The growth of the market for electric vehicles (EVs) is increasing each year with record numbers of newly registered electric vehicles in 2022. Electric vehicles are considered the key component of a sustainable transportation sector. The knowledge of influential factors on purchase decisions for new EVs is high. The research attention within the field has been huge over the last decade. As the number of EVs in the transport sector increases, the number of used EVs is increasing. However, basically no research about influential factors for purchase decisions of used EVs can be found. As the prices of new EVs are high, the market for such vehicles is constrained to certain consumer groups. To succeed with the transformation of the transport sector, more consumer groups need to have access to EVs, which can be accomplished with a well-established market for used EVs. The knowledge about financial factors for used EVs need to increase. The purpose of this study is to understand if well-known financial factors influencing purchase decisions for new EVs have similar effects on purchase decisions for used EVs. As in previous studies, this study applies a quantitative research approach where an online survey has been designed with liker-scale questions. A total of 90 respondents in varying age groups answered the survey based on five categories of financial factors: financial incentives, purchasing price, operational costs, maintenance costs, and residual value. The data has been analyzed using Spearman correlation, principal component analysis (PCA), and ordered logistic regression. The Spearman correlation found positive significance between the financial factors and the purchase intention of new and used EVs. The factors identified in the PCA are in line with the expected factors as the predefined research model. The ordered logistic regression could however support significant relation with purchase intensions of new EVs the aspect of financial incentives and residual value. For used EVs the regression was not successful. This study shows that the influence of financial incentives on the purchase intention of EVs, are similar to both new EVs as for used EVs. This result is however based on a small data sample that is much smaller than previous studies. For future research it is important to retrieve a larger data sample to improve reliability of the result. The regression analysis did not support the analytical outcome of the Spearman correlation and it needs to be further analyzed why a significant regression model could not be defined in relation to used EVs.

The future success of chargeable vehicles will, among other factors, depend on their charging costs and their ability to charge with minimal disturbances to the national, local and household electrical grid. To be able to minimize costs and schedule charging sessions, there has to be knowledge of how the charging power varies with time. This is called charging profile. A number of charging profiles for a Volvo V60 plug‑in hybrid electric vehicle have been recorded. For charging currents above 10 A they prove to be more complex than are assumed in most current research papers.   The charging profiles are used together with historical electricity prices to calculate charging costs for 2013 and 2014. Charging is assumed to take place during the night, between 18:00 and 07:00, with the battery being totally depleted at 18:00. By using a timer to have the charging start at 01:00, instead of immediately at 18:00, annual charging costs are reduced by approximately 7 to 8%. By using dynamic programming to optimize the charging sessions, annual charging costs are reduced by approximately 10 to 11%. An interesting issue regarding dynamic programming was identified, namely when using a limited set of predetermined discrete control signals, interpolation returns unrealizable cost-to-go values. This occurs specifically for instances crossing the zero cost-to-go area boundary.   It is concluded that the mentioned savings are realizable, via implementing timers or optimization algorithms into consumer charging stations. Finally, by using these decentralized charging planning tools and seen from a power usage perspective, at least 30% of the Swedish vehicle fleet could be chargeable and powered by the electrical grid.

To make a compelling case for government incentives as a stimulus for alternative fuel vehicle adoption, this thesis assesses the preliminary impacts associated with the elimination of Georgia’s income tax credits for low-emission and zero-emission vehicle purchases. The thesis identifies policy factors that appear to impact alternative fuel vehicle (AFV) adoption in the United States, with a focus on government incentives. Specific policy factors are discussed in the context of state and federal laws. For Georgia, motor vehicle registrations were collected to track AFV adoption rates before and after the change in law. Electric and hybrid vehicle registrations in Georgia have plummeted since the income tax credits were eliminated on June 30, 2015. Income tax credit data were collected to chart the significant increase in zero-emission and low-emission vehicle purchases and leases since electric vehicles started flooding the market. The primary outcome of this research is a set of distinct, measurable policy factors that influence AFV adoption in the United States. The factors identified include: 1) reward amount to income ratio, 2) ease of policy comprehension, 3) consumer awareness, 4) fuel/vehicle coverage of incentives, 5) incentive user groups, 6) forms of incentives (grants, income tax credits, etc.), 7) number of incentives available, and 8) dollar values of incentives. The conclusion presents factors for use in choice model estimation. These factors should be useful by policymakers who are trying to understand the true value of government incentives for alternative fuel vehicles.

Energy and transportation are topics of great importance to global sustainable development.  Tesla Motor Corporation is an electric vehicle company with the objective to “accelerate the world’s transition to sustainable energy” (Musk, 2016).  This thesis, a media discourse analysis, examines media texts concerning Tesla Motors to provide a better understanding of the company’s hitherto success in penetrating the automotive market.  Qualitative analyses of text were utilized to first define the discourse, then to describe how it has contributed to Tesla’s success.  A combination of word frequency analysis, textual analysis for positive modality, and analysis for principles of branding was utilized as method.  A sample set of 15 texts were analyzed to define the macro discourse, and one interview of Elon Musk analyzed closely to explicate how the textual content contributes to the company’s success. The results of a word frequency analysis suggest that Elon Musk’s personal narrative represents the discourse surrounding Tesla Motors and that it contributes to the company’s success via being imbued with authoritybuilding, trust building, and branding content.

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>

Climate change and air pollution pose serious consequences including longer heat waves and sea level rise. California is taking several initiatives to address these problems, calling for an 80% reduction in greenhouse gas emissions by 2050 from 1990 levels. The transportation sector in California has relied heavily on fossil fuels, significantly contributing to the emissions of greenhouse gas emissions. As a result, one of the main technologies the state has been motivating to combat this is the implementation of battery electric vehicles. These vehicles have not started gaining popularity until recently and there are still several market barriers that slow down electric vehicle adoption, such as availability of charging ports. Several other aspects need to be considered, such as the effects on grid demand and supply, as California expects to see a large- scale implementation of electric vehicles. This paper aims to provide information on California's long-term transportation electrification goals and analyze how the state is progressing towards their stated goals, given current electric vehicle market trends, charging availability, and electric demand and supply capacity.