Enteroviruses are associated with various diseases accompanied by rare but severe complications. In recent years, outbreaks of enterovirus D68 and enterovirus A71 associated with severe respiratory infections and neurological complications have been reported worldwide. Since information on molecular epidemiology in respiratory samples is still limited, the genetic diversity of enteroviruses was retrospectively analysed over a 4-year period (2013–2016) in respiratory samples from paediatric patients. Partial viral major capsid protein gene (VP1) sequences were determined for genotyping. Enteroviruses were detected in 255 (6.1%) of 4187 specimens. Phylogenetic analyses of 233 (91.4%) strains revealed 25 different genotypes distributed to Enterovirus A (39.1%), Enterovirus B (34.3%), and Enterovirus D (26.6%). The most frequently detected genotypes were enterovirus D68 (26.6%), coxsackievirus A6 (15.9%), and enterovirus A71 (7.3%). Enterovirus D68 detections were associated with lower respiratory tract infections and increased oxygen demand. Meningitis/encephalitis and other neurological symptoms were related to enterovirus A71, while coxsackievirus A6 was associated with upper respiratory diseases. Prematurity turned out as a potential risk factor for increased oxygen demand during enterovirus infections. The detailed analysis of epidemiological and clinical data contributes to the non-polio enterovirus surveillance in Europe and showed high and rapidly changing genetic diversity of circulating enteroviruses, including different enterovirus D68 variants.

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.

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.

Defining key parameters for a charge sustaining supervisory (torque split) control strategy as well as an engine and catalyst warm-up strategy for a Split Parallel Architecture Extended-Range Electric Vehicle (SPA E-REV) is accomplished through empirically and experimentally measuring vehicle tailpipe emissions and energy consumption for two distinct control strategies. The results of the experimental testing and analysis define how the vehicle reduces fuel consumption, petroleum energy use and greenhouse gas emissions while maintaining low tailpipe emissions. For a SPA E-REV operating in charge sustaining mode with the engine providing net propulsive energy, simply operating the engine in regions of highest efficiency does not equate to the most efficient operation of the vehicle as a system and can have adverse effects on tailpipe emissions. Engine and catalyst warm-up during the transition from all-electric charge depleting to engine-dominant charge sustaining modes is experimentally analyzed to evaluate tailpipe emissions. The results presented are meant to define key parameters for a high-level torque-split strategy and to provide an understanding of the tradeoffs between low energy consumption and low tailpipe emissions. The literature review gives a background of hybrid and plug-in hybrid vehicle control publications including tailpipe emissions studies, but does not include experimental results and comparisons of supervisory strategies designed for low fuel consumption and low tailpipe emissions the SPA E-REV architecture. This paper details the high-level control strategy chosen for balancing low energy consumption and low tailpipe emissions while the engine is operating. Vehicle testing data from a chassis dynamometer is presented in support of the research. / Master of Science

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此論文係以商業營運計畫為撰寫架構，希望透過創新的異業整合方式，結合油品銷售業者、整車製造廠、鋰鐵磷電池廠和資、通訊電子業者等跨越不同產業的廠商，以電動車為基礎打造全新的營運模式，並為各領域之廠商在現有事業之外另闢新的產銷契機。 本計畫以在台灣擁有最多加油站數的台灣中油公司為核心，建議由其負責主導與整合，並創設名為「綠寶石電池」的新公司，借重中油的加油站據點等無人可及的實體通路優勢來吸引不同電動車與鋰鐵磷電池的上、下游業者一起共相盛舉，進而共同在即將爆發大成長商機的電動車與鋰鐵磷電池市場獲得領先地位。 中油可將裕隆等整車製造廠、鋰鐵磷電池廠商和資、通訊電子業者視為可提供營運綜效的策略投資與合作夥伴，初期規劃的總資本額為新台幣100億元，由中油負責其中的40~50億元，希望引進的其他投資金額分別由裕隆等數家整車製造廠投資共約30~40億元，以及數家具備優異技術開發與量產能力的鋰鐵磷正極材料廠商共約20~30億元。 綠寶石計畫投入的市場包括依行駛里程收取充電費用，舊鋰鐵磷電池儲電模組轉售，和各種娛樂休閒與商務的資、通訊與網路服務等，自2011年開始營運，預估2011年到2015年的總營收分別為22.85億元、59.82億元、96.78億元、136.95億元和179.11億元。 其中，來自依行駛里程收取充電費用的收入約佔總營收60%，自舊鋰鐵磷電池儲電模組轉售業務所取得的營業收入約佔總營收30%~35%，來自資、通訊網路服務的營業收入則佔總營收的5%~10%左右。 綠寶石預估在2013年即可正式轉虧為盈，稅前淨利達22.92億元，每股獲利可達1.72元，2014年與2015年的營運將更上層樓，稅前獲利分別為43.95億元和77.06億元，每股獲利可達4.40元和7.71元。

The aim of this report is to evaluate how a future commercially owned fleet of self-driving electric vehicles (EV:s) would be able to provide power in order to avoid power exceedances in the power grid. Exceedances occur when network agreements between grid operating companies are exceeded. Exceedances are problematic, since they infer penalty fees for the paying company and make dimensioning the grid capacity more difficult for the supplying company. Capacity deficiency regarding the infrastructure of the grid is expected to increase, likely resulting in higher penalty fees. Integrating transport and power systems by using self-driving EV:s as Mobility as a Service combined with Vehicle-to-Grid (V2G) technology is a potential solution for this problem. By modeling the EV-fleet as the New York City taxi fleet, a usage pattern deemed to resemble Mobility as a Service is created. An economic value for the V2G service is estimated by comparing the availability of the EV-fleet with local exceedances from Uppsala as well as regional occurring exceedances. The highest income during the first quarter of 2019 is 96 000 SEK for the whole fleet, or 1100 SEK per EV and hour-long exceedance. The time of exceedance and the power magnitude have to interplay with the availability of the EV-fleet in order to enable the system. The EV battery capacity highly impacts the system, but is concluded to not be a limiting factor due to market logic. Lastly, key features such as market formation as well as geographical and technical aspects are presented and discussed.

The University of Waterloo Alternative Fuels Team’s participation in EcoCAR: The Next Challenge provided an unparalleled opportunity to execute advanced vehicle technology research with hands on learning and industry leading mentoring from practicing engineers in the automotive industry. This thesis investigates the optimization of the hybrid operating strategy on board the EcoCAR development vehicle. This investigation provides the framework to investigate the pros and cons of different hybrid control strategies, develop the model based design process for controls development in a student team environment and take the learning of this research and apply them to a mule development vehicle. A primary controls development model was created to simulate software controls before releasing to the vehicle level and served as a tool to evaluate and compare control strategies. The optimization routine was not directly compatible with this model and so a compromise was made to develop a simplified vehicle model in the MATLAB environment that would be useful for observing trends but realizing that the accuracy of the results may not be totally consistent with the real world vehicle. These optimization results were then used to create a new control strategy that was simulated in the original vehicle development model. This new control strategy exhibited a 15% gain in fuel economy over the best case from the literature during an Urban Dynamometer Driving Schedule (UDDS) drive cycle. Recommendations for future work include adding charge depletion operation to the simulation test cases and improving the accuracy of the optimization model by removing the simplifications that contributed to faster simulation time. This research has also illustrated the wide variability of drive cycles from the mildly aggressive UDDS cycle having 5 kilowatts average propulsion power to the very aggressive US06 cycle having 19 kilowatts average propulsion power and their impact on the efficiency of a particular control strategy. Understanding how to adapt or tune software for particular drive cycle or driver behaviour may lead to an interesting area of research.