery charger that allows the battery to be charged during OFF state, implying a possible discharge during a trip. This particularity adds complexity when it comes to the design of the energy management system. In this thesis, a complete vehicle model is proposed and used for the design of the controller. A study is then carried out to show the dependence between the optimal control of the motors and the speed profile followed during a trip as well as the available electrical energy at the beginning of a trip. According to this study, a self-learning optimization technique that aims at improving the energy management strategy by exploiting some driving data recorded on previous trips is proposed. The technique allows the adaptation of the control strategy to the current trip based on a pseudo-prediction of the total speed profile. Fuel consumption performances for the proposed technique will be evaluated by comparing it with an optimal control strategy that benefits from the exact a priori knowledge of the speed profile as well as a basic strategy commonly used in industry.

Hybrid electric vehicles significantly reduce exhaust emissions and increase fuel economy. Power packs are the most fundamental components in a series powertrain configuration of a hybrid vehicle, which produce the necessary power to run the vehicle. The aim of this project is to design a compact power pack for a series hybrid vehicle, using virtual prototyping. The hybrid electric vehicle characteristics and configurations are analysed, followed by an explanation of the principles of induction machines. A new type of rotary induction machine with an outer rotor construction is designed to be coupled with the novel rotary internal combustion engine with rotating crankcase in order to form the compact power unit for the hybrid vehicle. The starting and generation performance of the designed machine is analysed by an electric machine simulator, called JMAG. ADVISOR software is studied and utilised to simulate the overall vehicle performance, employing different categories of power packs in the powertrain. Results show that the proposed compact power pack has the best performance in terms of fuel economy, emissions and battery charging compared to the existing power unit options. Over the city cycle, fuel economy is increased by up to 47 % with emission reduced by up to 36 % and over the highway cycle, fuel economy is increased by up to 69 % with emission reduced by up to 42 %.

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.

Este trabalho apresenta a contribuição obtida no desenvolvimento de um Gerador de Eletricidade Híbrido (HYBRIDGEN), com tecnologia nacional, focado nos sistemas de terceira geração de energia elétrica híbrido, composto por um módulo de células a combustível tipo PEMFC, associado a um acumulador chumbo ácido. Mostra-se também a sua capacidade de operar em modo contínuo, carga com demanda variável e fator de carga inferior a 50%. Foram abordados quatro temas principais. O primeiro refere-se a um estudo para a melhoria da eficácia na conversão de energia em corrente contínua (cc), ao regular o potencial de saída do conversor cc-cc. A energia é proveniente do módulo de célula a combustível de 1 kWe, equipado com sistema térmico de refrigeração e sistema de alimentação de gases, aqui denominados MCC1. Para tal, foi construído o modelo matemático do sistema conversor de corrente contínua (sistema conversor cc-cc), com solução suportada em equações diferenciais algébricas, ensaios no MCC1, bem como em simulação computacional no programa MATLAB7®. O segundo tema refere-se ao desenvolvimento do projeto e montagem do protótipo do HYBRIDGEN devido à inexistência no mercado brasileiro de um equipamento com as características necessárias tanto para a pesquisa, quanto para uso comercial. Desenvolveu-se uma placa controladora para o acumulador (PCC), os esquemas elétricos, os barramentos e o sistema de relés. Também foi utilizado o MCC1 em desenvolvimento pelo IPEN e ELECTROCELL® com tecnologia 100% nacional. O HYBRIDGEN foi instalado em um sistema móvel. O terceiro tema refere-se à análise de estabilidade do modelo matemático do sistema conversor cc-cc. Utilizou-se de quatro testes de estabilidade, sendo: 1 - pela Resposta em Frequência ao utilizar o Teorema do Mapeamento, de Nyquist; 2 - Lugar das Raízes, de Nyquist; 3 - função de teste Degrau, em pontos de operação e, 4 - função de teste Impulso, em pontos de operação. Por fim, apresentaram-se os resultados dos ensaios de potencial e corrente de uma célula a combustível unitária de 25 cm2, do MCC1, e do HYBRIDGEN. No desenvolvimento dos primeiros testes o MCC1 atingiu 704,55 We, (potência considerada condição predominante de operação). A seguir, demonstrou-se a capacidade do HYBRIDGEN para simultaneamente: alimentar cargas em corrente contínua; carregar o acumulador de 45 Ah; alimentar o inversor de 2 kWe e o autotransformador, para fornecer energia a equipamentos em 12Vcc, 127 Vac e 220Vac, 60 Hz, todos num total de 819,52 We. Esses resultados foram obtidos mesmo com limitações na refrigeração ventilada do MCC1, observadas no decorrer dos testes. Assim, o HYBRIDGEN se mostrou viável tecnicamente, e com grande potencial de uso. / This work presents the contribution obtained by the development of the Hybrid Electric Power Generation System (HYBRIDGEN), with Brazilian technology, focused on third generation hybrid system, composed of the fuel cell type PEMFC, associated with a lead acid battery, and shows its variable load demand continuous mode operate ability with load factor below 50%. Four main themes were addressed. The first refers to a study concerning the to direct current (DC) energy converting efficiency improvement to regulate the dc-dc converter output potential. Power comes from the 1 kWe fuel cell stack, equipped with thermal cooling system and gas supply system, here named MCC1. After that a dc-dc converter system mathematical model was built supported on differential algebraic equations solution, the MCC1 trials, as well as in MATLAB7® program computer simulation. The second theme concerns the HYBRIDGEN prototype project and assembly due to lack on equipment on the Brazilian market with the necessary features for both research and for commercial use. Then, a charge controller card (CCC), wiring diagrams, copper bus and relay system were developed. A MCC1 developed by IPEN and ELECTROCELL® with Brazilian technology was use. The HYBRIDGEN can be installed in a mobile system. The third refers to a study concerning the stability analysis of the dc-dc converter system mathematical model. Four stability tests were addressed, namely: 1- The Frequency Response was used the Nyquist Mapping Theorem, 2 - The Nyquist Root Locus , 3 - The Step Test Function on operating points, and 4 - The Impulse Test Function on operating points. Finally, experiments with a 25 cm2 fuel cell unit, the MCC1 module and the HYBRIDGEN were carried out to, potential and current results. In the first MCC1 tests delivered a power output of 704.55 W (considered dominant operation power). Then, it was demonstrated the HYBRIDGEN ability to 819.52 We supply power, simultaneously: direct current loads, charge a 45Ah battery, a 2 kWe inverter and the autotransformer to supply power 12 Vcc, 127Vac, 220Vac, 60 Hz equipment. These results were achieved despite the MCC1 limit in the cooling system observed during the tests. Then, the HYBRIDGEN could be demonstrated technically feasible, and leading to great potential uses.