Journal articles: 'Electric engineering, estimates'

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Peterson, Michael, Chuntao Liu, Douglas Mach, Wiebke Deierling, and Christina Kalb. "A Method of Estimating Electric Fields above Electrified Clouds from Passive Microwave Observations." Journal of Atmospheric and Oceanic Technology 32, no. 8 (August 2015): 1429–46. http://dx.doi.org/10.1175/jtech-d-14-00119.1.

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AbstractA unique dataset of coincident high-altitude passive microwave and electric field observations taken by the NASA ER-2 aircraft is used to assess the feasibility of estimating electric fields above electrified clouds using ubiquitous global and multidecadal satellite products. Once applied to a global dataset, such a product would provide a unique approach for diagnosing and monitoring the current sources of the global electric circuit (GEC).In this study an algorithm has been developed that employs ice scattering signals from 37- and 85-GHz passive microwave observations to characterize the electric fields above clouds overflown by the ER-2 aircraft at nearly 20-km altitude. Electric field estimates produced by this passive microwave algorithm are then compared to electric field observations also taken by the aircraft to assess its potential future utility with satellite datasets. The algorithm is shown to estimate observed electric field strengths over intense convective clouds at least 71% (58%) of the time over land and 43% (40%) of the time over the ocean to within a factor of 2 from 85-GHz (37 GHz) passive microwave observations. Electric fields over weaker clouds can be estimated 58% (41%) of the time over land and 22% (8%) of the time over the ocean from 85-GHz (37 GHz) passive microwave observations. The accuracy of these estimates is limited by systematic errors in the observations along with other factors. Despite these sources of error, the algorithm can produce reasonable estimates of electric fields over carefully selected individual electrified clouds that differ from observations by less than 20 V m−1 for clouds that produce 200–400 V m−1 electric fields at 20 km.

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Nasution, Aminulsyah, Badriana Badriana, and Andik Bintoro. "Application of The Combined Method in Inventory Forecasting Electricity at PT PLN (Persero) ULP Sibuhuan." International Journal of Engineering, Science and Information Technology 2, no. 4 (December 19, 2022): 111–18. http://dx.doi.org/10.52088/ijesty.v2i4.348.

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The forecast of electricity consumption is a prediction of the use of electricity for the future by referring to the use of electricity in past data. Estimates of electricity consumption needs are intended to estimate how much electricity consumption is used by customers and must be provided by PT PLN (PERSERO) ULP SIBUHUAN as a provider of electrical energy services. Population growth occurs along with the development of an area, so it affects the demand for electricity and the need for electricity consumption. Load mapping must be done to maintain the continuity and distribution of electrical energy to customers. One way to preserve the continuity of service is to estimate electric power consumption using several forecasting methods. One of the methods that can be used is to combine several load forecasting methods called the combined method. The combined method is a model that incorporates various estimation methods, including econometrics, analytics, and trends, using historical customer data originating from BPS (Central Statistics Agency) Padang Lawas Regency and PT. PLN (PERSERO) ULP SIBUHUAN. The estimated load between 2021 and 2025 is 625,070,452 kWh, with an increase in electricity consumption of 20.7%, household expenses increasing by 1.8%, and business sector expenses by 1.35%. The method used is to calculate manually using Microsoft Excel to obtain forecasting values for population growth; increasing electricity consumption is very important for planning electric power generation, development, and planning of electric power distribution and mapping of loads on customers.

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Zaichenko, Stefan, Natalia Jukova, Dmitro Yakovlev, Vadym Shalenko, and Boris Korniychuk. "Intelligent multisensor system for identification ta estimates of the technical mill of electrical engineering." Gіrnichі, budіvelnі, dorozhnі ta melіorativnі mashini, no. 97 (July 29, 2021): 62–67. http://dx.doi.org/10.32347/gbdmm2021.97.0501.

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The problem of diagnosing power generating equipment by analyzing gases released into the atmosphere. The object of study is the process of diagnosing power generating equipment based on an internal combustion engine. The purpose of the work is the research is to develop the concept of the structure of the intellectual multisensory system of technical diagnostics of the autonomous electric generator on the basis of the internal combustion engine with use of electronic gas analyzers. To achieve this goal, the following tasks have been solved. To determine the possible states of the autonomous generator of electric energy on the basis of the internal combustion engine. For each state of the autonomous generator of electric energy to define characteristic gas evaporations. Choose a set of sensors that will determine the con-centration of components in the air with high accuracy. To develop an algorithm for the operation of a set of technical diagnostic equipment for the basic work of the principles of the neural system and electronic gas sensors. To check the developed diagnostic complex of electronic gas analyzers for determination of a condition of the independent generator of electric energy on the basis of the internal combustion engine. Improving the accuracy of localization in the search for a defect by additional chemical analysis of gases of power generating equipment is provided by the analysis of concentrations of hydrogen chloride, aldehydes, phenols and light hydrocarbons. A feature of the presented system for diagnosing the state of an autonomous electric power generator based on an internal combustion engine is the ability to perform diagnostic work without removing the equipment from work, which minimizes downtime. Also, the use of this system allows you to detect the development of a defect in the early stages of development, which prevents and significantly reduces the cost of repairing the energy source.

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Burlig, Fiona, James Bushnell, David Rapson, and Catherine Wolfram. "Low Energy: Estimating Electric Vehicle Electricity Use." AEA Papers and Proceedings 111 (May 1, 2021): 430–35. http://dx.doi.org/10.1257/pandp.20211088.

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We provide the first at-scale estimate of electric vehicle (EV) home charging. Previous estimates are based on conflicting surveys or are extrapolated from a small, unrepresentative sample of households with dedicated EV meters. We combine billions of hourly electricity meter measurements with address-level EV registration records from California households, including 64,000 EV owners. The average EV increases overall household load by 2.9 kilowatt-hours per day, well under half the amount assumed by state regulators. Results imply that EVs travel less than expected on electric power, raising questions about transportation electrification for climate policy.

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Volkov, M. A., and Z. Sh Ishmatov. "Synthesis of electric drive control systems using quality coefficient estimates." Russian Electrical Engineering 78, no. 11 (November 2007): 598–602. http://dx.doi.org/10.3103/s1068371207110077.

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Gakh, S. A., O. V. Khamisov, and S. V. Podkoval’nikov. "Dual Estimates in the Model of Expansion of Electric Power Systems." Automation and Remote Control 83, no. 5 (May 2022): 706–20. http://dx.doi.org/10.1134/s0005117922050046.

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Santini, Danilo J., Philip D. Patterson, and Anant D. Vyas. "Importance of Vehicle Costs, Fuel Prices, and Fuel Efficiency in Hybrid Electric Vehicle Market Success." Transportation Research Record: Journal of the Transportation Research Board 1738, no. 1 (January 2000): 11–19. http://dx.doi.org/10.3141/1738-02.

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Toyota’s introduction of a hybrid electric vehicle (HEV) named “Prius” in Japan and Honda’s proposed introduction of an HEV in the United States have generated considerable interest in the long-term viability of such fuel-efficient vehicles. A performance and cost projection model developed entirely at Argonne National Laboratory (ANL) is used to estimate costs. ANL staff developed fuel economy estimates by extending conventional vehicle modeling done primarily under the National Cooperative Highway Research Program. Together, these estimates are employed to analyze dollar costs versus benefits of two of many possible HEV technologies. Incremental costs and fuel savings are projected for a Prius-type low-performance hybrid (14.3-s 0 to 60 mph acceleration, Z60 time) and a higher-performance “mild” hybrid vehicle (11-s Z60 time). Each HEV is compared with a U.S. Toyota Corolla with automatic transmission (11-s Z60 time). The base incremental retail price range, projected a decade hence, is $3,200–$3,750, before considering battery replacement cost. Historical data are analyzed to evaluate the effect of fuel price on consumer preferences for vehicle fuel economy, performance, and size. The relationship among fuel price, the level of change in fuel price, and consumer attitude toward higher fuel efficiency also is evaluated. A recent survey on the value of higher fuel efficiency is presented and U.S. commercial viability of the hybrids is evaluated using discount rates of 20 percent and 8 percent. The analysis, with its current HEV cost estimates and current fuel savings estimates, implies that the U.S. market for such HEVs would be quite limited.

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Krupenev, D. S., and S. M. Perzhabinsky. "A reliability optimization algorithm with average dual estimates for electric power systems." Automation and Remote Control 78, no. 12 (December 2017): 2241–47. http://dx.doi.org/10.1134/s0005117917120128.

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Langston, Lee S. "Gas Turbines and Natural Gas Synergism." Mechanical Engineering 135, no. 02 (February 1, 2013): 30–35. http://dx.doi.org/10.1115/1.2013-feb-4.

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This article presents a study on new electric power gas turbines and the advent of shale natural gas, which now are upending electrical energy markets. Energy Information Administration (EIA) results show that total electrical production cost for a conventional coal plant would be 9.8 cents/kWh, while a conventional natural gas fueled gas turbine combined cycle plant would be a much lower at 6.6 cents/kWh. Furthermore, EIA estimates that 70% of new US power plants will be fueled by natural gas. Gas turbines are the prime movers for the modern combined cycle power plant. On the natural gas side of the recently upended electrical energy markets, new shale gas production and the continued development of worldwide liquefied natural gas (LNG) facilities provide the other element of synergism. The US natural gas prices are now low enough to compete directly with coal. The study concludes that the natural gas fueled gas turbine will continue to be a growing part of the world’s electric power generation.

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Onohaebi, S. O., and S. T. Apeh. "Electricity Network Planning: The Key to Efficient and Reliable Power Supply to Consumers." Advanced Materials Research 62-64 (February 2009): 172–80. http://dx.doi.org/10.4028/www.scientific.net/amr.62-64.172.

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This paper focuses on the need and procedure for the planning of electrical engineering infrastructure for any district/community in order to enhance reliability and efficiency of power supply to consumers. Almost all the towns/cities in Nigeria are unplanned and this has resulted in haphazard approach to Electricity Network Planning and implementation. A detailed theory, methodology and technical considerations, in compliance with both National and International standards are discussed in this paper. A proposed University campus was used to demonstrate the procedures involved in electricity network planning in order to achieve an efficient power supply. This involves the electric power supply, design concepts, load estimates and analysis, network distribution/equipment and sizing of cables and electrical panels taking into account the various modes of distribution. This paper also drew a simple analogy between Benin City and the Federal Capital Territory, Abuja, to illustrate the objective of the paper while highlighting the merits associated with planned electrical engineering infrastructure and suggested the ways to remedy the unplanned networks in Nigeria.

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Papaioannou, Athanasios, Stephen J. Elliott, Jordan Cheer, Jacques Cuenca, and Mansour Alkmim. "Power-based application of frequency-averaged 𝓁₁-norm regularisation technique for the synthesis of accelerating indoor tyre pass-by noise." Acta Acustica 5 (2021): 50. http://dx.doi.org/10.1051/aacus/2021044.

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Pass-by noise contribution analysis is an engineering procedure employed to estimate the contributions from various noise sources on a vehicle to the overall sound pressure level. This can be realised by placing a set of microphones close to the various sources to estimate their source strengths and then synthesising the response at a far-field linear array in the presence of the remaining sources. The results described in this paper rely on measured near-field pressure data close to the tyres of an electric vehicle under accelerating conditions. The number and position of the estimated virtual source strengths used is a compromise between complexity and accuracy, which has previously been addressed mostly empirically. A power-based, frequency-averaged 𝓁1-norm regularisation technique is investigated to optimise the equivalent source position and strength for one operating tyre and, subsequently, the far-field pass-by noise pressure estimates. It is shown that for the tyre under investigation, optimising the positions of only two equivalent sources over the frequency range of interest gives a good representation of the measured far-field spectra.

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Lim, Keumju, Justine Jihyun Kim, and Jongsu Lee. "Forecasting the future scale of vehicle to grid technology for electric vehicles and its economic value as future electric energy source: The case of South Korea." Energy & Environment 31, no. 8 (January 7, 2020): 1350–66. http://dx.doi.org/10.1177/0958305x19898283.

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With the world seeking ways to cope with climate change, the interest in and demand for electric vehicles are increasing as part of the efforts to resolve the issue of fine dust, especially in South Korea. The Korean government has consistently announced plans to promote electric vehicles as a means of transportation by providing benefits such as subsidies for electric vehicle purchase and expansion of charging infrastructure. Meanwhile, as electric vehicles continue to grow in number, the energy industry has become attentive to its role as a resource for power generation through vehicle to grid technology. This study analyzes electric vehicle consumer preferences using the discrete choice experiment (DCE) and found that there exists a clear nested structure in Korean consumers’ choice of vehicle. The study also estimates the amount of vehicle to grid electricity supply in the power market and calculates not only national but also individual economic benefit of electric vehicle owners participating in vehicle to grid services based on the estimated amount of electricity supplied. The results of scenario analysis indicate that the estimated electric vehicle supply in Korea will be about 560,000 units cumulatively and that the vehicle to grid electric vehicle power supply scale will reach 1.81 GW by 2030. The estimation shows that the economic benefit of vehicle to grid at the national power market level is 50.9 billion KRW per year, while the economic benefit at an individual level (per vehicle) is 104,151 KRW.

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Powell, Siobhan, Gustavo Vianna Cezar, and Ram Rajagopal. "Scalable probabilistic estimates of electric vehicle charging given observed driver behavior." Applied Energy 309 (March 2022): 118382. http://dx.doi.org/10.1016/j.apenergy.2021.118382.

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Movchan, N. V., S. Guenneau, A. B. Movchan, and R. C. McPhedran. "Estimates for localised transverse electric modes in multi-structured crystal fibres." Physica B: Condensed Matter 394, no. 2 (May 2007): 281–84. http://dx.doi.org/10.1016/j.physb.2006.12.052.

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Balandin, S. F., V. A. Donchenko, V. F. Myshkin, and V. A. Khan. "Physical processes in the channel of propagation of CO2 laser pulses during the generation of electric and magnetic fields." Izvestiya vysshikh uchebnykh zavedenii. Fizika, no. 3 (2021): 85–91. http://dx.doi.org/10.17223/00213411/64/3/85.

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The mechanisms of generation of electric and magnetic fields during the propagation of microsecond pulses of a CO2 laser in the atmosphere over long paths are considered. The range of radiated waves selected for research is substantiated. The power of the source required for the realization of the pre-breakdown and breakdown modes of interaction of radiation with the medium is estimated. The dependence of the observed signals on the conditions of radiation propagation is investigated. Comparison of theoretical estimates and results of outdoorexperiments is carried out.

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Isaacson, B. M., J. G. Stinstra, R. D. Bloebaum, P. F. Pasquina, and R. S. MacLeod. "Establishing Multiscale Models for Simulating Whole Limb Estimates of Electric Fields for Osseointegrated Implants." IEEE Transactions on Biomedical Engineering 58, no. 10 (October 2011): 2991–94. http://dx.doi.org/10.1109/tbme.2011.2160722.

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Ahn, Kyoungho, and Hesham A. Rakha. "Developing a Hydrogen Fuel Cell Vehicle (HFCV) Energy Consumption Model for Transportation Applications." Energies 15, no. 2 (January 12, 2022): 529. http://dx.doi.org/10.3390/en15020529.

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This paper presents a simple hydrogen fuel cell vehicle (HFCV) energy consumption model. Simple fuel/energy consumption models have been developed and employed to estimate the energy and environmental impacts of various transportation projects for internal combustion engine vehicles (ICEVs), battery electric vehicles (BEVs), and hybrid electric vehicles (HEVs). However, there are few published results on HFCV energy models that can be simply implemented in transportation applications. The proposed HFCV energy model computes instantaneous energy consumption utilizing instantaneous vehicle speed, acceleration, and roadway grade as input variables. The mode accurately estimates energy consumption, generating errors of 0.86% and 2.17% relative to laboratory data for the fuel cell estimation and the total energy estimation, respectively. Furthermore, this work validated the proposed model against independent data and found that the new model accurately estimated the energy consumption, producing an error of 1.9% and 1.0% relative to empirical data for the fuel cell and the total energy estimation, respectively. The results demonstrate that transportation engineers, policy makers, automakers, and environmental engineers can use the proposed model to evaluate the energy consumption effects of transportation projects and connected and automated vehicle (CAV) transportation applications within microscopic traffic simulation models.

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Chandel, P., M. M. Singh, A. K. Pati, V. Choudhary, and A. Parganiha. "Determination of short-interval time estimates in humans exposed to radiofrequency electromagnetic radiation." Journal of Environmental Biology 43, no. 03 (May 2, 2022): 369–76. http://dx.doi.org/10.22438/jeb/43/3/mrn-1807.

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Aim: The present study aimed at evaluating the effects of radiofrequency electromagnetic radiation exposure on short-interval time estimates in humans living in the vicinity of base transceiver stations. Methodology: The study was conducted in Phase-1 and Phase-2 with 1281 and 192 subjects, respectively. Four groups with one control were identified in each phase depending on the distance from the ground-based transceiver stations. The cognitive ability of the subjects of each group was determined by measuring short-interval time estimates, namely 10 s, 30 s, and 60 s, with time production and time reproduction methods using the Interval Clock software (Version 2.2). The electric field strength at each participant’s house was determined using the Narda Broadband Meter-550 with a probe EF0-391. Results: ANOVA results demonstrated a statistically significant difference in electric field strength among different zones around the installations of base transceiver stations (F4,1274 = 50.071; p<0.001). It was significantly higher in the inter-tower zone than in all other zones. The prevalence of various clinical problems was higher among the individuals living in the inter-tower zone. ANCOVA results revealed that the main factors zone, gender, and year of residence, did not significantly affect any short-interval time estimates. However, a statistically significant 'time of the day' variation in most of the target short-interval time estimates with both the methods for all the studied groups, except the inter-tower zone, was observed. Interpretation: The radiofrequency electromagnetic radiation emitted from base transceiver stations did not significantly impact the ability to estimate short-time intervals in humans.

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Das, Sanjoy, Padmavathy Kankanala, and Anil Pahwa. "Outage Estimation in Electric Power Distribution Systems Using a Neural Network Ensemble." Energies 14, no. 16 (August 6, 2021): 4797. http://dx.doi.org/10.3390/en14164797.

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Outages in an overhead power distribution system are caused by multiple environmental factors, such as weather, trees, and animal activity. Since they form a major portion of the outages, the ability to accurately estimate these outages is a significant step towards enhancing the reliability of power distribution systems. Earlier research with statistical models, neural networks, and committee machines to estimate weather-related and animal-related outages has reported some success. In this paper, a deep neural network ensemble model for outage estimation is proposed. The entire input space is partitioned with a distinct neural network in the ensemble performing outage estimate in each partition. A novel algorithm is proposed to train the neural networks in the ensemble, while simultaneously partitioning the input space in a suitable manner. The proposed approach has been compared with the earlier approaches for outage estimation for four U.S. cities. The results suggest that the proposed method significantly improves the estimates of outages caused by wind and lightning in power distribution systems. A comparative analysis with a previously published model for animal-related outages further establishes the overall effectiveness of the deep neural network ensemble.

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Domin, Rostyslav, Iurii Domin, and Ganna Cherniak. "Estimation of dynamic performances of the safe operation of high-speed electric train." Archives of Transport 41, no. 1 (March 13, 2017): 7–16. http://dx.doi.org/10.5604/01.3001.0009.7374.

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The process of implementation of new developments, in particular, new generation rolling stock holds a prominent place among the range of measures for organization of high-speed passenger rail transportation in Ukraine. The example of permission for use and the initial phase of work with interregional NRCS2 dual-mode electric trains produced by Hyundai-Rotem Corporation is the illustrative one in this context. Due to the detection of macro-cracks in bolster beams of the car body frames of these electric trains, namely in the areas of mounting of anti-yaw dampers, these trains were taken out of service until the completion of the modernization of problematic nodes. The comprehensive study on the determination of the safety parameters of electric trains was conducted to determine the causes of destruction of bolster beams. At the same time, bolster beams loading was estimated depending on the characteristics of anti-yaw dampers by means of computer simulation of the dynamics of motion of trailing and motor cars. The feasibility of selection of parameters for anti-yaw dampers mounted on electric train cars was assessed. The results of work will improve the safe operation of high-speed trains and increase the efficiency of estimates regarding the loading of bearing structures of underframes of the of rolling stock.

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Goel, L. "Prediction of customer load point service reliability worth estimates in an electric power system." IEE Proceedings - Generation, Transmission and Distribution 141, no. 4 (1994): 390. http://dx.doi.org/10.1049/ip-gtd:19949946.

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Movchan, A. B., N. V. Movchan, S. Guenneau, and R. C. McPhedran. "Asymptotic estimates for localized electromagnetic modes in doubly periodic structures with defects." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 463, no. 2080 (January 16, 2007): 1045–67. http://dx.doi.org/10.1098/rspa.2006.1800.

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The paper presents analytical and numerical models describing localized electromagnetic defect modes in a doubly periodic structure involving closely located inclusions of elliptical and circular shapes. Two types of localized modes are considered: (i) an axi-symmetric mode for the case of transverse electric polarization with an array of metallic inclusions; (ii) a dipole type localized mode that occurs in problems of waveguide modes confined in a defect region of an array of cylindrical fibres, and propagating perpendicular to the plane of the array. A thin bridge asymptotic analysis is used for case (i) to establish double-sided bounds for the frequencies of localized modes in macro-cells with thin bridges. For the case (ii), the electric and magnetic fields independently satisfy Helmholtz equations, but are coupled through the boundary conditions. We show that the model problem associated with localized vibration modes is the Dirichlet problem for the Helmholtz operator. We characterize defect modes by introducing a parameter called the ‘effective diameter’. We show that for circular inclusions in silica matrix, the effective diameter is accurately represented by a linear function of the inclusion radius.

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Castellani, Francesco, Davide Astolfi, and Francesco Natili. "SCADA Data Analysis Methods for Diagnosis of Electrical Faults to Wind Turbine Generators." Applied Sciences 11, no. 8 (April 7, 2021): 3307. http://dx.doi.org/10.3390/app11083307.

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The electric generator is estimated to be among the top three contributors to the failure rates and downtime of wind turbines. For this reason, in the general context of increasing interest towards effective wind turbine condition monitoring techniques, fault diagnosis of electric generators is particularly important. The objective of this study is contributing to the techniques for wind turbine generator fault diagnosis through a supervisory control and data acquisition (SCADA) analysis method. The work is organized as a real-world test-case discussion, involving electric damage to the generator of a Vestas V52 wind turbine sited in southern Italy. SCADA data before and after the generator damage have been analyzed for the target wind turbine and for reference healthy wind turbines from the same site. By doing this, it has been possible to formulate a normal behavior model, based on principal component analysis and support vector regression, for the power and for the voltages and currents of the wind turbine. It is shown that the incipience of the fault can be individuated as a change in the behavior of the residuals between model estimates and measurements. This phenomenon was clearly visible approximately two weeks before the fault. Considering the fast evolution of electrical damage, this result is promising as regards the perspectives of exploiting SCADA data for individuating electric damage with an advance that can be useful for applications in wind energy practice.

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Sharke, Paul. "Cheaper Watches." Mechanical Engineering 127, no. 02 (February 1, 2005): 33–35. http://dx.doi.org/10.1115/1.2005-feb-2.

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This article focuses on research that looks at wireless networks to lower the cost of monitoring plant machinery. General Electric (GE), through its Global Research arm in Niskayuna, N.Y., will investigate wireless motor monitoring; Eaton Corp. of Cleveland will examine wireless data acquisition from electrical distribution gear; and Minneapolis-based Honeywell Inc. will look at wireless process control. The projects, now completing their first phases, will produce demonstration systems when they wrap up two years from now. Distribution product maker Eaton estimates that 90 percent of the electrical switching equipment the company sells today can monitor the quality of the power running through it. The company further estimates that 90 percent of the buyers for that equipment do not wire it up to take advantage of the data's availability. Unlike the monitoring strategies of GE or Eaton, both of which would tolerate intermittent data and even interruptions without drastic consequences, real-time control for Honeywell means the wireless system needs to throw robustness and reliability into the bargain. The Honeywell business problem is one of building confidence that transmitting critical process data over short-range radio networks can happen without interference.

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Pal, Amit. "A Delphi Study of the Vehicular Emissions Control Strategies for the Capital City Delhi." International Journal of Advance Research and Innovation 1, no. 3 (2013): 56–65. http://dx.doi.org/10.51976/ijari.131309.

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In present work a Delphi study was commissioned to obtain the feedback and suggestions of the experts, having technical backgrounds, such as industrial, scientific, transport administration, engineering academics and engineering studies. The questionnaire was designed including a wide spectrum of different modes of transportation, beginning with bicycles and cycle rickshaws, encompassing all the prevalent modes of automobiles being used and including up to electric and solar powered vehicles. The collected data was analysed using the MATLAB software and the results have been used to estimate and then propose future emission modification factors. It is found that a large majority of experts were in favour of improving and subsidizing the public transportation system, enhancing the traffic management and accelerating the infra-structure projects. The preferences of the experts were given due consideration while proposing the future emission control strategies and making the estimates of the vehicle emissions in the next chapter.

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Tsitsikyan, G. N., and S. N. Kunaev. "Electrodynamic forces between flat circular coaxial coils." Transactions of the Krylov State Research Centre 4, no. 402 (October 14, 2022): 109–14. http://dx.doi.org/10.24937/2542-2324-2022-4-402-109-114.

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Object and purpose of research. Non-contact power transfer to various marine facilities. Subject matter and methods. The study relied on the methods of theoretical electric engineering. Main results. This paper gives analytical estimates for electrodynamic forces acting on inductively-coupled coaxial flat coils of circular shape. Conclusion. The study yielded the expressions for the electrodynamic forces in inductively coupled circular coils interfaced so as to perform non-contact power transfer.

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Gezelius, Mats, and Reza Mortazavi. "Effect of Having Solar Panels on the Probability of Owning Battery Electric Vehicle." World Electric Vehicle Journal 13, no. 7 (July 7, 2022): 125. http://dx.doi.org/10.3390/wevj13070125.

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Greenhouse gas emissions, produced by various sectors, including transportation, are significantly impairing the environment and drive climate change. Battery electric vehicles are increasingly seen as a way to alleviate these problems, but they must be charged with electricity produced through environmentally friendly methods. This paper investigates a possible relationship between battery electric vehicles and solar photovoltaic panels using ENABLE.EU household survey data from ten European countries in autumn 2017–spring 2018. Based on the estimates from a recursive bivariate probit model, it is found that the probability that a household owns a battery electric vehicle increases significantly if said household owns solar photovoltaic panels. This suggests that a policy encouraging the home charging of battery electric vehicles using solar photovoltaic panels that includes an energy storage facility could speed up the transition to the use of these vehicles.

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Pai, Suvrath, Benedikt Neuberger, and Michael Buchholz. "Adaptive model predictive stabilization of an electric cargo bike using a cargo load moment of inertia estimator." at - Automatisierungstechnik 69, no. 7 (June 30, 2021): 632–42. http://dx.doi.org/10.1515/auto-2021-0032.

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Abstract This paper addresses the problem of stabilizing an electric cargo bike. For most control objectives, it suffices to consider a cargo bike as a two-wheeler. However, in addition to the challenges posed to the control of traditional two-wheelers, electric cargo bikes also have the issue of the cargo load, which can significantly influence the driving behaviour. Hence, detection and estimation of the mass, position and inertial properties of the cargo load become important. Here, a Kalman filter based algorithm which estimates these parameters online is presented. For the estimation, measurements of the force exerted by the load are recorded using force sensors installed under the load. Along with these, roll angle and roll acceleration are also measured. The estimated values are then used by an adaptive model predictive controller (MPC) to adjust the model-parameters and stabilize a cargo bike while following a set trajectory.

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Pallonetti, Nicholas, and Brett D. H. Williams. "Refining Estimates of Fuel-Cycle Greenhouse-Gas Emission Reductions Associated with California’s Clean Vehicle Rebate Project with Program Data and Other Case-Specific Inputs." Energies 14, no. 15 (July 30, 2021): 4640. http://dx.doi.org/10.3390/en14154640.

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This work refines and updates estimates of the fuel-cycle greenhouse-gas (GHG) emission impacts of electric vehicles (EVs) rebated in California. Emissions are estimated using disaggregated data from the start of the rebate program through August 2018 (N = 269,902 participants) and factors that characterize fuel use and fuel life-cycle carbon intensity. GHG reductions are calculated for the first year of vehicle operation and subsequently scaled to reflect various operational timeframes. GHG reduction estimates over the first year of vehicle ownership total approximately 855 thousand metric tons of CO2-equivalent emissions, or 3.2 tons per vehicle. For nonfleet individuals, 54% of reductions are associated with “Rebate-Essential” participants who were most highly influenced by the rebate to purchase/lease. Comparing the estimated warranty-life benefit of 7.9 million tons of GHG reductions to USD 603 million in corresponding rebates results in USD 76 of state incentives per metric ton reduced over the first 100,000/150,000 miles of rebated vehicle use. Uncertainty in estimates presents opportunities for further refinement using additional participant-specific, time-variant, or otherwise detailed inputs. Nevertheless, the contributions of this work increased average first-year GHG reductions per vehicle by 35–45% compared to previous work, demonstrating that use of program-derived data can enhance the understanding of EV impacts.

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Rahighi, Alireza, Seyed Mohammad Hadi Seyed Kashani, and Behrang Sakhaee. "Developing a battery monitoring system software in matlab simulink environment using kalman filter." International Journal of Applied Power Engineering (IJAPE) 8, no. 1 (April 1, 2019): 1. http://dx.doi.org/10.11591/ijape.v8.i1.pp1-10.

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<p>Batteries play a vital role in electrical equipments and electrical engineering tools. In addition, in vehicles, the duties of the battery is very important, both in providing initial start energy for conventional cars and movement energy for electric vehicles. Therefore, the batteries could be counted as one of the most important segments of the electric vehicles. The batteries used in vehicles have various types. The most utilized of which in vehicles are the lead-acid batteries. Due to the noticeable privileges of the lead-acid batteries, they have been widely used in vehicles. The battery of the system, which have been processed in this project, is a traction battery with 24V nominal voltage and 500Ahours nominal capacity. In this project, the Kalman filter method has been used in order to estimate the remaining amount of battery’s charge. Kalman filter is an algorithm that estimates the state of a dynamic system using a set of measurements including fault in a specific time period. Having implemented the Kalman filter to the dynamic model of the battery, an estimation of state of the charge (SOC) and battery parameters have been acquired. This operation was simulated in Matlab Simulink environment and the results of the simulation were compared with the real amounts of the parameters achieved from prior experiments to make sure about the accuracy of the results. In the designed software, a graphical environment has been developed in order to providing an appropriate interface and simplifying the software performance. The program can be easily implemented to a real battery and calculate the desired parameters.</p>

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Nguyen, Thi Kim Lien, Hoang Nga Le, Van Hai Ngo, and Bang An Hoang. "CRITIC Method and Grey System Theory in the Study of Global Electric Cars." World Electric Vehicle Journal 11, no. 4 (December 15, 2020): 79. http://dx.doi.org/10.3390/wevj11040079.

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Science and technology development is a crucial for the elimination of air pollutants. The electric car industry, for example, contributes to minimizing emissions and climate change. The purpose of this study is to present an overview of electric car sales and its market share in 14 countries, from past to future, by integrating important criteria through the inter-criteria correlation (CRITIC) method in multi-criteria decision-making (MCDM), grey model first-order one variables (GM(1,1)), and grey relation analysis (GRA) method in grey system theory. First, the GM(1,1) estimates future terms based on historical time-series. Second, the objective weights of each variable, in every year, are determined by the CRITIC method. Finally, the research uses the GRA method for computing grades and ranks. The empirical result then reveals the performance and rank of electric car sales during the time period of 2016–2023. The analysis results thus reveal market share picture and direction of growth in the electric car industry.

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Widjiantoro, Bambang L., and Katherin Indriawati. "Sensor/actuator fault tolerant sliding mode control for anti-lock braking in a quarter electric vehicle." International Journal of Power Electronics and Drive Systems (IJPEDS) 11, no. 3 (September 1, 2020): 1220. http://dx.doi.org/10.11591/ijpeds.v11.i3.pp1220-1229.

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This paper proposes a scheme to improve regenerative ABS technology that already exists today by adding accommodation faults to the control system. The nominal control algorithm used is a sliding mode control so that system nonlinearities can be handled properly. The proposed method then is called sensor/actuator fault tolerant sliding mode control system. In designing the proposed control, there are two stages, namely estimation of faults, as well as the active mechanism for reconfiguring controls. Estimation of faults is done by using proportional-integral (PI) observers based on extended state space equation. Whereas the control signal reconfiguration is done actively by replacing measured output with their estimates and compensating for control signal using the actuator fault estimate. The simulation shows that the control system based on the proposed algorithm produces better dynamic performance than the sliding mode control (SMC) without fault tolerant feature. Furthermore, the system provides inherent characteristic for dealing with a minor fault in the hydraulic actuator.

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Steindl, Petr, and Petr Klenovský. "Dimension-Dependent Phenomenological Model of Excitonic Electric Dipole in InGaAs Quantum Dots." Nanomaterials 12, no. 4 (February 21, 2022): 719. http://dx.doi.org/10.3390/nano12040719.

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Permanent electric dipole is a key property for effective control of semiconductor quantum-dot-based sources of quantum light. For theoretical prediction of that, complex geometry-dependent quantum simulations are necessary. Here, we use k·p simulations of exciton transition in InGaAs quantum dots to derive a simple geometry-dependent analytical model of dipole. Our model, discussed here, enables reasonably good estimation of the electric dipole, caused in quantum dot by the elastic strain, including an externally induced one. Due to its apparent simplicity, not necessitating elaborate and time-consuming simulations, it might after experimental verification serve as a preferred choice for experimentalists enabling them to make quick estimates of built-in and induced electric dipole in quantum dots.

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Viña, Carlos, and Pascal Morin. "Micro air vehicle local pose estimation with a two-dimensional laser scanner: A case study for electric tower inspection." International Journal of Micro Air Vehicles 10, no. 2 (December 18, 2017): 127–56. http://dx.doi.org/10.1177/1756829317745316.

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Automation of inspection tasks is crucial for the development of the power industry, where micro air vehicles have shown a great potential. Self-localization in this context remains a key issue and is the main subject of this work. This article presents a methodology to obtain complete three-dimensional local pose estimates in electric tower inspection tasks with micro air vehicles, using an on-board sensor set-up consisting of a two-dimensional light detection and ranging, a barometer sensor and an inertial measurement unit. First, we present a method to track the tower’s cross-sections in the laser scans and give insights on how this can be used to model electric towers. Then, we show how the popular iterative closest point algorithm, that is typically limited to indoor navigation, can be adapted to this scenario and propose two different implementations to retrieve pose information. This is complemented with attitude estimates from the inertial measurement unit measurements, based on a gain-scheduled non-linear observer formulation. An altitude observer to compensate for barometer drift is also presented. Finally, we address velocity estimation with views to feedback position control. Validations based on simulations and experimental data are presented.

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VAN VAERENBERGH, STEVEN, ALBERTO SALCINES MENEZO, and OSCAR COSIDO COBOS. "DEVELOPMENT OF A SHORT-TERM PREDICTION SYSTEM FOR ELECTRICITY DEMAND." DYNA 96, no. 3 (May 1, 2021): 285–89. http://dx.doi.org/10.6036/9894.

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This article describes the development of a prediction method for the demand for electrical energy of a marketer's customer portfolio. The project is motivated by the economic benefit produced when the entity has accurate estimates of energy demand when buying energy in an electricity auction. The developed system is based on time series analysis and machine learning. As this system was part of a real-world project with data from a real environment, the article focuses on practical aspects of the design and development of system of these characteristics, such as the heterogeneity of data sources, and the delay in data availability. The predictions obtained by the developed system are compared with the results of a simple method used in practice. Keywords: energy demand prediction, electric power, machine learning, data-driven prediction.

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Ciller, Pedro, Sara Lumbreras, and Andrés González-García. "Network Cost Estimation for Mini-Grids in Large-Scale Rural Electrification Planning." Energies 14, no. 21 (November 5, 2021): 7382. http://dx.doi.org/10.3390/en14217382.

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Universal access to electricity is a crucial challenge in many developing countries. Establishing the electrification agenda of an underserved region is a complicated task where computer models play a critical role in calculating geospatial plans that efficiently allocate resources. Such plans should include—among other things—reasonable estimations of the designs and economic costs of standalone systems, mini-grids, and grid extensions. This implies that computer models need to estimate the network cost for many potential mini-grids. To that end, most planning tools apply quick rules of thumb or geometric methods that ignore power flows and electric constraints, which play a significant role in network designs. This paper presents a methodology that rapidly estimates any low-voltage mini-grid network cost without neglecting the impact of electrical feasibility in such cost. We present a case study where we evaluate our method in terms of accuracy and computation time. We also compare our method with a quick estimation similar to the ones most regional planning tools apply, showing the effectiveness of our method.

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Chiriac, Gabriel, Dumitru Dorin Lucache, Costică Nițucă, Alin Dragomir, and Seeram Ramakrishna. "Electric Bus Indoor Heat Balance in Cold Weather." Applied Sciences 11, no. 24 (December 10, 2021): 11761. http://dx.doi.org/10.3390/app112411761.

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The use of electric buses is increasing all over the world; this is due to the aim of limiting pollution in heavily urbanized areas. Using electric buses is one element of the desire to drop local pollution to zero emissions. The necessary electricity can be generated through centralized production, and in the case of electric buses, the pollution level is directly proportional to the amount of electricity produced. Their limited onboard power needs optimization, both in terms of traction and in auxiliary energy consumption. Heating in electric buses consumes the most energy from the auxiliaries, which can reduce the range of the vehicle up to a half, or more in the coldest days of the winter months. In this context, a precise estimation of heat loss and of the energy necessary for heating electric buses is crucial. Using the heat transfer theory, the heat balance method, and the U-value estimation, this article estimates the heat loss for a typical 12 m electric bus for a harsh winter day. Thermal simulations were made in order to estimate the heat flux through the structure of the bus (windows, walls, roof, and floor). Heat loss components were calculated in order to determine the most affected zones of the bus. The calculated data for the energy necessary to heat the bus were compared with the heating system data from an electric bus. By optimizing the necessary auxiliary energy consumption, the emissions at the source of electricity production will be significantly reduced.

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Trzynadlowski, Andrzej M. "Detection of Mechanical Abnormalities in Induction Motors by Electric Measurements." International Journal of Rotating Machinery 5, no. 1 (1999): 41–52. http://dx.doi.org/10.1155/s1023621x99000044.

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The paper gives an overview of the issues and means of detection of mechanical abnormalities in induction motors by electric measurements. If undetected and untreated, the worn or damaged bearings, rotor imbalance and eccentricity, broken bars of the rotor cage, and torsional and lateral vibration lead to roughly a half of all failures of induction motor drives. The detection of abnormalities is based on the fact that they cause periodic disturbance of motor variables, such as the speed, torque, current, and magnetic flux. Thus, spectral analysis of those or related quantities may yield a warning about an incipient failure of the drive system. Although the traditional non-invasive diagnostics has mostly been based on the signature analysis of the stator current, other media can also be employed. In particular, the partial instantaneous input power is shown, theoretically and experimentally, to offer distinct advantages under noisy operating conditions. Use of torque and flux estimates is also discussed.

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Villa, Daniel, Alejandro Montoya, and Aura Maria Herrera. "The Electric Riverboat Charging Station Location Problem." Journal of Advanced Transportation 2020 (November 12, 2020): 1–16. http://dx.doi.org/10.1155/2020/6527924.

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Nowadays, the electric mobility is mainly focused on urban areas. However, the use of Photovoltaic-assisted Charging Stations (PVCSs) can contribute to implement the electric mobility in rural areas disconnected from the national grid. Inspired by the new river operations with an Electric Boat (EB), we introduce a new location problem named the Electric Riverboat Charging Station Location Problem (ERCSLP). This problem estimates the necessary infrastructure for an EB to be able to perform a round trip. In this case, we decide the location of the PVCSs and the size of the EB battery aiming to minimize the sum of the PVCS and the EB battery costs. In this problem, we include the nonlinear behavior of the charging function and the variation of the solar radiation. For solving this problem, we propose a Mixed-Integer Linear Programming (MILP) formulation. For testing this MILP formulation, we build a set of instances based on real river transport operations that have the potential to migrate to the electric mobility. In our computational experiments, we show that our MILP formulation can find the optimal solution of the instances. Finally, we perform a sensitivity analysis and an economic viability analysis of the electric mobility in these operations.

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Koengkan, Matheus, José Alberto Fuinhas, Mônica Teixeira, Emad Kazemzadeh, Anna Auza, Fatemeh Dehdar, and Fariba Osmani. "The Capacity of Battery-Electric and Plug-in Hybrid Electric Vehicles to Mitigate CO2 Emissions: Macroeconomic Evidence from European Union Countries." World Electric Vehicle Journal 13, no. 4 (March 24, 2022): 58. http://dx.doi.org/10.3390/wevj13040058.

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The decarbonisation of the transportation sector is crucial to reducing carbon dioxide (CO2) emissions. This study analyses evidence from European countries regarding achievement of the European Commission’s goal of achieving carbon neutrality by 2050. Using panel quantile econometric techniques, the impact of battery-electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs) on CO2 emissions in twenty-nine European Union (EU) countries from 2010–2020 was researched. The results show that BEVs and PHEVs are capable of mitigating CO2 emissions. However, each type of technology has a different degree of impact, with BEVs being more suited to minimizing CO2 emissions than PHEVs. We also found a statistically significant impact of economic development (quantile regression results) and energy consumption in increasing the emissions of CO2 in the EU countries in model estimates for both BEVs and PHEVs. It should be noted that BEVs face challenges, such as the scarcity of minerals for the production of batteries and the increased demand for mineral batteries, which have significant environmental impacts. Therefore, policymakers should adopt environmentally efficient transport that uses clean energy, such as EVs, to reduce the harmful effects on public health and the environment caused by the indiscriminate use of fossil fuels.

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Talaat, Mohamed M., Andrew Seifried, Abhinav Anup, Gregory S. Hardy, and John M. Richards. "Simplified methods to estimate mean hazard due to updated ground motion model: Application to nuclear power plants in CEUS." Earthquake Spectra 37, no. 1_suppl (May 7, 2021): 1550–78. http://dx.doi.org/10.1177/87552930211007499.

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Two methods were developed to estimate updated mean seismic hazard for existing probabilistic seismic hazard analyses (PSHAs) due to a change in the ground motion model (GMM). Both methods were used to estimate updated hazard at nuclear power plant (NPP) sites in the Central and Eastern United States (CEUS) for a change from the Electric Power Research Institute (EPRI) 2013 GMM to the Next Generation Attenuation (NGA)-East GMM. These methods present efficient tools to inform decisions on whether to perform a full PSHA revision or other detailed evaluations, especially when a large number of sites must be analyzed. A Simplified Hazard (SiHaz) method was developed to estimate mean hazard explicitly using a reduced PSHA logic tree that incorporates the updated GMM and potential changes in the site response model. An alternative scaling method was independently developed to be applied directly to current CEUS NPP hazard. Both methods were validated using updated PSHA results at several sites. Estimates at 46 NPP sites using both methods showed good agreement for mean annual frequencies of exceedance between 1E-4 and 1E-5/yr.

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Martins, Vanderlei Affonso, David Alves Castelo Branco, and Michelle Carvalho Metanias Hallack. "Economic Effects of Micro- and Mini-Distributed Photovoltaic Generation for the Brazilian Distribution System." Energies 15, no. 3 (January 20, 2022): 737. http://dx.doi.org/10.3390/en15030737.

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The micro- and mini-distributed generation (MMDG) has significantly increased after the normative resolution No. 482/2012 in Brazil; the installed capacity surpassed 7 GW in 2021. In the international context, a similar event was observed, whose process generated a cross-subsidy for other consumers, in addition to other problems that affect the economic balance of concessionaires. To mitigate this issue, the National Electric Energy Agency (ANEEL) is in the process of revising current rules. Thus, this study estimates the weight of this decision, through a methodology adapted from international assessment models, based on information from the Brazilian regulatory system. In order to achieve it, this paper presents metrics to define the potential market MMDG, based on the consumption patterns of consumers. Then, through time series analysis, the MMDG demand curve is estimated under two scenarios up to 2030. Finally, the economic impact on tariff adjustments and revisions, and their effect on the electric power concessionaires are evaluated. In the distribution companies of the Enel Group alone, economic losses are estimated at USD 1.2 billion by 2030; 53% of this will be passed on to consumers’ tariffs. Thus, based on international experiences, it can be concluded that the best model is the adequate grid remuneration.

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Palmer, Karen, and Hadi Dowlatabadi. "Implementing Social Costing in the Electric Utility Industry1." Energy & Environment 4, no. 3 (September 1993): 197–220. http://dx.doi.org/10.1177/0958305x9300400301.

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Social costing refers to the regulatory practice of requiring electric utilities to incorporate external costs into utility decision making. This practice is being adopted by a growing number of state public utility commissions (PUCs). The effectiveness of this new regulatory approach in reducing the social costs of supplying electricity will depend on the range of utility decisions covered. We use a utility planning model and illustrative estimtes of environmental costs to analyze the implications of different social costing regimes for generation technology choice, social and private costs of electricity supply and electricity price. Due to large differences in private costs across technologies and fuel types, social costing regulation has little or no effect on the utility's investment decisions, dispatch of generators or output price for many of the external cost estimates considered. Applying social costing exclusively to new generating units could result in increased use of existing units and higher social cost electricity production.

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Filippov, A. S., I. A. Korotkin, I. O. Urazov, O. A. Ushakova, and V. A. Vasil’ev. "Thermo-electrical regime of a vertical electrolyzer: Estimates of the effects of electric conductivity and gas evolution." Journal of Engineering Thermophysics 17, no. 3 (August 10, 2008): 218–26. http://dx.doi.org/10.1134/s1810232808030065.

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Danielis, Romeo, Mariangela Scorrano, Marco Giansoldati, and Stefano Alessandrini. "The Economic Case for Electric Vehicles in Public Sector Fleets: An Italian Case Study." World Electric Vehicle Journal 11, no. 1 (March 10, 2020): 22. http://dx.doi.org/10.3390/wevj11010022.

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The paper investigates whether it makes economic sense to use electric vehicles (EVs) in the public sector fleet. Thanks to the data collected in 2018 in 77 public sector entities in an Italian region, Friuli Venezia Giulia, we compare the total cost of ownership of a battery electric vehicle with that of a similar internal combustion engine one. We provide estimates for four scenarios (status quo, social cost internalization, price discounts and a combination of the last two) for three groups of public entities (local health authorities, municipalities and special purpose authorities) regarding passenger cars and mixed-use small light commercial vehicles. We find that, with the current price and cost structure, it makes economic sense to adopt EVs for a positive although relatively small percentage of the public sector fleet.

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Fraiha Lopes, Ramz L., Simone G. C. Fraiha, Vinicius D. Lima, Herminio S. Gomes, and Gervásio P. S. Cavalcante. "Hybrid ARIMA and Neural Network Modelling Applied to Telecommunications in Urban Environments in the Amazon Region." International Journal of Antennas and Propagation 2020 (February 24, 2020): 1–14. http://dx.doi.org/10.1155/2020/2671746.

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This study explores the use of a hybrid Autoregressive Integrated Moving Average (ARIMA) and Neural Network modelling for estimates of the electric field along vertical paths (buildings) close to Digital Television (DTV) transmitters. The work was carried out in Belém city, one of the most urbanized cities in the Brazilian Amazon and includes a case study of the application of this modelling within the subscenarios found in Belém. Its results were compared with the ITU recommendations P. 1546-5 and proved to be better in every subscenario analysed. In the worst case, the estimate of the model was approximately 65% better than that of the ITU. We also compared this modelling with a classic modelling technique: the Least Squares (LS) method. In most situations, the hybrid model achieved better results than the LS.

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Maroufmashat, Azadeh, and Michael Fowler. "Policy Considerations for Zero-Emission Vehicle Infrastructure Incentives: Case Study in Canada." World Electric Vehicle Journal 9, no. 3 (August 23, 2018): 38. http://dx.doi.org/10.3390/wevj9030038.

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Transportation accounts for more than 20% of the total Greenouse Gas (GHG) emissions in Canada. Switching from fossil fuels to more environmentally friendly energy sources and to Zero-Emission Vehicles (ZEVs) is a promising option for future transportation but well to wheel emission and charging/refuelling patterns must also be considered. This paper investigates the barriers to and opportunities for electric charging and hydrogen refueling infrastructure incentives in Ontario, Canada and estimates the number of Internal Combustion Engine Vehicles (ICEVs) that would be offset by infrastructure incentives. The paper also assesses the potential of electric and hybrid-electric powertrains to enable GHG reductions, explores the impact of the electricity supply mix for supporting zero-emission vehicles in different scenarios and studies the effect of the utility factor for PHEVs in Ontario. The authors compare the use of electric vehicle charging infrastructures and hydrogen refueling stations regarding overall GHG emission reductions for an infrastructure incentive funded by a 20-million-dollar government grant. The results suggest that this incentive can provide infrastructure that can offset around 9000 ICEVs vehicles using electricity charging infrastructure and 4000–8700 when using hydrogen refuelling stations. Having appropriate limitations and policy considerations for the potential 1.7 million electric-based vehicles that may be in use by 2024 in Ontario would result in 5–7 million tonne GHG avoidances in different scenarios, equivalent to the removal of 1–1.5 million ICEVs from the road.

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Deivasigamani, Revathy, Nur Nasyifa Mohd Maidin, M. F. Mohd Razip Wee, Mohd Ambri Mohamed, and Muhamad Ramdzan Buyong. "Dielectrophoresis Prototypic Polystyrene Particle Synchronization toward Alive Keratinocyte Cells for Rapid Chronic Wound Healing." Sensors 21, no. 9 (April 25, 2021): 3007. http://dx.doi.org/10.3390/s21093007.

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Diabetes patients are at risk of having chronic wounds, which would take months to years to resolve naturally. Chronic wounds can be countered using the electrical stimulation technique (EST) by dielectrophoresis (DEP), which is label-free, highly sensitive, and selective for particle trajectory. In this study, we focus on the validation of polystyrene particles of 3.2 and 4.8 μm to predict the behavior of keratinocytes to estimate their crossover frequency (fXO) using the DEP force (FDEP) for particle manipulation. MyDEP is a piece of java-based stand-alone software used to consider the dielectric particle response to AC electric fields and analyzes the electrical properties of biological cells. The prototypic 3.2 and 4.8 μm polystyrene particles have fXO values from MyDEP of 425.02 and 275.37 kHz, respectively. Fibroblast cells were also subjected to numerical analysis because the interaction of keratinocytes and fibroblast cells is essential for wound healing. Consequently, the predicted fXO from the MyDEP plot for keratinocyte and fibroblast cells are 510.53 and 28.10 MHz, respectively. The finite element method (FEM) is utilized to compute the electric field intensity and particle trajectory based on DEP and drag forces. Moreover, the particle trajectories are quantified in a high and low conductive medium. To justify the simulation, further DEP experiments are carried out by applying a non-uniform electric field to a mixture of different sizes of polystyrene particles and keratinocyte cells, and these results are well agreed. The alive keratinocyte cells exhibit NDEP force in a highly conductive medium from 100 kHz to 25 MHz. 2D/3D motion analysis software (DIPP-MotionV) can also perform image analysis of keratinocyte cells and evaluate the average speed, acceleration, and trajectory position. The resultant NDEP force can align the keratinocyte cells in the wound site upon suitable applied frequency. Thus, MyDEP estimates the Clausius–Mossotti factors (CMF), FEM computes the cell trajectory, and the experimental results of prototypic polystyrene particles are well correlated and provide an optimistic response towards keratinocyte cells for rapid wound healing applications.

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Jazea, Najim Abdallah, Mohammed Hussein Ali, and Noora Hani Sherif. "Evaluate consumption of electric energy of residential sector and its environmental and economic effects." Indonesian Journal of Electrical Engineering and Computer Science 28, no. 1 (October 1, 2022): 41. http://dx.doi.org/10.11591/ijeecs.v28.i1.pp41-48.

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The demand for electric power in Iraq increased significantly after 2003, The residential sector is the most consumption according to the statistics of the iraqi ministry of electricity (ICME) and the data published by the international energy agency (IEA). In this paper, a survey was applied for a sample of the population; whereby questionnaire models were used for some of the most energy consuming devices to determine the estimates of supply and demand for energy, and some data from the Iraqi Ministry of Electricity available until 2020 was relied on to predict the consumption of electrical energy for next ten years. Five Scenarios have been implemented for energy saving, CO2 gas emission and electricity production cost that reduce the accumulative energy consumed for the coming years.

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Zhu, Beizuo, Weiyang Chen, and Luo Chen. "Electromagnetic Vector Sparse Nested Array: Array Structure Design, Off-Grid Parameter Estimation Algorithm." Mathematical Problems in Engineering 2021 (March 26, 2021): 1–14. http://dx.doi.org/10.1155/2021/5525221.

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In this paper, a new array structure of sparse nested array (SNA) for electromagnetic vector sensor is designed. An electromagnetic vector sensor is composed of six spatially colocated, orthogonally oriented, diversely polarized antennas, which can measure three-dimensional electric and magnetic field components. By introducing sparse factor (SF) between every adjacent sensor, the proposed SNA has flexibility of extending the array aperture and reducing the mutual coupling effect. Meanwhile, a low-complexity multiparameter estimation algorithm is proposed for SNA. First, the vectorization operation for array manifold ensures the large degrees of freedom for multiparameter estimation, where the initial coarse estimates decrease search range. In addition, the improved off-grid orthogonal matching pursuit method obtains joint direction of arrival (DOA) and polarization estimates with a relatively small overcomplete dictionary because this off-grid method achieves high performance even if the estimates do not fall on the grid of the dictionary. Theoretical analysis and simulation results verify the superiority of the proposed array structure and the algorithm.

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Journal articles on the topic 'Electric engineering, estimates'

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