For the purpose of this study, data for low voltage distribution transformer loading in small communities in Maryland was collected from a local electric utility company. Specifically, analysis was done on three distribution transformers on their system. Each of these transformers serves at least one electric vehicle (EV) owner. Of the three transformers analyzed, Transformer 2 serves eight residential homes and has the highest risk of experiencing an overload if all customers purchase at least one EV. Transformer 2 has a nameplate rating of 25kVA (22.5kW assuming a 0.9 power factor). With one EV owner, Transformer 2 has a peak load of 46.82kW during the study period between August 4 and August 17, 2013. When seven additional EVs of different types were added in a simulated scenario, the peak load for Transformer 2 increased from 46.82kW to 89.76kW, which is outside the transformer thermal limit. With the implementation of TOU pricing, the peak load was reduced to 56.71kW from 89.76kW. By implementing a combination of TOU pricing and appliance cycling through demand side management (DSM), the peak load was further reduced to 52.27kW. / Master of Science

The pursuit to combat climate change continues, identifying new methods and technologies for sustainable energy management. Automakers continue developing battery electric vehicles while researchers identify new applications and materials for solar photovoltaics. The continued advancement of technology creates new holes within literature, requiring investigation to understand the unknown. Photovoltaic vehicle integration gained popularity during the 1970s but did not commercialize due to technology, economics, and other factors. By 2021 the idea resurfaced, showcasing commercial and concept vehicles utilizing photovoltaics. The emergence of new transparent photovoltaics presents additional options for vehicle integration but lacks literature analyzing the energy output and economics. The theoretical analysis investigated transparent photovoltaic replacing a vehicle’s windows. The investigation found that transparent photovoltaic vehicle integration generates energy and financial savings. However, due to high system costs and location, the system does not provide a financial payback period like other photovoltaic arrays. Improving cost, location, and other financial parameters create more favorable circumstances for the photovoltaic system. Furthermore, transparent photovoltaics provide energy saving benefits and some return on investment compared to regular glass windows.

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<p>  </p> <p>As consumer adoption and total energy consumption of electric vehicles continues to rapidly increase, it is important to develop comprehensive system modeling frameworks that consider the complex interactions of their mechanical, electrical, and thermal subsystems to guide component technology development. This thesis studies the influence of cabin glass properties on the performance of an electric vehicle thermal system and overall cabin design considerations. The work first builds a generic long-range electric vehicle dynamic thermal system model while considering the system architecture, component sizing, control scheme, and glass properties. This comprehensive system model is used to assess the influence of cabin glass radiative properties on vehicle performance. The system model incorporates simplified models for all salient components in the electric traction drive, cabin HVAC, and battery subsystems, and uses a higher fidelity cabin thermal model that is able to capture the individual properties of the cabin glass used in the vehicle. To study the cabin model in isolation, a heat-up scenario is used to find that a cabin air temperature reduction of 8 °C through the use of different glass properties alone. Additionally, the cabin model is run repeatedly to produce a large data set that is trained using a machine learning regression model. This surrogate regression model that is used to reduce the computational time allowing for fast studies of glass properties and build an application engineering tool. The overall system performance is then evaluated under a dynamic NEDC drive cycle which is repeated until battery depletion to determine a vehicle range. A system validation is done on the HVAC subsystem by using steady-state thermodynamic analysis and comparing to the dynamic system model. This results in good agreement between four different subsystem modeling approaches. The system model is used to study five different glazing design cases, each corresponding to different transmission and reflection properties of the glass, by predicting their impact on the vehicle range. The cases span all theoretically possible glass properties while also enabling inspection of practical glass technologies that are available or under development to be adopted in modern electric vehicles. The influence of glass on vehicle range is then further compared at various locations across the United States to understand and illustrate the effects of ambient conditions and solar load. The system model predicts a vehicle range of 188.5 miles under a high solar loading scenario typical for Phoenix, AZ using traditional glass properties, which increases to a range of 221.6 miles using high-performance glass properties, representing a significant potential gain of 33.1 miles using technologies available on the market today. Under this same loading scenario, the glass properties at their extreme physical limits could theoretically affect the vehicle range by up to 92.5 miles. The influence of the glass properties is location-specific, and the model predicts that using the same glass at different locations can affect the range of vehicle by up to 100.8 miles for traditional glass properties and 73.4 miles for high-performance glass properties. </p>

Electric vehicles (EVs) are increasing in popularity and play an important role in decarbonizing the transport sector. However, a growing EV fleet can cause problems for power grids as the grids are not initially designed for EV charging. The potential of a power grid to accommodate EV loads can be assessed through hosting capacity (HC) analysis. The HC is grid specific and varies, therefore it is necessary to conduct analysis that reflects local conditions and covers uncertainties and correlations over time. This theses aims to investigate the HC for EVs in existing residential power grids, and to gain a better understanding of how it varies based on how the EVs are implemented and charged. The work is in collaboration with a distribution system operator (DSO) and is based on two case studies using real-life data reflecting conditions in Swedish grids. Combinations of different HC assessment methods have been used and the HC is evaluated based on cable loading, transformer loading and voltage deviation. Additionally, the study investigated three distinct charging strategies: charging on arrival, evenly spread charging over whole connection period, and charging at the lowest spot price.  The results show that decisions on acceptable voltage deviation limit can have a large influence on the HC as well as the charging strategy used. A charging strategy based on energy prices resulted in the lowest HC, as numerous EVs charging simultaneously caused high power peaks during low spot price periods. Charging on arrival was the second worst strategy, as the peak power coincided with household demand. The best strategy was to evenly spread out the charging, resulting in fewer violations for 100% EV implementation compared to the other two strategies for 25% EV implementation.  The findings underscore the necessity for coordinated charging controls for EV fleets or diversified power tariffs to balance power on a large scale in order to use the grids efficiently.

Electric vehicles (EVs) are increasing in popularity and play an important role in decarbonizing the transport sector. However, a growing EV fleet can cause problems for power grids as the grids are not initially designed for EV charging. The potential of a power grid to accommodate EV loads can be assessed through hosting capacity (HC) analysis. The HC is grid specific and varies, therefore it is necessary to conduct analysis that reflects local conditions and covers uncertainties and correlations over time. This theses aims to investigate the HC for EVs in existing residential power grids, and to gain a better understanding of how it varies based on how the EVs are implemented and charged. The work is in collaboration with a distribution system operator (DSO) and is based on two case studies using real-life data reflecting conditions in Swedish grids. Combinations of different HC assessment methods have been used and the HC is evaluated based on cable loading, transformer loading and voltage deviation. Additionally, the study investigated three distinct charging strategies: charging on arrival, evenly spread charging over whole connection period, and charging at the lowest spot price.  The results show that decisions on acceptable voltage deviation limit can have a large influence on the HC as well as the charging strategy used. A charging strategy based on energy prices resulted in the lowest HC, as numerous EVs charging simultaneously caused high power peaks during low spot price periods. Charging on arrival was the second worst strategy, as the peak power coincided with household demand. The best strategy was to evenly spread out the charging, resulting in fewer violations for 100% EV implementation compared to the other two strategies for 25% EV implementation.  The findings underscore the necessity for coordinated charging controls for EV fleets or diversified power tariffs to balance power on a large scale in order to use the grids efficiently.

The emergence of wide-bandgap-based (WBG) devices, such as silicon carbide (SiC) and gallium nitride (GaN), have unveiled unprecedented opportunities, enabling the realization of superior power conversion systems. Among the potential areas of advancement are medium-voltage (MV) and high-voltage (HV) applications, due to the growing demand for high-power-density and high-efficiency power electronics converters. These advancements have propelled a wide adoption of electric vehicles (EV), which in the future will require great improvements in the charging time of these vehicles. Thereby, this thesis attempts to address such a challenge and bring about technological improvements, enabling faster, more efficient, and more effective ways of charging an electric vehicle through the application of MV 3.3 kV SiC MOSFETs. The current fast-charging solution involves heavy and bulky MV-LV transformers, which add installation complexity for EV charging stations. However, this thesis presents an alternative power-delivery solution utilizing an MV dual-active-bridge (DAB) converter. The proposed architecture is designed to directly interface with the MV grid for high-power, fast-charging capabilities while eliminating the need for an installation of the MV-LV transformer. The MV DAB converter utilizes 3.3 kV SiC MOSFETs to realize the next 800 V EV charging system, along with an extended zero-voltage-switching (ZVS) scheme, in order to provide an efficient charging strategy across a wide range of battery voltage levels. Lastly, a detailed design comparison analysis of an MV Flyback converter, targeted for the auxiliary power supply for the proposed MV EV charging architecture, is presented. / The field of power electronics, which controls and manages the conversion of electrical energy, is an important topic of discussion, as new technologies like electric vehicles (EV) are quickly emerging and disrupting the current status-quo of vehicle-choice. In order to promote timely and extensive adoption of such an enabling EV technology, it is critical to understand the current challenges involving EV charging stations and seek out opportunities to engender future innovations. Indeed, wide-bandgap (WBG) devices, such as silicon carbide (SiC) and gallium nitride (GaN), have unveiled unprecedented opportunities in enabling the realization of superior power conversion systems. Thus, utilizing these WGB devices in EV charging applications can bring about improved design and development of EV fast chargers that are faster-charging, more efficient, and more effective. Hence, this thesis presents an opportunity in EV charging station applications with the utilization of medium-voltage SiC MOSFETs. Because the current fast-charging solution involves a heavy and bulky transformer, it adds installation complexity for EV charging stations. However, this thesis presents an alternative power-delivery solution that could potentially provide an efficient and fast-charging mechanism of EVs while reducing the size of EV chargers. All things considered, this thesis provides in-depth evaluation-studies of medium-voltage 3.3 kV SiC MOSFET-based power converters, targeted for future fast EV charging applications. The development and design of the hardware prototype is presented in this thesis, along with testing and verification of experimental results.

<p>In recent years lithium-ion battery electric vehicles and stored hydrogen electric vehicles have been developed to address the ever-present threat of climate change and global warming. These technologies have failed to achieve profitability at costs consumers are willing to bear when purchasing a vehicle. IFBattery, Inc. has developed a unique primary battery chemistry which simultaneously produces both electricity and hydrogen-on-demand while being both low cost and without carbon emissions. In order to determine the feasibility of the IFBattery chemistry for mobile applications, a prototype golf cart was constructed as the first public application of IFBattery technology. The legacy lead acid batteries of the prototype golf cart were replaced with an IFBattery chemistry tuned to primarily produce hydrogen-on-demand with supplemental electricity. Hydrogen produced by the IFBattery was purified and then fed into a hydrogen fuel cell where electricity was produced to power the vehicle. Electricity from the IFBattery was converted to the common voltage of the golf cart and also used to power the vehicle. Validation testing of the IFBattery powered golf cart demonstrated favorable results as an alternative to both lithium-ion battery and stored hydrogen technologies, and displayed potential for future applications.</p>

This master‘s thesis pertains to the design of a cargo truck with battery electric drivetrain. The presented design offers a solution which respects the technical requirements of such a vehicle, ergonomic needs of its crew, and demands on the aesthetics of a modern commercial vehicle. In consideration of the chosen drivetrain, this solution is proposed as a concept with an outlook of 10 to 15 years in the future. In keeping with the specified goals, this vehicle offers a novel appearance which attempts to characterize the electric drivetrain with certain visual elements, includes solutions that are readily available or currently in development, and optimizes ergonomics for maximum user comfort and safety.

The Well-To-Wheels (WTW) methodology is widely used for policy making in the transportation sector. In this paper updated WTW calculations are provided, relying on 2013 statistic data, for the carbon intensity (CI) of the European electricity mix; detail is provided for electricity consumed in each EU Member State (MS). An interesting aspect presented is the calculation of the GHG content of electricity traded between Countries, affecting the carbon intensity of the electricity consumed at national level. The amount and CI of imported electricity is a key aspect: a Country importing electricity from another Country with a lower CI of electricity will lower, after the trade, its electricity CI, while importing electricity from a Country with a higher CI will raise the CI of the importing Country. In average, the CI of electricity used in EU at low voltage in 2013 was 447 gCO2eq/kWh, which is the 17% less compared to 2009. Then, some examples of calculation of GHG emissions from the use of electric vehicles (EVs) compared to internal combustion engine vehicles are provided. The use of EVs instead of gasoline vehicles can save (about 60% of) GHG in all or in most of the EU MSs, depending on the estimated consumption of EVs. Compared with diesel, EVs show average GHG savings of around 50% and not savings at all in some EU MS.