Design and analysis of polysilicon and single crystal silicon gyroscopes have been carried out. Variations in suspension design have been explored. Designs that utilize in-plane and out-of-plane sensing are studied. Damping plays an important role in determining the sense response. Reduction in damping directly affects sensor performance. The various damping mechanisms that are prevalent in gyroscopes are studied. Perforations on the proof mass are observed to significantly reduce the damping in the device when operated in air. The effects of perforation geometry and density have been analyzed. The analysis results show that there is a two orders of magnitude reduction in damping of thick gyroscope structures with optimized perforation design. Equivalent circuit lumped parameter models have been developed to analyze gyroscope performance. The simulation results of these models have been compared with results obtained from SABER, a MEMS specific system level design tool from Coventor-ware. The lumped parameter models are observed to produce faster simulation results with an accuracy comparable to that of Coventorware Three gyroscopes specific to the PolyMUMPS fabrication process have been designed and their performance analyzed. Two of the designs sense motion out-of-plane and the other senses motion in-plane. Results of the simulation show that for a given damping, the gyro design with in-plane modes gives a resolution of 4◦/s. The out-of-plane gyroscopes have two variations in suspension. The hammock suspension resolves a rate of 25◦/s in a 200 Hz bandwidth while the design with folded beam suspension resolves a rate of 2◦/s in a 12 Hz bandwidth. A single crystal silicon in-plane gyroscope has been designed with vertical electrodes to sense Coriolis motion. This design gives an order of magnitude higher capacitance change for a given rotation in comparison to conventional comb-finger design. The effects of process induced residual stress on the characteristic frequencies of the polysilicon gyroscopes are also studied. The in-plane gyroscope is found to be robust to stress variations. Analysis results indicate that the tuning fork gyroscope with the hammock suspension is the most susceptible to compressive residual stress, with a significant drop in sensitivity at high stress values.

Thesis (PhD)--University of Pretoria, 2013. / Electrical, Electronic and Computer Engineering

No description available.

<p>Due to increasing regulation on emissions and shifting consumer preferences, the wide adoption of battery electric vehicles (BEV) hinges on research and development of technologies that can extend system range. This can be accomplished either by increasing the battery size or via more efficient operation of the electrical and thermal systems. This thesis endeavours to accomplish the latter through comparative investigation of BEV integrated thermal management system (ITMS) performance across a range of ambient conditions (-20 °C to 40 °C), cabin setpoints (18 °C to 24 °C), and six different ITMS architectures. A dynamic ITMS modelling framework for a long-range electric vehicle is established with comprehensive sub models for the operation of the drive train, power electronics, battery, vapor compression cycle components, and cabin conditioning. This modelling framework is used to construct a baseline thermal management system, as well as for adaptation to four common systems. Additionally, a novel low-temperature waste heat recovery (LT WHR) system is proposed and shown to have potential benefits at low ambient temperatures through the reduction of the necessary cabin ventilation loading. While this system shows performance improvements, the regular WHR system offers the greatest benefit for long-range BEV drive cycles in terms of system range and transient response. With an optimal thermal management system found for long range BEV’s this system is then used as a boundary condition for a study on cooling of the battery. Battery conditioning, health, and as a result their along cell and system lifetime remains an additional concern of consumers as well as thermal systems engineers seeking to ensure safety and ensure longevity of EV battery cells. Three typical coolant flow orientations are studied to compare them under different flow conditions and thermal interface material performance. The battery cooling model is then coupled to the previously established dynamic modelling environment to demonstrate the added modelling capability (and necessity) for incorporating module-level cooling performance in both battery cooling studies and transient ITMS environments. </p>

This thesis investigates simulation of synchronous machines using a novel Magnetic Equivalent Circuit (MEC) model. The proposed model offers sufficient detail richness for design calculations, while still keeping the simulation time acceptably short. Different modeling methods and circuit alternatives are considered. The selected approach is a combination of several previous methods added with some new features. A detailed description of the new model is given. The flux derivative is chosen as the magnetic flow variable which enables a description with standard circuit elements. The model is implemented in dq-coordinates to reduce complexity and simulation time. A new method to reflect winding harmonics is introduced. Extensive measurements have been made to estimate the traditional dq-model parameters. These in combination with analytical calculations are used to determine the parameters for the new MEC model. The model is implemented using the Dymola simulation program. The results are evaluated by comparison with measurements and FEM simulations. Three different operation cases are investigated; synchronous operation, asynchronous start and inverter fed operation. The agreement with measurements and FEM simulations varies, but it is believed that it can be improved by more work on the parameter determination. The overall conclusion is that the MEC method is a useful approach for detailed simulation of synchronous machines. It enables proper modeling of magnetic saturation, and promises sufficiently detailed results to enable accurate loss calculations. However, the experience is that the complexity of the circuits should be kept at a reasonable low level. It is believed that the practical problems with model structure, parameter determination and the simulation itself will otherwise be difficult to master.

The battery is a component with significant impact on both the cost and environmental footprint of a full electric vehicle (EV). Consequently, there is a strong motivation to maximize its degree of utilization. Usage limits are enforced by the battery management system (BMS) to ensure safe operation and limit battery degradation. The limits tend to be conservative to account for uncertainty in battery state estimation as well as changes in the battery's characteristics due to aging. To improve the utilization degree, aging sensitive battery control is necessary. This refers to control that a) adjusts during the battery's life based on its state and b) balances the trade-off between utilization and degradation according to requirements from the specific application.  In state-of-the-art battery installations, only three signals are measured; current, voltage and temperature. However, the battery's behaviour is governed by other states that must be estimated such as its state-of-charge (SOC) or local concentrations and potentials. The BMS therefore relies on models to estimate states and to perform control actions. In order to realize points a) and b), the models that are used for state estimation and control must be updated onboard. An updated model can also serve the purpose of diagnosing the battery, since it reflects the changing properties of an aging battery. This thesis investigates identification of physics-based and empirical battery models from operational EV data. The work is divided into three main studies. 1) A global sensitivity analysis was performed on the parameters of a high-order physics-based model. Measured current profiles from real EV:s were used as input and the parameters' impact on both modelled cell voltage and other internal states was assessed. The study revealed that in order to excite all model parameters, an input with high current rates, large SOC span and longer charge or discharge periods was required. This was only present in the data set from an electric truck with few battery packs. Data sets from vehicles with more packs (electric bus) and limited SOC operating window (plug-in hybrid truck) excited fewer model parameters. 2) Empirical linear-parameter-varying (LPV) dynamic models were identified on driving data. Model parameters were formulated as functions of the measured temperature, current magnitude and estimated open circuit voltage (OCV). To handle the time-scale differences in battery voltage response, continuous-time system identification was employed. We concluded that the proposed models had superior predictive abilities compared to discrete and time-invariant counterparts.  3) Instead of using driving data to parametrize models, we also investigated the possibility to design the charging current in order to increase its information content about model parameters. This was formulated as an optimal control problem with charging speed and information content as objectives. To also take battery degradation into account, constraints on polarization was included. The results showed that parameter information can be increased without significant increase in charge time nor aging related stress. / Elekriska fordon utgör en allt större andel av världens fordonsflotta. Batteriet är en komponent med betydande påverkan både på fordonets kostnadoch dess miljö- och klimatpåverkan. Det är därför viktigt att försöka maximera batteriets utnytjandegrad. Användargränser upprätthålls av batterietsstyrsystem, såkallad BMS, för att garantera säker drift samt för att begränsabatteriets åldrande. Användargränserna tenderar att vara konservativa för attta höjd för osäkerhet i tillståndsestimeringen samt batteriets förändrade egenskaper under dess livstid. För att utöka utnyttjandegraden är ålderskänsligstyrning nödvändig. Med detta avses styrning som a) justeras under batterietslivstid och b) balancerar utnyttjande och prestanda på ett sätt som passar enspecifik applikation. Ombord på fordon mäts typiskt tre signaler; ström, spänning och temperatur. Batteriets beteende bestäms dock av andra tillstånd som måste estimeras, såsom dess laddnivåeller lokala koncentrationer och potentialer. BMS:enförlitar sig därför på modeller för att estimera interna tillstånd och utföra styrning. För att uppfylla punkterna a) och b) måste modellerna som användsuppdateras ombord i takt med att batteriet åldras. En uppdaterad modellkan också fungera som ett diagnostiskt verktyg eftersom det speglar batteriets förändrade egenskaper. Den här avhandlingen undersöker identifieringav fysikbaserade och empiriska modeller från kördata. Arbetet delas in i treseparata studier. 1) En global känslighetsanalys utfördes på parametrarna i en fysikbaseradmodell av hög ordning. Som inputsignal användes uppmätt ström från riktigaelfordon i drift. Parametrarnas effekt på både cellspänning och interna batteritillstånd analyserades. Studien visade att alla modellparametrar exciteradesav strömmen från ett helelektriskt fordon. Anledningen var att batteriernaanvändes inom ett brett SOC spann samt att den dragna strömmen var stor.I fordon med snävare SOC span och lägre strömmar var inte alla parametrarkänsliga. 2) Dynamiska parametervarierande modeller formulerades och identifierades från kördata. Den uppmätta temperaturen, samt strömmens storlekoch den estimerade tomgångsspänningen (OCV) användes till parameterberoenden. För att hantera skillnader i tidsskala mellan spänningssvarets olikakomponenter användes systemidentifiering i kontinuerlig tid. Vi kunde draslutsatsen att de föreslagna modellerna var överlägsna motsvarande diskretaoch konstanta modeller. 3) Istället för att använda kördata för att parametrisera modeller undersökte vi också möjligheten att designa laddförloppet för att öka dess informationsinnheåll. Detta formulerades som ett optimeringsproblem med laddtidoch informationsinnehåll i kostnadsfunktionen. För att även ta batteriets åldrande i beaktning, ansattses bivillkor på polariseringsspänningen. / <p>QC 20220516</p>

In this thesis, the basics of electromagnetic theory for wave-energy conversion are reviewed, some of the characteristics of the ocean wave are investigated, some of the power take-off (PTO) systems are introduced, and details about linear permanent magnetic machines, in particular, are discussed.  The thesis aims to model the novel linear transverse flux machine designed by Anders Hagnestål and to build hysteresis current controller for power factor correc- tion. Although this machine is expected to have high performance in terms of efficiency, it also exhibits a strong mutual interaction between the three phases of the machine. Thus, simplification of the actual model of the machine is im- posed to mitigate the complexity of the machine and facilitate the Simulink model. Four cases of the double band hysteresis control are studied. The cur- rents seem to be responding properly to the control scheme; however, software and hardware programming of a microprocessor would be preferable to ensurethe applicability of the control strategy in a real environment. / I detta examensarbete undersöks elektromagnetisk teori och havsvågors egenskaper. Några energiomvandlingssystem introduceras och permanentmagnetiserade maskiner diskuteras i detalj. Syftet med avhandlingen är att modelleraen ny linjär transversalflödesmaskin som är designad av Anders Hagnestål och att bygga en hysteresbaserad strömkontroll för denna. Även om maskinen förväntas prestera bra, uppvisar den också en stark ömsesidig magnetisk interaktion mellan de tre faserna. För att kunna hantera detta problem och därmed kunna genomföra simuleringar införs en förenklad elektromagnetisk modell av maskinen. En strömkontroller har implementerats i Simulink, där fyra fall av dubbelbandshystereskontroll studerats. Resultaten från simuleringarna visar att strömkontrollern fungerar. Nästa steg i projektet är att utföra mjukvaru och hårdvaruprogrammering av en mikrokontroller för att testa systemet i enverklig miljö.

ELECTROCHEMICAL IMPEDANCE SPECTROSCOPY (EIS) has been widely used to study the electrical properties of biological material due to its non-invasive nature and experimental reliability. However, most of the precision impedance analyzers used in EIS only provide single- or two-channel measurements which are inadequate for larger-scale multiplexed measurements, such as those found in modern microfluidic cell culture experiments. The Biomedical Microsystems Laboratory has developed a 16-channel cell culture platform with integrated electrode arrays for monitoring cell growth and electrical properties (i.e., the so-called “electrical phenotype”). In this paper, a system consisting of a 16-channel solid-state analog multiplexer (MUX)paired with a low-cost, impedance analyzer is developed to replace high-cost physical relay MUX and impedance analyzer systems. System requirements and design constraints for monitoring biological systems are considered and a prototype device was fabricated. Initial testing was performed on a breadboard to verify the feasibility of the design idea. Results identified measurement errors due to parasitic elements in the system. Software compensation successfully corrected for parasitic capacitance in the analog MUX design. The accuracy of the measurement system was evaluated on a developed Printed Circuit Board Assembly (PCBA) by comparing theoretical values to MUX compensated data. Finally, an EIS experiment was carried out with tap water with the PCBA system, and measurement results were analyzed using an equivalent Circuit Model (ECM). These results successfully captured the dynamics of charge transport in the electrical double layer, consistent with a modified-Randlecell ECM.

Switching from fossil-fuel-powered vehicles to electric vehicles has become an international focus in the pursuit of combatting climate change. Regardless, the adoption of electric vehicles has been slow, in part, due to range anxiety. One solution to mitigating range anxiety is to provide a more accurate state of charge (SOC) and range estimation. SOC estimation of lithium-ion batteries for electric vehicle application is a well-researched topic, yet minimal tools and code exist online for researchers and students alike. To that end, a publicly available Kalman filter-based SOC estimation function is presented. The MATLAB function utilizes a second-order resistor-capacitor equivalent circuit model. It requires the SOC-OCV (open circuit voltage) curve, internal resistance, and equivalent circuit model battery parameters. Users can use an extended Kalman filter (EKF) or adaptive extended Kalman filter (AEKF) algorithm and temperature-dependent battery data. A practical example is illustrated using the LA92 driving cycle of a Turnigy battery at multiple temperatures ranging from -10C to 40C. Current range estimation methods suffer from inaccuracy as factors including temperature, wind, driver behaviour, battery voltage, current, SOC, route/terrain, and much more make it difficult to model accurately. One of the most critical factors in range estimation is the battery. However, most models thus far are represented using equivalent circuit models as they are more widely researched. Another limitation is that any machine learning-based range estimation is typically based on historical driving data that require odometer readings for training. A range estimation algorithm using a machine learning-based voltage estimation model is presented. Specifically, the long short-term memory cell in a recurrent neural network is used for the battery model. The model is trained with two datasets, classic and whole, from the experimental data of four Tesla/Panasonic 2170 battery cells. All network training is completed on SHARCNET, a resource provided by Canada Compute to researchers. The classically trained network achieved an average root mean squared error (RMSE) of 44 mV compared to 34 mV achieved by the network trained on the whole dataset. Based on the whole dataset, all test cases achieve an end range estimation of less than 5 km with an average of 0.29 km. / Thesis / Master of Applied Science (MASc)

Les techniques de camouflage, mimétisme ou invisibilité ont récemment connu une forte émergence, qui se poursuit aujourd’hui avec l’apparition des méta-surfaces. C’est dans ce contexte que ce travail de doctorat a été réalisé, notamment avec un premier objectif d’étendre ces outils et concepts aux problèmes inverses du domaine de la diffusion de la chaleur. La suite du travail a concerné le rayonnement thermique, les méta-surfaces et les transformations de champ. Après avoir étendu les techniques de mimétisme au domaine de la conduction, nous avons résolu le problème inverse associé, qui consiste à camoufler des objets imposés en forme ou conductivité. Ce premier travail a permis de mettre en évidence les classes de transformation qui laissent invariantes les paramètres physiques, conférant ainsi plus de pragmatisme au domaine du mimétisme. Nous avons ensuite considéré le cas du rayonnement thermique, et démontré pour la première fois que les illusions par rayonnement étaient envisageables, en appui sur l’invariance du théorème de fluctuation/dissipation. Dans une deuxième étape, nous avons mis au point une nouvelle méthode pour calculer le rayonnement thermique par des objets de forme arbitraire, mettant en jeu des méta-surfaces inhomogènes, anisotropes, chirales et non locales. Nous montrons également comment tirer profit des méta-surfaces pour remplacer les capes volumiques tout en conservant la fonction de camouflage. Cette technique est particulièrement prometteuse pour les applications, même si elle reste intrinsèquement liée à l’éclairement. Des techniques similaires sont développées pour que soit facilité l’utilisation de transformations discontinues de l’espace. / Mimetism, camouflage or invisibility have motivated numerous efforts in the last decade, which are now extended with metasurfaces. This PhD work fits this international context and was first focused on inverse problems in heat conduction before we address thermal radiation and metasurfaces, field transformation. After we generalize the mimetism techniques to heat diffusion, we solved the associated inverse problem which consists of the camouflage of given objects, that is, objects with shape or conductivity that are before hand chosen. The results allowed us to emphasize the class of transformations which hold the physical parameters, hence giving more pragmatism to the field of mimetism. Then we addressed the case of thermal radiation and proved for the first time that mimetism effects could also be controlled in this field, on the basis of the fluctuation/dissipation theorem. In a second step, we built an original technique able to predict the thermal radiation from objects of arbitrary shapes. This technique involves inhomogeneous, anisotropic, chiral and nonlocal metasurfaces. We also show how to take more benefits of metasurfaces in order to replace the bulk mimetism cloaks. We believe this technique to give again more push forward to the field, though the mimetism efficiency now relies on the illumination conditions. Similar techniques are further developed to allow a practical use of discontinuous space transformations. Eventually, field transformation is introduced to complete all these results.