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

<div>This thesis proposes an Adaptive Rule-Based Energy Management Strategy (ARBS EMS) for a parallel hybrid electric vehicle (P-HEV). The strategy can effciently be deployed online without the need for complete knowledge of the entire duty cycle in order to optimize fuel consumption. ARBS improves upon the established Preliminary Rule-Based Strategy (PRBS) which has been adopted in commercial vehicles. When compared to PRBS, the aim of ARBS is to maintain the battery State of Charge (SOC) which ensures the availability of the battery over extended distances. The proposed strategy prevents the engine from operating in highly ineffcient regions and reduces the total equivalent fuel consumption of the vehicle. Using an HEV model developed in Simulink, both the proposed ARBS and the established PRBS strategies are compared across eight short duty cycles and one long duty cycle with urban and highway characteristics. Compared to PRBS, the results show that, on average, a 1.19% improvement in the miles per gallon equivalent (MPGe) is obtained with ARBS when the battery initial SOC is 63% for short duty cycles. However, as opposed to PRBS, ARBS has the advantage of not requiring any prior knowledge of the engine efficiency maps in order to achieve optimal performance. This characteristics can help in the systematic aftermarket hybridization of heavy duty vehicles.</div>

There is an increasing interest in sustainability and a growing debate about environmental policy measures aiming at the reduction of green house gas emissions across di erent economic sectors worldwide. The transportation sector is one major greenhouse gas emitter which is heavily regulated to reduce its dependance on oil. These regulations along with the growing customer awareness about global warming has led vehicle manufacturers to seek di erent technologies to improve vehicle e ciencies and reduce the green house gases emissions while at the same time meeting customer's expectation of mobility and exibility. Plug-in hybrid electric vehicles (PHEV) is one major promising solution for a smooth transition from oil dependent transportation sector to a clean electric based sector while not compromising the mobility and exibility of the drivers. In the medium term, plug-in hybrid electric vehicles (PHEV) can lead to signi cant reductions in transportation emissions. These vehicles are equipped with a larger battery than regular hybrid electric vehicles which can be recharged from the grid. For short trips, the PHEV can depend solely on the electric engine while for longer journeys the alternative fuel can assist the electric engine to achieve extended ranges. This is bene cial when the use pattern is mixed such that and short long distances needs to be covered. The plug-in hybrid electric vehicles are well-suited for logistics since they can avoid the possible disruption caused by charge depletion in case of all-electric vehicles with tight time schedules. The use of electricity and fuel gives rise to a new variant of the classical vehicle routing with time windows which we call the plug-in hybrid electric vehicle routing problem with time windows (PHEVRPTW). The objective of the PHEVRPTW is to minimize the routing costs of a eet of PHEVs by minimizing the time they run on gasoline while meeting the demand during the available time windows. As a result, the driver of the PHEV has two decisions to make at each node: (1) recharge the vehicle battery to achieve a longer range using electricity, or (2) continue to the next open time window with the option of using the alternative fuel. In this thesis, we present a mathematical formulation for the plug-in hybrid-electric vehicle routing problem with time windows. We solve this problem using a Lagrangian relaxation and we propose a new tabu search algorithm. We also present the rst results for the full adapted Solomon instances.

The main goal of this thesis study is the optimization of the basic design parameters of hybrid electric vehicle drivetrain components to minimize fuel consumption and emission objectives, together with constraints derived from performance requirements. In order to generate a user friendly and flexible platform to model, select drivetrain components, simulate performance, and optimize parameters of series and parallel hybrid electric vehicles, a MATLAB based graphical user interface is designed. A basic sizing procedure for the internal combustion engine, electric motor, and battery is developed. Pre-defined control strategies are implemented for both types of hybrid configurations. To achieve better fuel consumption and emission values, while satisfying nonlinear performance constraints, multi-objective gradient based optimization procedure is carried out with user defined upper and lower bounds of optimization parameters. The optimization process is applied to a number of case studies and the results are evaluated by comparison with similar cases found in literature.

Hybrid electric vehicle technology has become a preferred method for the automotive industry to reduce environmental impact and fuel consumption of their vehicles. Hybrid electric vehicles accomplish these reductions through the use of multiple propulsion systems, namely an electric motor and internal combustion engine, which allow the elimination of idling, operation of the internal combustion engine in a more efficient manner and the use of regenerative braking. However, the added cost of the hybrid electric system has hindered the sales of these vehicles. A more cost effective design of an electro-hydraulic braking system is presented. The system electro-mechanically controlled the boost force created by the brake booster independently of the driver braking force and with adequate time response. The system allowed for the blending of the mechanical and regenerative braking torques in a manner transparent to the driver and allowed for regenerative braking to be conducted efficiently. A systematic design process was followed, with emphasis placed on demonstrating conceptual design feasibility and preliminary design functionality using virtual and physical prototyping. The virtual and physical prototypes were then used in combination as a powerful tool to validate and develop the system. The role of prototyping in the design process is presented and discussed. Through the experiences gained by the author during the design process, it is recommended that students create physical prototypes to enhance their educational experience. These experiences are evident throughout the thesis presented.

Increased environmental awareness together with new legislative demands on lowered emissions and a rising fuel cost have put focus on increasing the fuel efficiency in new vehicles. Hybridization is a way to increase the efficiency of the powertrain.The Haldex electric Torque Vectoring Device is a rear axle with a built in electric motor, designed to combine all-wheel drive with hybrid functionality. A method is developed for creating a real time control algorithm that minimizes the fuel consumption. First the consumption reduction potential of the system is investigated using Dynamic Programming. A real time control algorithm is then devised that indicates a substantial consumption reduction potential compared to all-wheel drive, under the condition that the assumed and measured efficiencies are accurate. The control algorithm is created using equivalent consumption minimization strategy and is implemented without any knowledge of the future driving mission. Two ways of adapting the control according to the battery state of charge are proposed and investigated. The controller optimizes the torque distribution for the current gear as well as assists the driver by recommending the gear which would give the lowest consumption. The simulations indicate a substantial fuel consumption reduction potential even though the system primarily is an all-wheel drive concept. The results from vehicle tests show that the control system is charge sustaining and the driveability is deemed good by the test-drivers.

Hybrid electric vehicle technology has become a preferred method for the automotive industry to reduce environmental impact and fuel consumption of their vehicles. Hybrid electric vehicles accomplish these reductions through the use of multiple propulsion systems, namely an electric motor and internal combustion engine, which allow the elimination of idling, operation of the internal combustion engine in a more efficient manner and the use of regenerative braking. However, the added cost of the hybrid electric system has hindered the sales of these vehicles. A more cost effective design of an electro-hydraulic braking system is presented. The system electro-mechanically controlled the boost force created by the brake booster independently of the driver braking force and with adequate time response. The system allowed for the blending of the mechanical and regenerative braking torques in a manner transparent to the driver and allowed for regenerative braking to be conducted efficiently. A systematic design process was followed, with emphasis placed on demonstrating conceptual design feasibility and preliminary design functionality using virtual and physical prototyping. The virtual and physical prototypes were then used in combination as a powerful tool to validate and develop the system. The role of prototyping in the design process is presented and discussed. Through the experiences gained by the author during the design process, it is recommended that students create physical prototypes to enhance their educational experience. These experiences are evident throughout the thesis presented.

With increasing interest in energy storage and conversion devices for automobile applications, the necessity to understand and predict life behavior of rechargeable batteries, PEM fuel cells and super capacitors is paramount. These electrochemical devices are most beneficial when used in hybrid configurations rather than as individual components because no single device can meet both range and power requirements to effectively replace internal combustion engines for automobile applications. A system model helps us to understand the interactions between components and enables us to determine the response of the system as a whole. However, system models that are available predict just the performance and neglect degradation. In the first part of the thesis, a framework is provided to account for the durability phenomena that are prevalent in fuel cells and batteries in a hybrid system. Toward this end, the methodology for development of surrogate models is provided, and Pt catalyst dissolution in PEMFCs is used as an example to demonstrate the approach. Surrogate models are more easily integrated into higher level system models than the detailed physics-based models. As an illustration, the effects of changes in control strategies and power management approaches in mitigating platinum instability in fuel cells are reported. A system model that includes a fuel cell stack, a storage battery, power-sharing algorithm, and dc/dc converter has been developed; and preliminary results have been presented. These results show that platinum stability can be improved with only a small impact on system efficiency. Thus, this research will elucidate the importance of degradation issues in system design and optimization as opposed to just initial performance metrics. In the second part of the thesis, modeling of silicon negative electrodes for lithium ion batteries is done at both particle level and cell level. The dependence of the open-circuit potential curve on the state of charge in lithium insertion electrodes is usually measured at equilibrium conditions. Firstly, for modeling of lithium-silicon electrodes at room temperature, the use of a pseudo-thermodynamic potential vs. composition curve based on metastable amorphous phase transitions with path dependence is proposed. Volume changes during lithium insertion/de-insertion in single silicon electrode particle under potentiodynamic control are modeled and compared with experimental data to provide justification for the same. This work stresses the need for experiments for accurate determination of transfer coefficients and the exchange current density before reasoning kinetic hysteresis for the potential gap in Li-Si system. The silicon electrode particle model enables one to analyze the influence of diffusion in the solid phase, particle size, and kinetic parameters without interference from other components in a practical porous electrode. Concentration profiles within the silicon electrode particle under galvanostatic control are investigated. Sluggish kinetics is established from cyclic voltammograms at different scan rates. Need for accurate determination of exchange current density for lithium insertion in silicon nanoparticles is discussed. This model and knowledge thereof can be used in cell-sandwich model for the design of practical lithium ion cells with composite silicon negative electrodes. Secondly, galvanostatic charge and discharge of a silicon composite electrode/separator/ lithium foil is modeled using porous electrode theory and concentrated solution theory. Porosity changes arising due to large volume changes in the silicon electrode with lithium insertion and de-insertion are included and analyzed. The concept of reservoir is introduced for lithium ion cells to accommodate the displaced electrolyte. Influence of initial porosity and thickness of the electrode on utilization at different rates is quantitatively discussed. Knowledge from these studies will guide design of better silicon negative electrodes to be used in dual lithium insertion cells for practical applications.

This dissertation identifies the average treatment effect of state level incentives for hybrid vehicles, identifies individual-level predictors of early adopters, and attempts to understand why states adopt these incentives. These questions are estimated using traditional parametric techniques, logistic regression, difference-in-difference regression, and fixed effects. In particular, this dissertation looks at changes in aggregate demand on two comparison groups: (1) the natural control group, states that did not adopt subsidies, and (2) a constructed control group, states that proposed subsidies during this same time period but did not adopt them. In addition to these parametric models, propensity score matching was used to construct a third comparison group using the models that identified determinants of the policy adoption. These findings were supplemented by exploratory analyses using the individual-level National Household Travel Survey. This multitude of evaluative analyses shows that HOV lane exemptions, if implemented in places with high traffic congestion, were found to impact aggregate demand and an individual's propensity to adopt a hybrid, while traditional incentives had limited impact. These analyses provide insight into why states adopt certain policies and the circumstances in which these incentives are effective. Since people may be motivated by factors other than economic factors, creating effective incentives for energy efficiency technologies may be more challenging than just offsetting the price differential. Instead, customization to the local community's characteristics could help increase the efficacy of such policies.

Energy-storing electrochemical batteries are the most critical components of high energy density storage systems for stationary and mobile applications. Lithium-ion batteries have received considerable interest for hybrid electric vehicles (HEV) because of their high specific energy, but face inherent thermal management challenges that have not been adequately addressed. In the present investigation, a fully coupled electrochemical and thermal model for lithium-ion batteries is developed to investigate the impact of different thermal management strategies on battery performance. This work represents the first ever study of these coupled electrochemical-thermal phenomena in batteries from the electrochemical heat generation all the way to the dynamic heat removal in actual HEV drive cycles. In contrast to previous modeling efforts focused either exclusively on particle electrochemistry on the one hand or overall vehicle simulations on the other, the present work predicts local electrochemical reaction rates using temperature-dependent data on commercially available batteries designed for high rates (C/LiFePO4) in a computationally efficient manner. Simulation results show that conventional external cooling systems for these batteries, which have a low composite thermal conductivity (~1 W/m-K), cause either large temperature rises or internal temperature gradients. Thus, a novel, passive internal cooling system that uses heat removal through liquid-vapor phase change is developed. Although there have been prior investigations of phase change at the microscales, fluid flow at the conditions expected here is not well understood. A first-principles based cooling system performance model is developed and validated experimentally, and is integrated into the coupled electrochemical-thermal model for assessment of performance improvement relative to conventional thermal management strategies. The proposed cooling system passively removes heat almost isothermally with negligible thermal resistances between the heat source and cooling fluid. Thus, the minimization of peak temperatures and gradients within batteries allow increased power and energy densities unencumbered by thermal limitations.