The electrification of passenger vehicles has been a step towards the reduction of greenhouse gas emissions by automobiles; however, in the United States many plug-in hybrid electric vehicles (PHEVs) and battery electric vehicles (BEVs) must still be plugged in to a grid that is heavily reliant on the burning of fossil fuels to charge. The goal of this thesis is to investigate how to develop a system capable of fully charging a PHEV using only alternative and/or regenerative energy sources. In developing such a system, various alternative and regenerative energy sources were investigated with the intent of reaching a specified daily energy goal; sufficient to charge a PHEV. These energy sources were evaluated based upon criteria such as novelty, ability to reach desired daily energy goal, applicability to BEV/PHEV, etc. The primary technological categories considered include but are not limited to regenerative and solar technologies. The evaluation of technologies indicated that a major opportunity lies in solar technologies, and in particular concentrated photovoltaics. Design alternatives for a concentrated photovoltaic system capable of reaching the desired energy goal are described. The design alternatives utilize Fresnel lenses as a means of concentrating a large area of sunlight onto an array of photovoltaics affixed to a vehicle. Various tracking mechanisms for the concentrating systems have been outlined to meet given design criteria. 3-D ray tracing algorithms have been developed to determine the path of the tracking mechanisms depending upon the time of year and on the geographic location. The same algorithms have been used in conjunction with typical meteorological year data to determine the expected output of the concentrating systems based upon the solar resource and solar angles at a specific place and time. The findings suggest that a concentrated photovoltaic system designed specifically for charging an electrified vehicle may generate sufficient energy over the course of a day to power a typical driver’s trips. However, for such a concentrating system to be commercially feasible there are still many design challenges to be overcome. Design limitations and implications for further research are discussed.

A comprehensive framework is presented for the integration of electrified transportation and renewable energy through repurposing batteries of plug-in electric vehicles towards a sustainable energy future. The framework considers future market penetration scenarios of plug-in electric vehicles, availability of batteries at their vehicular end of life, and the storage capacity required to generate base-load wind power in the region of study. The objective is to develop a model that can be used as a policy tool to investigate how different scenarios and pertinent parameters can effectively meet the challenges of sustainability in the energy and transportation sectors when the ultimate goal is to simultaneously displace fossil fuels with new generation of low-cost intermittent renewable energy. A sample case study is performed for Canada to investigate and verify the performance of the model. The analysis shows that the proposed approach can further improve the energy sustainability performance of Canada in 2050 by 1.65–4.11%, depending on the confidence level and in addition to electrification of transportation. In the framework, a statistical algorithm is developed to calculate the capacity of an energy storage system required for delivering base-load electricity for a wind farm in the future electric grids. The algorithm contributes towards the goal of utilizing low- cost intermittent wind energy to base-load power generation in the future electric grids. The introduced algorithm presents three methods to perform the sizing calculations each representing a scenario associated with the stages of the wind energy industry. The results of the studied case are applied to estimate the cost of wind energy to produce rated power at different confidence levels, which show cost-effectiveness and less intermittency on the power systems allowing for larger penetrations of renewables. Advanced statistical methods are used to more accurately characterize the operational wind power output versus manufacturer’s power curve. This is essential for effective integration of wind power into the power systems. Four parametric and nonparametric models are applied to estimate the power curve of wind turbines based on the available operational wind power data. The results of this study suggest that the penalized spline regression method presents a better performance over the other analyzed methods. Finally, an experimental testing is performed in laboratory to show the proof of concept of the capacity degradation of used batteries of plug-in electric vehicles in stationary applications using a 25 kWh repurposed energy storage system obtained from a taxi fleet in their “as-is” condition. The proposed comprehensive framework herein presents an approach leading to a sustainable transportation system by providing low-cost renewable energy, and can be used as a gold standard to compare other policies like hydrogen energy technologies. / October 2015

Electric vehicles can play an important role in a future sustainable road transport system and many Swedish politicians would like to see them implemented faster. This is likely desirable to reach the target of a fossil independent vehicle fleet in Sweden by 2030 and a greenhouse gas neutral Swedish society no later than 2050. However, to reach both these targets, and certainly to support the full scope of sustainability, it is important to consider the whole life-cycle of the vehicles and also the interaction between the transport sector and other sectors. So far, there are no plans for transitions towards a sustainable transport system applying a sufficiently wide systems perspective, in Sweden or elsewhere. This implies a great risk for sub-optimizations. The overall aim of this work is to elaborate methodological support for development of sustainable personal road transport systems that is informed by a strategic sustainable development perspective. The Framework for Strategic Sustainable Development (FSSD) is used as a foundation for the work to ensure a sufficiently wide systems perspective and coordinated collaboration across disciplines and sectors, both in the research and application. Maxwell’s Qualitative Research Design and the Design Research Methodology are used as overall guides for the research approach. Specific research methods and techniques include literature studies, action research seminars, interviews, and measurements of energy use, costs, and noise. Moreover, a case study on the conditions for a breakthrough for vehicles in southeast Sweden has been used as a test and development platform. Specific results include a preliminary vision for electrical vehicles in southeast Sweden, framed by the principled sustainability definition of the FSSD, an assessment of the current reality in relation to that vision, and proposed solutions to bridge the gap, organized into a preliminary roadmap. The studies show that electric vehicles have several sustainability advantages even when their whole life-cycle is considered, provided that they are charged with electricity from new renewable sources. Electrical vehicles also imply a low total cost of ownership and could promote new local ‘green jobs’ under certain conditions. Particularly promising results are seen for electric buses in public transport. As a general result, partly based on the experiences from the specific case, a generic community planning process model is proposed and its usefulness for sustainable transport system development is discussed. The strategic sustainable development perspective of this thesis broadens the analysis beyond the more common focus on climate change issues and reduces the risk of sub-optimizations in community and transport system development. The generic support for multi-stakeholder collaboration could potentially also promote a more participatory democratic approach to community development, grounded in a scientific foundation. Future research will explore specific decision support systems for sustainable transport development based on the generic planning process model. / GreenCharge

A problem of non-acceptance of new information technologies becomes a predominant obstacle that results in companies’ losses and represents an arena of avid debate for researchers. Hereof this netnographic study explores changes in the individual beliefs that contribute to new information system acceptance such as autopilot in the light of the Technology Acceptance model (TAM). The research takes place within three automobile communities related to Tesla Motors and uses content analysis for its collected data. Based on the findings new influencers on individual beliefs emerge hence the research proposes to incorporate these determinants into the adopted TAM model. This study has theoretical, practical and methodological contributions.

<p>Ever-increasing need for freight transportation and mounting environmental concerns call for a cleaner and more efficient energy source. Hybrid electric vehicles have shown potential to reduce both petroleum usage as well as harmful emissions. In this thesis, a newly developed series hybrid electric powertrain by a small start-up company is studied on a route between Florence, Kentucky and Cambridge, Ohio hubs to evaluate potential fuel savings due to hybridization.</p> <p> </p> <p>An experimental testing protocol to calculate fuel economy has been developed and the real-world fuel economy of this hybrid electric powertrain is calculated. A vehicle simulation model representing the experimental powertrain is created in Autonomie and this vehicle model is simulated on three distinct drive cycles obtained from experimental testing phase. These results are compared with a conventional class 8 truck to evaluate fuel savings. The simulation analysis indicates that fuel economy of hybrid is better on only one of the three drive cycles under consideration. Further, it is determined that the existing powertrain does not meet the gradeability criterion. To remedy this, a series electric hybrid powertrain with different compo-</p> <p>nent sizes is then modeled and simulated on the same drive cycles. The modified powertrain is found to result in fuel economy improvement on all three drive cycles considered while also meeting the gradeability requirement. The effect of drive cycle on fuel economy of a hybrid powertrain is also studied in this thesis.</p><br>

Thesis (M.S.)--West Virginia University, 2007. / Title from document title page. Document formatted into pages; contains xiii, 112 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 107-112).

Thesis (M.S.)--Oregon State University, 2007. / Printout. Includes bibliographical references (leaves 97-99). Also available on the World Wide Web.

Range anxiety is a relatively new concept which is defined as the fear of running out of power when driving an electric vehicle. To decrease range anxiety you can increase the battery size or decrease the minimum state of charge, the least amount of power that can be left in the battery, or to expand the available fast charging infrastructure. But is that economical feasible or even technically possible in today’s society? In this project we have used a theoretical model for estimating range anxiety and have simulated the average electricity consumption using two different kinds of electric vehicles, to see how often they reach range anxiety according to a specific definition of range anxiety implemented in this model. The simulations were performed for different scenarios in order to evaluate the effect of different parameters on range anxiety. The result that we got were that range anxiety can be decreased with bigger batteries but to get range anxiety just a few times a year you have to use battery sizes which aren’t economical feasible today. Despite the shortcomings of todays electric vehicles there are promising new and future technologies such as better batteries which might help alleviate range anxiety for electric vehicle owner. The conclusion from this study is that in the present fleet of electric vehicles is in need of more charging stations and faster charging to get by the problem with range anxiety and having a chance to compete with gasoline and diesel vehicles.

Power-split hybrid-electric vehicles (HEVs) provide two power paths between the internal combustion (IC) engine and the driven wheels through gearing and electric machines (EMs) composing an electrically variable transmission (EVT). EVTs allow IC engine control such that rotational speed is independent of vehicle speed at all times. By breaking the rigid mechanical connection between the IC engine and the driven wheels, EVTs allow the IC engine to operate in the most efficient region of its characteristic brake specific fuel consumption (BSFC) map. If the most efficient IC engine operating point produces more power than is requested by the driver, the excess IC engine power can be stored in the energy storage system (ESS) and used later. Conversely, if the most efficient IC engine operating point does not meet the power request of the driver, the ESS delivers the difference to the wheels through the EMs. Therefore with an intelligent supervisory control strategy, power-split architectures can advantageously combine traditional series and parallel power paths. In the first part of this work, two different power-split HEV powertrains are compared using a two-term cost function and steady-state backward-looking simulation (BLS). BLS is used to find battery power management strategies that result in minimized fuel consumption over a user-defined drive-cycle. The supervisory control strategy design approach amounts to an exhaustive search over all kinematically admissible input operating points, leading to a minimized instantaneous cost function. While the approach provides a valuable comparison of two architectures, non-ideal engine speed fluctuations result. Therefore, in the second part of the work, two approaches for designing control strategies with refined IC engine speed transitions are investigated using high-fidelity forward-looking simulation (FLS). These two approaches include: i) smoothing the two-term cost function optimization results, and ii) introducing a three-term cost function. It is found that both achieve operable engine speed transitions, and result in fuel economy (FE) estimates which compare well to previous BLS results. It is further found that the three-term cost function finds more efficient operating points than the smoothed two-term cost function approach. From the investigations carried out in parts one and two of this work, a two-phase control strategy development process is suggested where control strategies are generated using efficient steady-state BLS models, and then further tested and verified in high-fidelity FLS models. In conclusion, the FLS results justify the efficacy of the two-phased process, suggesting rapid and effective development of implementable power-split HEV supervisory control strategies.

Thesis (M. S.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2010. / Committee Chair: Dr. A. P. Meliopoulos; Committee Member: Dr. David Taylor; Committee Member: Dr. Ronald Harley; Committee Member: Dr. Shijie Deng. Part of the SMARTech Electronic Thesis and Dissertation Collection.