Parameter optimization for noise and vibration reduction associated with position and speed sensorless control of permanent magnet machines at low speed

With the advantages and popularity of Permanent Magnet (PM) motors due to their high power density, there is an increasing incentive to use them in variety of applications including electric actuation. These applications have strict noise emission standards. The generation of audible noise and associated vibration modes are characteristics of all electric motors, it is especially problematic in low speed sensorless control rotary actuation applications using high frequency voltage injection technique. This dissertation is aimed at solving the problem of optimizing the sensorless control algorithm for low noise and vibration while achieving at least 12 bit absolute accuracy for speed and position control. The low speed sensorless algorithm is simulated using an improved Phase Variable Model, developed and implemented in a hardware-in-the-loop prototyping environment. Two experimental testbeds were developed and built to test and verify the algorithm in real time.^ A neural network based modeling approach was used to predict the audible noise due to the high frequency injected carrier signal. This model was created based on noise measurements in an especially built chamber. The developed noise model is then integrated into the high frequency based sensorless control scheme so that appropriate tradeoffs and mitigation techniques can be devised. This will improve the position estimation and control performance while keeping the noise below a certain level. Genetic algorithms were used for including the noise optimization parameters into the developed control algorithm.^ A novel wavelet based filtering approach was proposed in this dissertation for the sensorless control algorithm at low speed. This novel filter was capable of extracting the position information at low values of injection voltage where conventional filters fail. This filtering approach can be used in practice to reduce the injected voltage in sensorless control algorithm resulting in significant reduction of noise and vibration.^ Online optimization of sensorless position estimation algorithm was performed to reduce vibration and to improve the position estimation performance. The results obtained are important and represent original contributions that can be helpful in choosing optimal parameters for sensorless control algorithm in many practical applications.^

Investigation of generation -recombination noise and related processes in aluminum gallium arsenide TEGFETs and Hall structures with quantum wells

Experimental and theoretical studies regarding noise processes in various kinds of AlGaAs/GaAs heterostructures with a quantum well are reported. The measurement processes, involving a Fast Fourier Transform and analog wave analyzer in the frequency range from 10 Hz to 1 MHz, a computerized data storage and processing system, and cryostat in the temperature range from 78 K to 300 K are described in detail. The current noise spectra are obtained with the “three-point method”, using a Quan-Tech and avalanche noise source for calibration. ^ The properties of both GaAs and AlGaAs materials and field effect transistors, based on the two-dimensional electron gas in the interface quantum well, are discussed. Extensive measurements are performed in three types of heterostructures, viz., Hall structures with a large spacer layer, modulation-doped non-gated FETs, and more standard gated FETs; all structures are grown by MBE techniques. ^ The Hall structures show Lorentzian generation-recombination noise spectra with near temperature independent relaxation times. This noise is attributed to g-r processes in the 2D electron gas. For the TEGFET structures, we observe several Lorentzian g-r noise components which have strongly temperature dependent relaxation times. This noise is attributed to trapping processes in the doped AlGaAs layer. The trap level energies are determined from an Arrhenius plot of log (τT2) versus 1/T as well as from the plateau values. The theory to interpret these measurements and to extract the defect level data is reviewed and further developed. Good agreement with the data is found for all reported devices. ^

Noise in gallium nitride-based quantum well structures used for nanometer devices in the frequency range 1 Hz--3 Mhz and temperature range 77K--324K

Electronic noise has been investigated in AlxGa1−x N/GaN Modulation-Doped Field Effect Transistors (MODFETs) of submicron dimensions, grown for us by MBE (Molecular Beam Epitaxy) techniques at Virginia Commonwealth University by Dr. H. Morkoç and coworkers. Some 20 devices were grown on a GaN substrate, four of which have leads bonded to source (S), drain (D), and gate (G) pads, respectively. Conduction takes place in the quasi-2D layer of the junction (xy plane) which is perpendicular to the quantum well (z-direction) of average triangular width ∼3 nm. A non-doped intrinsic buffer layer of ∼5 nm separates the Si-doped donors in the AlxGa1−xN layer from the 2D-transistor plane, which affords a very high electron mobility, thus enabling high-speed devices. Since all contacts (S, D, and G) must reach through the AlxGa1−xN layer to connect internally to the 2D plane, parallel conduction through this layer is a feature of all modulation-doped devices. While the shunting effect may account for no more than a few percent of the current IDS, it is responsible for most excess noise, over and above thermal noise of the device. ^ The excess noise has been analyzed as a sum of Lorentzian spectra and 1/f noise. The Lorentzian noise has been ascribed to trapping of the carriers in the AlxGa1−xN layer. A detailed, multitrapping generation-recombination noise theory is presented, which shows that an exponential relationship exists for the time constants obtained from the spectral components as a function of 1/kT. The trap depths have been obtained from Arrhenius plots of log (τT2) vs. 1000/T. Comparison with previous noise results for GaAs devices shows that: (a) many more trapping levels are present in these nitride-based devices; (b) the traps are deeper (farther below the conduction band) than for GaAs. Furthermore, the magnitude of the noise is strongly dependent on the level of depletion of the AlxGa1−xN donor layer, which can be altered by a negative or positive gate bias VGS. ^ Altogether, these frontier nitride-based devices are promising for bluish light optoelectronic devices and lasers; however, the noise, though well understood, indicates that the purity of the constituent layers should be greatly improved for future technological applications. ^

Specific Increase in MDR1 Mediated Drug-Efflux in Human Brain Endothelial Cells following Co-Exposure to HIV-1 and Saquinavir

Persistence of HIV-1 reservoirs within the Central Nervous System (CNS) remains a significant challenge to the efficacy of potent anti-HIV-1 drugs. The primary human Brain Microvascular Endothelial Cells (HBMVEC) constitutes the Blood Brain Barrier (BBB) which interferes with anti-HIV drug delivery into the CNS. The ATP binding cassette (ABC) transporters expressed on HBMVEC can efflux HIV-1 protease inhibitors (HPI), enabling the persistence of HIV-1 in CNS. Constitutive low level expression of several ABC-transporters, such as MDR1 (a.k.a. P-gp) and MRPs are documented in HBMVEC. Although it is recognized that inflammatory cytokines and exposure to xenobiotic drug substrates (e.g HPI) can augment the expression of these transporters, it is not known whether concomitant exposure to virus and anti-retroviral drugs can increase drug-efflux functions in HBMVEC. Our in vitro studies showed that exposure of HBMVEC to HIV-1 significantly up-regulates both MDR1 gene expression and protein levels; however, no significant increases in either MRP-1 or MRP-2 were observed. Furthermore, calcein-AM dye-efflux assays using HBMVEC showed that, compared to virus exposure alone, the MDR1 mediated drug-efflux function was significantly induced following concomitant exposure to both HIV-1 and saquinavir (SQV). This increase in MDR1 mediated drug-efflux was further substantiated via increased intracellular retention of radiolabeled [3H-] SQV. The crucial role of MDR1 in 3H-SQV efflux from HBMVEC was further confirmed by using both a MDR1 specific blocker (PSC-833) and MDR1 specific siRNAs. Therefore, MDR1 specific drug-efflux function increases in HBMVEC following co-exposure to HIV-1 and SQV which can reduce the penetration of HPIs into the infected brain reservoirs of HIV-1. A targeted suppression of MDR1 in the BBB may thus provide a novel strategy to suppress residual viral replication in the CNS, by augmenting the therapeutic efficacy of HAART drugs.