PMSM Sensorless Speed Control Drive

Permanent magnet synchronous machines (PMSM) are very popular in many industrial applications such as in mechatronics, automotive, energy storage flywheels, centrifugal compressors, vacuum pumps, and robotics. This paper proposes Sensorless control for a PMSM speed drive which is based on a closed loop control system using a proportional and integral (PI) controller that is designed to operate in flux weakening regions under a constant torque angle. This Sensorless element was adopted for best estimating the PMSM rotor position based on its performance characteristics eliminating the need for speed sensors which are usually required in such control applications. To achieve this goal, a pulse width modulation (PWM) control scheme was developed to work in conjunction with a field oriented motor control drive using Simulink.This innovative control system was simulated assuming realistic circuit components to maximize the accuracy of the proposed model. Finally, simulation results obtained under different operation conditions at below and above the rated speed of the motor were presented and discussed in this paper

Lead Acid Battery Modeling for PV Applications

Lead-Acid batteries continue to be the preferred choice for backup energy storage systems. However, the inherent variability in the manufacturing and component design processes affect the performance of the manufactured battery. Therefore, the developed Lead-Acid battery models are not very flexible to model this type of variability. In this paper, a new and flexible modeling of a Lead-Acid battery is presented. Using curve fitting techniques, the model parameters were derived as a function of the battery’s state of charge based on a modified Thevenin equivalent model. In addition, the charge and discharge characteristics of the derived model were investigated and validated using a real NP4-12 YUASA battery manufacturer\u27s data sheet to match performance at different capacity rates. Furthermore, an artificial neural network based learning system with back-propagation technique was used for estimating the model parameters using MATLAB software. The proposed neural model had the ability to predict values and interpolate between the learning curves data at various characteristics without the need of training. Finally, a closed-form analytical model that connects between inputs and outputs for neural networks was presented. It was validated by comparing the target and output and resulted in excellent regression factors

Smart Grids Technology Fundamentals - New Course

In this paper, a new course in smart grid technologies to enhance the power systems concentration in an Electrical Engineering program is presented. The aim of this course is to introduce students to contemporary topics related to distributed generation, micro-grids, renewable energy sources, and smart homes applications. This proposed 4-credit course is designed to provide students with a working knowledge from the basic concepts of power systems to the inherent elements of computational intelligence including decision support systems, smart metering, cyber security, optimization, and renewable energy sources. The automation and computational techniques involved in Smart Grid technologies are also introduced with special emphasis on the interoperability of different renewable energy sources without losing the integrity and reliability of the existing power systems. Furthermore, the standards and requirements for designing new devices and products for Smart Grid applications are introduced and discussed in this course. Topics in power generation, transmission, distribution, demand response, and reconfiguration are thoughtfully explained with real world applications to enhance the student learning process. Several case studies are analyzed and simulated using software tools such as MATLAB, Simulink, and PowerWorld packages. The course has also a laboratory component which provides students with hand-on experience in the utilization of commonly used tools to formulate and solve engineering problems

Wind Energy Estimation Functions for Future Homes

Wind energy is ideally suited for distributed generation systems to meet growing demand for electricity that find applications especially in developing countries. The motive of this study is to develop an efficient method to help identify and select the best sites to harvest the wind energy in Egypt. In this paper, a novel approach is proposed to estimate and appraise wind energy resources using Artificial Neural Network (ANN). To achieve this goal, an ANN-based algorithm was created and trained using relevant data collected from several wind monitoring posts installed across the country. Parameters such as latitude, longitude, elevation, and monthly wind speed were recorded for use as inputs and outputs for the ANN system. A key advantage of this model lies in its ability to predict and make interpolation between the learning curves data without the need for additional training runs. This feature was attainable using back-propagation techniques to estimate the model parameters with the aid of MATLAB. Another advantage of this proposed model is the derivation of closed-form input/output relationships which permitted to obtain fast and accurate results with excellent regression factors. Simulation results were presented in 3D plots and validated with real system data. Finally, The Horizontal Axis Wind Turbine (HWT) is modeled by many actual data from various manufacturers’ manuals. Results have shown that the actual data was closely matched confirming the merits of this proposed model. Many other desirable features that researchers can find useful to quantify wind energy resources such as easy model construction, integration with other technologies, and converting into Visual Basic or C++ codes were also identified with this model

Predicting Intermediate Storage Performance for Workflow Applications

Configuring a storage system to better serve an application is a challenging task complicated by a multidimensional, discrete configuration space and the high cost of space exploration (e.g., by running the application with different storage configurations). To enable selecting the best configuration in a reasonable time, we design an end-to-end performance prediction mechanism that estimates the turn-around time of an application using storage system under a given configuration. This approach focuses on a generic object-based storage system design, supports exploring the impact of optimizations targeting workflow applications (e.g., various data placement schemes) in addition to other, more traditional, configuration knobs (e.g., stripe size or replication level), and models the system operation at data-chunk and control message level. This paper presents our experience to date with designing and using this prediction mechanism. We evaluate this mechanism using micro- as well as synthetic benchmarks mimicking real workflow applications, and a real application.. A preliminary evaluation shows that we are on a good track to meet our objectives: it can scale to model a workflow application run on an entire cluster while offering an over 200x speedup factor (normalized by resource) compared to running the actual application, and can achieve, in the limited number of scenarios we study, a prediction accuracy that enables identifying the best storage system configuration

COVID-19 vaccine acceptance in older Syrian refugees : Preliminary findings from an ongoing study

Funding source This work was supported by ELRHA’s Research for Health in Humanitarian Crisis (R2HC) Programme, which aims to improve health outcomes by strengthening the evidence base for public health interventions in humanitarian crises. R2HC is funded by the UK Foreign, Commonwealth and Development Office (FCDO), Wellcome, and the UK National Institute for Health Research (NIHR). The views expressed herein should not be taken, in any way, to reflect the official opinion of the NRC or ELRHA. The funding agency was not involved in the data collection, analysis or interpretation.Peer reviewedPublisher PD

Polarizability of D+X complex in bulk semiconductors

The electric polarizability α of ionized-donor-bound exciton D+X in bulk semiconductor is calculated for all values of the effective electron-to-hole mass ratio σ included in the range of stability (σ<σχ). The calculation is performed within the variational method by using 56-term wave function. An asymptotic behavior of α in the vicinity of the critical value σc is deduced. We have also calculated the limiting value σ for which the polarizability equals that of D− system

Parametrized Equations for Excitons in Quantum Wires

A set of analytic equations for calculating the binding energies of excitons in T-shaped and squared quantum well wires are established within the effective mass approximation and the two-band model. The resolution is performed in the framework of the variational method. The projections of the relative movement in a lateral plane (2D exciton) and along the free movement direction (1D exciton) are examined as limiting cases. Binding energies and spatial extensions of the exciton as functions of the size of the wire for both the ground and the first excited states are calculated in the case of GaAs/GaAlAs heterostructures for T-shaped and squared geometries. The method is applied to calculate the effects on the excitons induced by the application of crossed electric and magnetic fields. Comparison between quantum wells, T-wires and squared wires is given

MDHAQ/RAPID3 scores in patients with osteoarthritis are similar to or higher than in patients with rheumatoid arthritis: A cross-sectional study from current routine rheumatology care at four sites

Objective To compare patients with a primary diagnosis of osteoarthritis (OA) versus rheumatoid arthritis (RA) for scores on a patient self-report MDHAQ/RAPID3 (Multidimensional Health Assessment Questionnaire/Routine Assessment of Patient Index Data 3), and for physician global assessment (DOCGL). Methods All patients with all diagnoses complete an MDHAQ/RAPID3 at all routine rheumatology visits in the waiting area before seeing a rheumatologist at four sites, one in Australia and three in the USA. The two-page MDHAQ includes 0-10 scores for physical function (in 10 activities), pain and patient global assessment [on 0-10 visual analogue scales (VAS)], compiled into a 0-30 RAPID3, as well as fatigue and self-report painful joint count scales. Rheumatologists estimate a 0-10 DOCGL VAS. Demographic, MDHAQ/RAPID3 and DOCGL data from a random visit were compared in patients with RA versus patients with OA using multivariate analysis of variance, adjusted for age, disease duration and formal education level. Results Median RAPID3 was higher in OA versus RA at all four sites (11.7-16.8 vs 6.2-11.8) (p<0.001 at three sites). Median DOCGL in OA versus RA was 5 vs 4, 4 vs 3.7, 2.2 vs 2.5 and 2 vs 1. Patterns were similar for individual RAPID3 items, fatigue and painful joint scales, and in stratified analyses of patients aged 55-70. Conclusion Patient MDHAQ/RAPID3 and physician DOCGL indicate similar or higher disease burden in OA versus RA. Routine MDHAQ/RAPID3 allows direct comparisons of the two diseases. The findings suggest possible revision of current clinical and public policy views concerning OA

Formation of highly oxygenated organic molecules from aromatic compounds

Anthropogenic volatile organic compounds (AV-OCs) often dominate the urban atmosphere and consist to a large degree of aromatic hydrocarbons (ArHCs), such as benzene, toluene, xylenes, and trimethylbenzenes, e.g., from the handling and combustion of fuels. These compounds are important precursors for the formation of secondary organic aerosol. Here we show that the oxidation of aromatics with OH leads to a subsequent autoxidation chain reaction forming highly oxygenated molecules (HOMs) with an O:C ratio of up to 1.09. This is exemplified for five single-ring ArHCs (benzene, toluene, o-/m-/p-xylene, mesitylene (1,3,5-trimethylbenzene) and ethylbenzene), as well as two conjugated polycyclic ArHCs (naphthalene and biphenyl). We report the elemental composition of the HOMs and show the differences in the oxidation patterns of these ArHCs. A potential pathway for the formation of these HOMs from aromatics is presented and discussed. We hypothesize that AV-OCs may contribute substantially to new particle formation events that have been detected in urban areas.Peer reviewe