16 research outputs found

    Optimum Design of a Five-phase Permanent Magnet Synchronous Motor for Underwater Vehicles by use of Particle Swarm Optimization

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    Permanent magnet synchronous motors are efficient motors which have widespread applications in electric industry due to their noticeable features. One of the interesting applications of such motors is in underwater vehicles. In these cases, reaching to minimum volume and high torque of the motor are the major concern. Design optimization can enhance their merits considerably, thus reduce volume and improve performance of motors. In this paper, a new method for optimum design of a five-phase surface-mounted permanent magnet synchronous motor is presented to achieve minimum loss and magnet volume with an increased torque. A multi-objective optimization is performed in search for optimum dimensions of the motor and its permanent magnets using particle swarm optimization. The design optimization results in a motor with great improvement regarding the original motor. Finally, finite element analysis is utilized to validate the accuracy of the design

    Comparison of several improved versions of particle swarm optimizer algorithm for parameter estimation of squirrel-cage induction motors / Mohammad Yazdani-Asrami, Mehran Taghipour Gorjikolaie and S. Asghar Gholamian

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    In this paper, three versions of Particle Swarm Optimization (PSO) are proposed to estimate the equivalent circuit parameters of squirrel cage induction motor. It is believed that how inertia weight changes during iterations can impact on final results. Constricted coefficients, linear model and exponential version are used as inertia weight, each of them presents different variations for inertia weight and consequently for particle movements and speed of such movements. In the linear version, particles start searching process with high speed and their speed will decrease by constant ramp, this kind of variation let to search all solution space in a short time and local search at the final iterations with low speed, also exponential version presents same treatment as linear version with non-linear variations in inertia weight and speed of movement. But, mathematical analysis shows that they trap into local minima and scientists presents constricted version to solve this problem. In order to evaluate proposed versions additional to make changing in PSO’s version, sensitivity of proposed methods is analyzed using three sets of data. Results confirm the ability of proposed method which can estimate parameters with a possible least error

    Influence of field-dependent critical current on harmonic AC loss analysis in HTS coils for superconducting transformers supplying non-linear loads : harmonic analysis of HTS transformers

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    There are two main obstacles in front of the development of high temperature superconducting (HTS) technology for electric power network applications; tape price and cooling cost. In order to reduce cooling cost, it is vital to evaluate AC transport current loss of the tapes precisely and then reduce it by some design innovative approaches. In addition, AC transport current loss in HTS material is a critical design variable for large-scale power network applications such as HTS transformers, superconducting fault current limiters, and power cables, since they are continuously carrying the network/load current during their operating life. In existing power networks, harmonic production sources are commonly used and thus, currents are distorted. Therefore, the effect of nonsinusoidal current on the critical apparatus in the network such as transformer must be studied. In this paper, AC transport current loss of a single-turn 2G YBCO HTS coil was modeled and numerically calculated under nonsinusoidal transport current using finite element method. Furthermore, influence of dependency of critical current density to magnetic field on the AC transport current loss of HTS coil when carries distorted currents was considered. It was observed that nonsinusoidal current causes excessive losses in HTS coil. On the other hand, a case study on an HTS transformer supplying non-linear load was considered to study the loss increment as well as heat load change. It was observed that current harmonics increases the AC loss, and heat load of transformer and decreases the efficiency, consequently

    Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

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    Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

    Technical and Financial Analysis of Photovoltaic Water Pumping System for GORGAN, IRAN

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    Abstract Because of human need for energy, extra special attention is in the usage of renewable-energy sources in recent years. On the other hand, environmental pollution is created with fossil energy. Photovoltaic (PV) energy is also one of the renewable-energy sources that are available in almost all parts of the globe, especially in Iran. One application of this energy is in water pumping system. In this paper, we precede the technical and financial study on photovoltaic water pumping system for irrigation of GORGAN's farm fields (one of Northern Province of Iran) with the RETScreen software tools. In order to the results, it is obvious that the usage of this clean energy causes the reduction on production costs during of its operation

    A COMPARATIVE STUDY BETWEEN DIRECT TORQUE CONTROL AND PREDICTIVE TORQUE CONTROL FOR AXIAL FLUX PERMANENT MAGNET SYNCHRONOUS MACHINES

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    This paper presents a comparative study between direct torque control (DTC) and predictive torque control (PTC) of Axial Flux Permanent magnet Machines (AFPM). In conventional DTC method for permanent magnet machines, only six actives voltage vectors of inverter are used to control torque and flux of machine. But in predictive torque control, in addition to six active voltage vectors, zero voltage vectors are used to control machine. So number of voltage vectors to control AFPM increases that leads to lower ripple of torque and flux. In predictive torque control, the response of torque and flux are computed for all possible switching states of inverter at every sample time according to discrete time model of machine, and then the switching state that optimizes ripple of torque and flux, will be applied in next discrete-time interval. Simulation results which compare the results of implementation of both methods and confirm the good performance of the proposed predictive torque control are presented

    Modeling and Control of a DFIG-Based Wind Turbine During a Grid Voltage Drop

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    Doubly-fed induction generators (DFIG) are widely used in wind energy generation systems. During a grid voltage drop, performance is degraded with rotor over current deteriorating the fault-ride through (FRT) capability of the DFIG wind-energy generation system. In this paper, a complete mathematical DFIG model is proposed. The rotor is considered fed by a voltage source converter whereas the stator is connected to the grid directly. Output power and electromagnetic torque are controlled using field-oriented control (FOC). Simulation results show the efficiency of the controller in exploiting the maximum power of wind
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