In this work Scanning Kelvin Probe Microscopy (SKPM) was used to characterize surface states and device surface charging in nitride materials. Samples grown by Molecular Beam Epitaxy (MBE), Metal Organic Chemical Vapor Deposition (MOCVD) and Hydride Vapor Phase Epitaxy (HVPE) typically show a high surface band bending of about 1 eV. In an n-type sample with 3X1017 cm-3 carrier concentration, 1 eV upward band bending corresponds to 1.7X1012 cm-2 trapped charge density in the surface states. Under continuous ultraviolet (UV) illumination up to 0.6 eV surface photo voltage effect could be observed in some samples, which further indicates that surface band bending is very likely larger than 0.6 eV, i.e. close to 1 eV. Reactive Ion Etching (RIE)damage was observed to increase surface band bending by about 0.4 eV where as surface treatments in organic solvents and inorganic acids did not affect surface band bending significantly. These results indicate presence of high density of surface states in devices fabricated in nitride materials. Surface potential measurements immediately after turning off a reverse bias to the Schottky contact of a GaN Schottky diode as well as an AlGaN/GaN Hetero-junction Field Effect Transistor (HFET) show an increase of band bending near the Schottky contact edge. For an applied reverse bias of 4 V, about 0.5 eV increase of band bending was observed. This increase of band bending was caused by tunneling of electrons from the Schottky contact and their subsequent capture by surface states near the contact edge. In case of the HFET, the increase of band bending for a bias that caused no current flow through the device was similar to a bias that did. This showed that hot electron injection from the channel did not play a significant role in increasing surface band bending. The accumulated charge near the gate edge of a HFET can deplete the channel, which would cause the drain current to decrease. The total times of accumulation and dissipation of excess surface charge near the gate edge of the HFET were comparable to the time scales of drain current transients of current collapse and recovery. From this observation we attributed current collapse phenomena to charge accumulation near the edge of the reverse biased gate contact of a HFET.

A new “best match” match model has been developed to account for adduct formation on multiply charged peptides observed in negative ion electrospray mass spectrometry. To obtain a stable adduct, the model necessitates an approximate matching of apparent gas-phase basicity (GBapp) of a given proton bearing site on the peptide with the gas-phase basicity (GB) of the anion attaching at that site. Evidence supporting the model is derived from the fact that singly charged adducts were only observed for lower GB anions: HSO4-, I-, CF3COO-. Ions that have medium GBs (NO3-, Br-, H2PO4-) only form adducts having -2 charge states, whereas Cl- (higher GB) can form adducts having -3 charge states. Hydrogen bonds are the main interactions pertinent to the “Best Match” model, however, ion-ion interactions formed between peptides ([Glu]Fibrinopeptide B, Angiotensin I or [Asn1,Val5]-Angiotensin II) and low GB anions (ClO4- or HSO4-) have been established by CID-MS/MS. Evidence for ion-ion interactions comes especially from product ions formed during the first dissociation step, where, in addition to the expected loss of the anion or neutral acid, other product ions that require covalent bond cleavage (i.e., H2O or NH3 loss) are also observed. In this study, the “Best Match” model is further supported by the decomposition behavior of adducts formed when Na+/H+ exchange has occurred on peptides. Na+/H+ exchanges were found to occur preferentially at higher acidity sites. Without any Na+/H+ exchange, F- and CH3COO- can hardly form observable adducts with [Glu]Fibrinopeptide B. However, after multiple Na+/H+ exchanges, F- and CH3COO- do form stable adducts. This phenomenon can be rationalized by considering that Na+ cations serve to “block” the highly acidic sites, thereby forcing them to remain overall neutral. This leaves the less acidic protons available to match with higher GB anions. According to the "best match" model, high GB anions will match with high GBapp sites on the peptide, whereas low GB anions will match with low GBapp peptide sites. High charge states readily augment GBapp of the peptide (through-space effect). Na+/H+ exchanges substantially decrease GBapp by neutralizing charged sites, while slightly increasing intrinsic GBs by the inductive effect.

This diploma thesis is about description and analysis of urban traffic. First part of this work is focused on subsystems of urban public transport, categorization and description of the external costs in road transport and possible ways of charging. Electronic toll systems, their legal framework, the basic architecture, applied technologies and their interoperability and standardization are described. The final and main part of this work is devoted to a description and evaluation of urban toll systems in three Norwegian cities: Oslo, Trondheim and Bergen.

Autonomous electric vehicles are set to replace most conventional vehicles in the near future. Extensive research is being done to improve efficiency at the individual and fleet level. There is much potential benefit in optimizing the deployment and rebalancing of Autonomous Electric Taxi Fleets (AETF) in cities with dynamic demand and limited charging infrastructure. We propose a Fleet Management System with an Online Optimization Model to assign idle taxis to either a region or a charging station considering the current demand and charging station availability. Our system uses real-time information such as demand in regions, taxi locations and state of charge (SoC), and charging station availability to make optimal decisions in satisfying the dynamic demand considering the range-based constraints of electric taxis. We integrate our Fleet Management System with MATSim, an agent-based transport simulator, to simulate taxis serving real on-demand requests extracted from the San Francisco taxi mobility dataset. We found our system to be effective in rebalancing and ensuring efficient taxi operation by assigning them to charging stations when depleted. We evaluate this system using different performance metrics such as passenger waiting time, fleet efficiency (taxi empty driving time) and charging station utilization by varying initial SoC of taxis, frequency of optimization and charging station capacity and power.

Autonomous electric vehicles are set to replace most conventional vehicles in the near future. Extensive research is being done to improve efficiency at the individual and fleet level. There is much potential benefit in optimizing the deployment and rebalancing of Autonomous Electric Taxi Fleets (AETF) in cities with dynamic demand and limited charging infrastructure. We propose a Fleet Management System with an Online Optimization Model to assign idle taxis to either a region or a charging station considering the current demand and charging station availability. Our system uses real-time information such as demand in regions, taxi locations and state of charge (SoC), and charging station availability to make optimal decisions in satisfying the dynamic demand considering the range-based constraints of electric taxis. We integrate our Fleet Management System with MATSim, an agent-based transport simulator, to simulate taxis serving real on-demand requests extracted from the San Francisco taxi mobility dataset. We found our system to be effective in rebalancing and ensuring efficient taxi operation by assigning them to charging stations when depleted. We evaluate this system using different performance metrics such as passenger waiting time, fleet efficiency (taxi empty driving time) and charging station utilization by varying initial SoC of taxis, frequency of optimization and charging station capacity and power.

Un modèle décrivant les phénomènes physiques internes de batteries lithium-ion est développé pour une détection précise de leur état, avec application au domaine de l'industrie automobile. Pour pouvoir utiliser le modèle à des fins de contrôle de charge rapide, un observateur de vieillissement est tout d'abord conçu et intégré au modèle de batterie. Dans un second temps, une stratégie de contrôle de charge rapide robuste est conçue. Elle est basée sur un contrôleur Crone capable de gérer les grandes incertitudes paramétriques du modèle de batterie tout en atteignant l'objectif de charge rapide. Enfin, quelques simplifications du modèle de batterie, de la technique d'optimisation et de la définition des profils de charge rapide sont proposées et évaluées afin de rendre l'ensemble de la stratégie de recharge rapide applicable à un système embarqué de gestion de batterie. / A physics-based battery model is developed for an accurate state-detection of batteries in the automotive industry. In order to use the model for the purpose of fast charging control an aging observer is designed and integrated to the battery model. In a subsequent step a robust fast charging control is introduced to design a controller able to deal with large parametric uncertainties of the battery model while achieving the fast charging target. Finally some simplifications in the battery model structure, in the optimization technique and in the definition of fast charging profiles are proposed and evaluated to make the whole model applicable for an onboard battery management system.

The purpose of this bachelor thesis is to develop a smart charging algorithm for electric vehicles (EVs) and examine the potential of the smart charging scheme, compared to uncontrolled charging scheme at residential houses with an installed photovoltaic (PV) system. The thesis examines if smart charging can increase the photovoltaic self-consumption and self-sufficiency of houses. Also, the thesis will evaluate if the smart charging scheme can reduce the household peak loads compared to the uncontrolled charging scheme. The presented results show that the implementation of the proposed algorithm will reduce the household peak load on average by 38.64 percent at a house with an installed PV system. The self-consumption and self-sufficiency increased by 4.69 percent and 4.97 percent when the smart charging algorithm was applied. To increase the credibility of the developed model a sensitivity analysis considering a number of houses and vehicles was done.  From the results, it can be concluded that the proposed smart charging algorithm could be an option to reduce the household peak load and increase the usage of renewable energy sources.

"In this thesis, based on the existing researches on power factor correction technology, I analyze, design and study the Boost type power factor correction technology, which is applied in the in-board two-stage battery charger. First I analyzed the basic working principle of the active power factor corrector. By comparing several different topologies of PFC converter main circuit and control methods, I specified the research object to be the average current control (ACM) boost power factor corrector. Then I calculated and designed the PFC circuit and the ACM controller applied in the first level charging of EVs. And I run the design in Simulink and study the important features like power factor, the input current waveform and the output DC voltage and the THD and odd harmonic magnitude."

This thesis examines the possibility of enforcing a toll in Prague's central region, which has long been struggling with congestion. The central objective was to determine how interest groups affect the problem of introducing tolls in the area of Prague. Interest groups underwent an analysis at whose beginning they were identified and searched out. A determination of its benefits and costs followed to rovide a more detailed assessment establishing the motivation and the influence that various interest groups may have. In this thesis, a relatively strong interest group from the corporate sector was identified, which would be significantly affected by the toll -- the providers of courier services. Experts anticipate an assumption of negative attitudes by this group to the introduction of tolls, which is also confirmed in the/an interview with the stakeholders.

To promote higher air quality and reduce greenhouse gas emissions, the Californian government is investing heavily in developing public charging infrastructure to meet its electric vehicle adoption goal of five million zero-emission vehicles on the road by 2030. This thesis investigates the effect of public charging infrastructure availability on electric vehicle adoption at the zip code level in California. The analysis considers other factors that may influence electric vehicle adoption such as education level, income, commute time, gas prices, and public transportation rate. The findings suggest that public charging infrastructure availability does significantly positively correlate with electric vehicle registrations. Linear regressions were run using data from the U.S Department of Energy Alternative Fuels Data Center, IHS Markit vehicle registration data, and the US Census Bureau. The findings support continued investment in public charging infrastructure as a means of promoting electric vehicle adoption.