Thesis (M.S.)--West Virginia University, 2009. / Title from document title page. Document formatted into pages; contains viii, 61 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 59-61).

Thesis (M.S.)--Ohio State University, 2005. / Includes bibliographical references (leaves 166-170). Available online via OhioLINK's ETD Center

Dissertation (Ph.D.)--University of Toledo, 2005. / Typescript. "A dissertation [submitted] as partial fulfillment of the requirements of the Doctor of Philosophy degree in Engineering." Bibliography: leaves 61-63.

Thesis (M.S.)--Tennessee Technological University, 2009. / Title from title page screen (viewed on June 29, 2010). Bibliography: leaves 127-131.

The lithium ion battery is today mainly used in cell phonesand laptops. In the future, this kind of battery might beuseful in hybrid electric vehicles as well. In this work, the main focus has been to gain more knowledgeabout the lithium ion battery in the hybrid electric vehicle(HEV) and more precisely to examine what processes of thebattery that are limiting at HEV currents. Both experiments andmathematical modelling have been used. In both cases, highrate, pulsed currents typical for the HEV, have been used. Two manuscripts have been written. Both of them concern thebehaviour of the battery at HEV load, but from different pointsof view. The first one concerns the electrochemical behaviourof the battery at different ambient temperatures. Theexperimental results of this paper were used to validate amathematical model of a Li-ion battery. Possiblesimplifications of the model were identified. In this work itwas also concluded that the mass transfer of the electrolyte isthe main limiting process within the battery. The mass transferof the electrolyte was further studied in the second paper,where the concentration of lithium ions was measured indirectlyusing in situ Raman spectroscopy. This study showed that themathematical description of the mass transfer of theelectrolyte is not complete. One main reason of this issuggested to be the poor description of the physical parametersof the electrolyte. These ought to be further studied in orderto get a better fit between concentration gradients predictedby experiments and model respectively.

Power management strategies have impacts on fuel economy, greenhouse gasses (GHG) emission, as well as effects on the durability of power-train components. This is why different off-line and real-time optimal control approaches are being developed. However, real-time control seems to be more attractive than off-line control because it can be directly implemented for managing power and energy flow inside an actual vehicle. One interesting illustration of these power management strategies is the model predictive control (MPC) based algorithm. Inside an MPC, a cost function is optimized while system constraints are validated in real time. The MPC algorithm relies on dynamic models of the vehicle and the battery. The complexity and accuracy of the battery model are usually neglected to benefit the development of new cost functions or better MPC search algorithms. In fact, the literature does not deal with the impact of the battery model on MPC. This is why this Ph.D. dissertation evaluates the impact of different battery models of a plug-in hybrid electric vehicle (PHEV) through a sensitivity analysis to reach optimal performance for an MPC. The required fidelity of the battery might depend on different factors:the prediction horizon also called look-ahead step time the vehicle states update time the vehicle model step time the objective function The results of simulations show that higher fidelity model improves the capability to predict accurately the battery aging. As the battery pack is currently one of the most expensive components of an electric vehicle and lithium is a limited natural resource, being able to manage precisely the battery aging is a crucial point for both the automotive company and the battery manufacturer. Another important aspect highlighted by this PhD dissertation is that higher battery fidelity model reduces the possibility to violate the SoC constraint, which is greatly desirable. In fact, this constraint is usually defined by battery manufacturers for safety and battery aging management reasons. Last but not least, it has been proven that the impact of the battery modeling for the MPC controller depends on what the objective function aims to optimize. For instance, battery modeling have limited impact if the objective function takes into account the fuel consumption but far more for if it considers the battery degradation.

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The increasing demand for sustainable transportation solutions has led to the rapid evolution of hybrid and electric vehicles. This thesis, undertaken as part of the EcoCAR Mobility Challenge, presents the development and implementation of a control system for a P4 parallel through-the-road hybrid electric vehicle. A comprehensive vehicle model was developed using MATLAB Simulink. This model was used to model overall vehicle performance and component-specific performance throughout the EcoCAR Mobility Challenge and served as the foundation for the subsequent stages of control system development. Extensive component and vehicle testing formed the crux of this thesis. These bench tests provide invaluable data that aided in the implementation of the component control loops into the MAC Team vehicle. On-road vehicle testing further refined the energy management strategy, drivability, and charge sustaining of the high voltage battery. The vehicle control system has 10 control modules that successfully operated the MAC Team vehicle for over 1500km on public roads. The methodologies and findings can guide future projects aiming to optimize hybrid vehicle performance. / Thesis / Master of Applied Science (MASc) / With hybrid electric vehicles and electric vehicles rising in popularity, the EcoCAR Mobility Challenge and its sponsors created an opportunity for McMaster University and 10 other universities across North America to modify a 2019 Chevrolet Blazer into a hybrid electric vehicle. This thesis focuses on the development of the control strategy for the McMaster University vehicle. A mathematical vehicle model was developed to run vehicle simulations in order to evaluate vehicle performance and the performance of individual components. Individual components were tested in order to develop control loops for these components. These control loops and other control modules were used during vehicle testing. On-road vehicle testing refined the vehicle control strategy evidenced by the over 1500km driven on public roads.

This work describes the design, development and research applications of a Modular Automotive Technology Testbed (MATT). MATT is built to evaluate technology components in a hybrid vehicle system environment. MATT can also be utilized to evaluate energy management and torque split control strategies and to produce physical measured component losses and emissions to monitor emissions behavior. In the automotive world, new technology components are first developed on a test bench and then they are integrated into a prototype vehicle for transient evaluation from the vehicle system perspective. This process is expensive and the prototype vehicles are typically inflexible in hardware and software configuration. MATT provides flexibility in component testing through its component module approach. The flexible combination of modules provides a vehicle environment to test and evaluate new technology components. MATT also has an open control system where any energy management and torque split strategy can be implemented. Therefore, the control's impact on energy consumption and emissions can be measured. MATT can also emulate different types and sizes of vehicles. MATT is a novel, unique, flexible and powerful automotive research tool that provides hardware-based data for specific research topics. Currently, several powertrain modules are available for use on MATT: a gasoline engine module, a hydrogen engine module, a virtual scalable energy storage and virtual scalable motor module, a manual transmission module and an automatic transmission module. The virtual battery and motor module uses some component Hardware-In-the-Loop (HIL) principles by utilizing a physical motor powered from the electric grid in conjunction with a real time simulation of a battery and a motor model. This module enables MATT to emulate a wide variety of vehicles, ranging from a conventional vehicle to a full performance electric vehicle with a battery pack that has virtually unlimited capacity. A select set of PHEV research studies are described in this dissertation. One of these studies had an outcome that influenced the PHEV standard test protocol development by SAE. Another study investigated the impact of the control strategy on emissions of PHEVs. Emissions mitigation routines were integrated in the control strategies, reducing the measured emissions to SULEV limits on a full charge test. A special component evaluation study featured in this dissertation is the transient performance characterization of a supercharged hydrogen internal combustion engine on MATT. Four constant air-fuel ratio combustions are evaluated in a conventional vehicle operation on standard drive cycles. Then, a variable air fuel ratio combustion strategy is developed and the test results show a significant fuel economy gain compared to other combustion strategies, while NOx emissions levels are kept low. / Ph. D.

A growing dependence on foreign oil, along with a heightened concern over the environmental impact of personal transportation, had led the U. S. government to investigate and sponsor research into advanced transportation concepts. One of these future technologies is the hybrid electric vehicle (HEV), typically featuring both an internal combustion engine and an electric motor, with the goal of producing fewer emissions while obtaining superior fuel economy. While vehicles such as the Virginia Tech designed and built HEV Lumina have provided a substantial proof of concept for hybrids, there still remains a great deal of research to be done regarding optimization of hybrid vehicle design. This optimization process has been made easier through the use of ADVISOR, a MATLAB simulation program developed by the U. S. Department of Energy's National Renewable Energy Lab. ADVISOR allows one to evaluate different drivetrain and subsystem configurations for both fuel economy and emissions levels. However, the present version of ADVISOR uses a constant power model for the auxiliary power unit (APU) that, while effective for cursory simulation efforts, does not provide for a truly accurate simulation. This thesis describes modifications made to the ADVISOR code to allow for the use of a load sharing APU scheme based on models developed from vehicle testing. Results for typical driving cycles are presented, demonstrating that the performance predicted by the load sharing simulation more closely follows the results obtained from actual vehicle testing. This new APU model also allows for easy adaptation for future APU technologies, such as fuel cells. Finally, an example is given to illustrate how the ADVISOR code can be used for optimizing vehicle design. This work was sponsored by the U.S. Department of Energy under contract XCG-6-16668-01 for the National Renewable Energy Laboratory. / Master of Science