Loss Of Predictive Power Research Articles

Modelling of dynamic losses in soft ferrite cores

In this paper a time domain model of the dynamic behavior of ferrite cores is implemented and discussed. This model is based on the magnetic field decomposition in three parts dealing with the static anhysteretic magnetization, the static hysteretic magnetization and the dynamic magnetization processes. These three components are depending on the magnetic induction values and derivative in time domain by means three functions properly identified. In particular, the capability of the model for power losses prediction is discussed, also in comparison with the classical approaches defined on both frequency domain and time domain by Steinmetz. The model parameters are identified for a suitable Mn–Zn ferrite inductor with toroidal core, and the reliability of the method for the prediction of the magnetization processes, under sinusoidal and not sinusoidal excitations, is assessed for the typical work frequency range of magnetic components in power electronics devices.

Power loss prediction in asymmetric spur gear considering gear tooth dynamic load

In many gear drives, one side of the flank is subjected to relatively higher load for a longer duration than the other side. Asymmetric spur gears with drive side pressure angle higher than the coast side reflects this functional difference. Conventional design criteria and procedures followed for symmetric spur gears are suitably modified and applied to predict the gear tooth bending, contact stress and power loss in asymmetric spur gears. Quasi-static gear tooth load and empirical friction coefficient formulae were applied in the past to predict the sliding power loss in asymmetric spur gears. In the present work, Finite element method is used to determine the time varying mesh stiffness of the normal contact ratio asymmetric spur gear tooth. Computed gear tooth stiffness is used to predict the dynamic load at two different speeds under non-extended contact condition. Sliding power loss during the course of meshing is analytically calculated under quasi static and dynamic load conditions. Study demonstrates the difference in sliding power loss computed based on friction formulae and empirical friction coefficient formulae under static and dynamic load.

Analytical Switching Loss Model for GaN-Based Control Switch and Synchronous Rectifier in Low-Voltage Buck Converters

In this paper, an analytical switching loss model for a gallium nitride (GaN) based control switch (CS) and synchronous rectifier (SR) in low-voltage buck converters is proposed. Based on the consideration of parasitic inductances, SR reverse conduction voltage drop, and overshoot current effect caused by output capacitance of SR, the total switching loss is modeled with regard to both CS and SR, which can lead to more accurate prediction of power loss and system efficiency in low-voltage buck converters. The modeling results show that the percentage of SR switching loss in total switching loss is 25.4% in the 12–1.2-V converter, which is far larger than the 6.3% in the 48–5-V converter, and this verifies the necessity of including SR into the model for low-voltage converters. Experiment results exhibit an average increase of 52.3% and 66.1% in the accuracy of predicted system efficiency and converter power loss through the proposed model with SR than conventional models from 400 kHz to 1 MHz.

Analysis of rolling bearing power loss models for twin screw oil injected compressor

The mechanical losses inside a screw compressor limit the performance of the compressor in terms of efficiency. These losses arise due to relative motion between elements inside the screw compressor. The estimation of mechanical losses predicted in the literature is around 10-15% of the total shaft power. One of the elements which contribute significantly to these losses is rolling element bearings. There are numerous mathematical models available which predict power losses in the rolling bearings.The objective of this paper is to study different models to predict power loss for rolling bearings and to predict the power losses for the bearings used for oil injected, twin screw compressor. A comparison between different power loss models for different operating conditions of compressor is also presented in this paper and results of analysis are compared with available experimental observations. The analysis helps to determine suitable power loss model for different operating conditions and more realistic predictions of the power losses. This allows designers for more accurate estimation of the performance of screw compressors.

Prediction of carotenoid content in tomato fruit using a fluorescence screening method

Many nondestructive techniques have been developed and used for the prediction of phytochemical content in fruit. Colorimeters are usually used to predict carotenoid content in tomato fruit. The objective of this study was to explore the accuracy of the fluorescence indices as a predictor of carotenoid content in tomato fruit compared to the accuracy of the color indices. Several fluorescence indices were highly correlated with the color indices. Especially, FRF_B, FRF_G, FRF_R, BGF_B, BGF_G, and ANTH_RG were highly correlated with a* and a*/b* with a correlation R between 0.914 and 0.965 (R2 between 0.83 and 0.93). FRF_B, FRF_G, BGF_B and BGF_G were highly correlated with lycopene (R2 between 0.31 and 0.43) and with β-carotene (R2 between 0.20 and 0.27). These correlations were as high as the correlations between the carotenoids and key color indices such as a* and a*/b* values (R2 between 0.37 and 0.39 for lycopene and between 0.24 and 0.27 for β-carotene). When lycopene and β-carotene were predicted using principal component analysis, six fluorescence indices (BGF_R, BGF_G, BGF_B, FRF_R, FRF_G, and FRF_B) showed similar predictive performance when compared to color indices based on cross-validation. A potential shortcoming of a colorimetric method can be found when a sample surface has non-homogeneous colors because it measures only a small area, and this fluorescence method can overcome the shortcoming due to a larger measurement area. Therefore, from practical perspectives, the use of fluorescence indices can be a more effective nondestructive method without a loss of predictive power for the carotenoid content of tomato fruit when compared to the traditional use of color indices.

A discussion of Arana, A., Larrañaga, J., & Ulacia, I. (2019). Partial EHL friction coefficient model to predict power losses in cylindrical gears. Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology, Vol. 233(2) 303–316

There is presently a heated debate within the field of elastohydrodynamic lubrication (EHL). Some have attributed this to a controversy regarding the shear dependence of viscosity. However, the real nature of the debate is, as it has been for more than 40 years, whether or not to correctly describe the piezoviscous effect. If real pressure dependence of viscosity were to be employed in all EHL analyses, then the true nature of shear dependence would become apparent and the debate would end.

A Novel AC Power Loss Model for Ferrite Power Inductors

Recent studies have proved that sustainable saturation operation of Ferrite Power Inductors (FPIs) allows reducing the inductor size and increasing the power density in Switch-Mode Power Supply (SMPS) applications. This paper discusses a new behavioral model for reliable prediction of ac power loss in FPIs, including the effects of saturation. The new model has been identified by means of the Genetic Programming (GP) algorithm combined with a Multi-Objective Optimization (MOO) technique, starting from large sets of power loss experimental measurements. The proposed ac power loss model uses as input variables the voltage and switching frequency imposed to the inductor by the SMPS operation, while the dc inductor current is used as a parameter expressing the impact of saturation. Such quantities can be easily determined for whatever converter topology and in real-world switching operation, thus confirming the readiness and the easiness-to-use of the proposed behavioral model. The results of experimental tests presented in this paper prove the reliability of the power loss predictions, also by correctly accounting for the impact of inductors saturation.

Conductor losses calculation in two-dimensional simulations of H-plane rectangular waveguides

ABSTRACTThis paper presents a novel numerical approach to simulate H-plane rectangular-waveguide microwave circuits considering a reduced quasi-2D simulation domain with benefits for computational cost and time. With the aim to evaluate the attenuation of the full height 3D component, we propose a modified expression for the waveguide top/bottom wall conductivity. Numerical 2D simulations are validated against results from full wave 3-D commercial electromagnetic simulator. After a benchmark on a simple straight waveguide model, the method has been successfully applied to an asymmetric un-balanced power splitter, where an accurate power loss prediction is mandatory. Simulation time and memory consumption can be reduced by a factor ten and seven respectively, in comparison with complete 3D geometries. Finally, we show that, also for quasi-2D E-bend waveguide, a case where the translational H-plane symmetry is broken, the error on conductor losses computation is mitigated by our approach since the method remains still valid in a first approximation.

Effect of Learning Rate on GRNN and MLP for the Prediction of Signal Power Loss in Microcell Sub-Urban Environment

Effect of Learning Rate on GRNN and MLP for the Prediction of Signal Power Loss in Microcell Sub-Urban Environment

Investigation and Comparison of Generalization Ability of Multi-Layer Perceptron and Radial Basis Function Artificial Neural Networks for Signal Power Loss Prediction

Investigation and Comparison of Generalization Ability of Multi-Layer Perceptron and Radial Basis Function Artificial Neural Networks for Signal Power Loss Prediction

Application of fuzzy regression analysis method for determination of electric power losses in intrafactory power supply networks

One of the main objectives of the development of modern industry in Russia, along with an increase in the absolute volumes of electric power (EP) production, is to strengthen control over its more rational use. Saving EP and reducing the cost of its transmission along power distribution networks is of great importance for the country's energy sector. In terms of their physical nature, in terms of production, transmission and consumption, EP losses are no different from EP served to consumers. Therefore, the assessment of power losses in electrical networks is based on the same economic principles as the assessment of energy served to consumers. EP losses have a significant impact on the technical and economic parameters of the network, since the cost of losses is included in the estimated cost (reduced costs) and cost price (annual operating costs) of EP transmission. The cost component of losses in the cost of EP transmission has a large proportion. The article presents the results of research on the possibility of application of fuzzy regression analysis for problems of assessment and prediction of electric power losses in intrafactory networks. Initial information on the network is uncertain to some extent, which complicates application of traditional methods. The calculation is presented for conventional and fuzzy regression models, along with estimation of error of these models. The relevance of application of fuzzy regression analysis methods is determined by the difficulty of obtaining reliable information about the circuit and regime parameters of intrafactory networks, the probabilistic nature of change of the modes, as well as a whole complex of affecting factors, which are generally challenging for quantitative assessment. Advantages of application of fuzzy regression analysis consist in obtaining confidence intervals of required variables (value of electric power losses) for schemes of networks with uncertain initial information on their parameters, which is characteristic of intrafactory power supply systems, and enables to consider dynamics of their variation.

CHARACTERISTIC LAYOUTS OF DISTRIBUTION NETWORKS WITH THE ANALYSIS OF VOLTAGE DEVIATIONS AND EXPEDIENCY OF ITS CONTROL

Urgency of the research. It is well-known that electric energy characteristics are the levels of electromagnetic compatibility of electric grid providing adequate performance of any electrical means connected to the grid if the electric energy characteristics do not exceed permitted values. In the context of general idea of electromagnetic compatibility of consumers within power supply grids, power quality is the topical problem of modern electric-power supply industry. Target setting. The issue of assessing the possibility of ensuring the quality of electricity in terms of voltage deviation by consumers is very important. The problem of voltage fluctuations is relevant, so that voltage deviation have a negative impact on functioning electrical equipment Actual scientific researches and issues analysis. Papers [2-11] are devouted the effective management methods of electrical energy consumption. The articles [6-8] shows that under present conditions only system approach ensures accurate identification and prediction of electric power losses in distribution networks that are characterized by considerable ambiguity. Uninvestigated parts of general matters defining. Generalized diagram of the voltage modes characterizes the state for the entire distribution network connected to the main substation; it consists of the branched 10 kV network, all the distribution transformers, and all the 0.4 kV networks connected to those transformers. Along with the generalized diagram, values of the available voltage losses have been obtained; those values occur within 10 kV and 0.4 kV networks in terms of the favourable conditions of voltage control and the initial values of the admissible voltage deviations of electrical receivers. Moreover, that is the basis to determine operating position of control tappings of distribution transformers. The research objective. Since one of the important characteristics of electrical energy is the deviation of the voltage in the network, it is advisable to carry out its analysis in the urban distribution networks in terms of Levanevska substation, town of Zaporizhzhia. To simplify practical representation of possible voltage modes on the main substation buses and within the whole distribution networks, it is expedient to use graphic representation – so-called generalized diagram of voltage modes. That diagram helps make the analysis of voltage modes more demonstrative than analytical calculation; besides, the diagram gives great possibilities for further study. The statement of basic materials. While analyzing voltage mode in the distribution networks and determining the required law of voltage control in the main substation (MS), one should take into consideration great amount of factors effecting and complicating that study. Those factors include the following: changes in the operating mode of the network, differences in the points of connections of electrical receivers (ER) to the distribution network, differences in possible operating positions of the control tappings in the distribution transformers (DT), differences in the points of DT connections to 10 kV network, available dead zones of automatic voltage controller etc. Owing to that fact, it is required to perform generalized analysis of the voltage mode and conditions of its control within 10 kV and 0.4 kV distribution networks and on main substation buses. To do that, one should apply probabilistic calculation methods. At the same time, it is expedient to use graphic depiction (so-called generalized diagram (GD) of the voltage modes) to simplify representation of possible voltage modes on MS buses and within the whole distribution network. That diagram will help make the analysis of the voltage modes more clearly arranged than analytic calculations; moreover, it gives great opportunities for further study. Conclusions. Voltage deviation in the distribution networks has been performed and expediency of the voltage deviation control for electrically closest and farthest consumers have been analyzed in terms of Levanevska substation, town of Zaporizhzhia. Expediency of practical application of generalized diagrams for that purpose has been demonstrated. It has been defined that in the modes of maximum and minimum loads, voltage exceeds the admissible deviation norms of ± 5 %. Conclusion has been made on the expediency of more careful voltage control. Generalized diagram for 0-1 and 9-10 hours with the maximum voltage deviations has been constructed. Graph of dependences has been developed; formula of voltage deviations in the main substation, due to the voltage passing along that line, has been defined. According to the voltage data before and after the implementation of control, graphs of voltage deviations on the distribution transformer and in terms of the farthest consumer have been constructed.

Power Loss Prediction for Aging Characteristics and Condition Monitoring for Parallel‐Connected Power Modules Using Nonlinear Autoregressive Neural Network

Power modules connected in parallel may have different electrothermal performance variances resulting from aging because of the nonuniform rate of degradation; different electrothermal performance variances mean different current sharing, different junction temperature, and power losses, which will directly influence the overall characteristics of them. Thus, it is essential to monitor the condition and evaluate the degradation grade to improve the reliability of large‐scale power modules. In this paper, the impact of thermal resistance difference on current sharing, junction temperature, and power loss of parallel‐connected power modules has been discussed and analyzed. Additionally, a methodology is proposed for condition monitoring and evaluation of the power modules without intruding them by recognizing the increase in external power loss due to internal degradation from aging. In this method, power modules are deemed as a whole system considering only external factors associated with them, all important electrical and thermal parameters are classified as the inputs, and power loss is considered as the output. Firstly, power dissipation is predicted by models using NARX (nonlinear autoregressive with exogenous input) neural network. Then, a monitoring method is illustrated based on the prediction model; a reasonable criterion for the error between the normal and the predicted real‐time power loss is established. Finally, the real‐time condition and the degradation grade of aging can be evaluated so that the operator can take suitable operating measures by means of this approach. Experimental results validated the effectiveness of the proposed methodology.

渐开线直齿轮机械功率损失和啮合效率预测

渐开线直齿轮机械功率损失和啮合效率预测

Model-based aging tolerant control with power loss prediction of Proton Exchange Membrane Fuel Cell

Proton Exchange Membrane Fuel Cells are promising energy converters that allow powering vehicles or buildings in a clean manner. Nevertheless, their performance are affected by faults and irreversible degradation mechanisms that are far from being fully understood. Consequently, during the last decade, researches have been conducted on the diagnostic of faults of this promising converter. Nevertheless, aging was never the subject of a particular attention concerning control. As a result, this paper proposes an aging tolerant control strategy for Proton Exchange Membrane Fuel Cells. It aims at generating the load current reference taking the state of health into account. Moreover, using a model inversion of an Energetic Macroscopic Representation with time-varying parameters, the coherent references of input flows of gas can be calculated. Finally, the paper details a method to identify and predict the maximum power the fuel cell is able to provide at present time based on a Maximum Power Point Tracking algorithm. Also this algorithm aims at forecasting the Remaining Useful Life for a given power reference. This method is validated on a simulation case.

Bulk temperature prediction of a two-speed automatic transmission for electric vehicles using thermal network method and experimental validation

Nowadays, the development of electric vehicle equipped with a two-speed automatic transmission has become a hotspot. As well known, the automatic transmission operates with power loss including gear meshing loss, bearing loss, and oil churning loss. This paper focuses on the bulk temperature prediction of a two-speed automatic transmission using thermal network method. An integrated model, including an efficiency model and a heat balance model, is proposed, which makes it possible to predict power loss, bulk temperature, and temperature distributions under different conditions. In the efficiency model, each part of power losses from gear meshes is studied to calculate the summation of mechanical power losses in the transmission, including losses of gear meshing, bearing and oil churning. In the heat balance model, the entire gearbox is divided into elements with a uniform temperature connected by thermal resistances which account for conduction, convection, and radiation, based upon the first law of thermodynamics for transient conditions. The effectiveness of bulk temperature prediction using thermal network method is validated by the comparison between simulation results and the experimental data. Consequently, this study on heat transfer characteristics, thermal characteristics, and bulk temperature prediction of the two-speed automatic transmission has significant academic and application values.

Brief Report: The Amsterdam Symptom and Risk-Based Score Predicts for Acute HIV Infection in Men Who Have Sex With Men in San Diego.

Dijkstra et al recently described a risk- and symptom-based score moderately predictive for HIV seroconversion in the preceding 6-12 months in men who have sex with men (MSM) in Amsterdam. Our objective was to determine whether this "Amsterdam Score" could also predict for acute HIV infection (AHI) in MSM. This study is a case-control analysis of a prospectively enrolled cohort of MSM who voluntarily presented for HIV testing in San Diego. The study sample was composed of MSM who screened HIV antibody-negative and then either tested positive with AHI [HIV nucleic acid test (NAT)-positive] or tested HIV NAT-negative. The Amsterdam Score was calculated for each participant in the study sample. Score performance was assessed using receiver operating characteristic curves and their area under the curve (AUC). An optimal cutoff was determined using the Youden index. Seven hundred fifty-seven MSM (110 AHI and 647 HIV NAT-negative) were included in the analysis. AHI and HIV-negative cases were similar in age [median 32 years (interquartile range 26-42) vs 33 (27-45), respectively, P = 0.082]. The Amsterdam Score yielded a receiver operating characteristic curve with an AUC of 0.88 (95% confidence interval: 0.84 to 0.91). An optimal cutoff of ≥1.6 was 78.2% sensitive and 81.0% specific. The risk- and symptom-based Amsterdam Score was highly predictive (AUC of 0.88) of AHI in MSM in San Diego. The Amsterdam Score could be used to target NAT utilization in resource-poor settings among MSM who test HIV antibody-negative, although the potential cost-savings must be balanced with the risk of missing AHI diagnoses.

Novel coupled model for power loss prediction in a record-breaking electric aircraft motor

PurposeThe purpose of this paper is to devise an analytical approach to calculate conductor winding losses, considering multiple contributing aspects simultaneously. These include the geometric configuration of coil windings, frequency of the electric current and the dependency on the coil temperature, derived studying a coupled fluid–solid model considering the cooling system characteristics. The obtained results allow identifying power loss trends according to such system variables as coolant inlet temperature or overall flow rate of the motor.Design/methodology/approachAn easy-to-use coupled analytical approach is applied, which is suitable for rapid estimations of the impact of parameter variation on the resulting conductor winding power losses that facilitates decision-making in the design process of electric aircraft engines.FindingsIn the considered cooling parameters, the overall conductor winding power losses vary approximately between 6 kW and 7.2 kW. More than 95 per cent of this loss is because of direct current losses. These losses cause the variation in maximal coil temperature ranging between 115°C and 170°C.Practical implicationsThe SP260D motor is set and was currently tested in Extra 330. It recently broke two world records.Social implicationsOne of the current trends in aircraft engineering is electric aircraft. Advantages of electric aircraft include improved manoeuvrability because of greater torque from electric motors, increased safety because of decreased chance of mechanical failure, less risk of explosion or fire in the event of a collision and less noise. There will be environmental and cost benefits associated with the elimination of dependency on fossil fuels and resultant emissions.Originality/valueThe use of a novel fluid–solid interaction model for predicting conductor winding power loss of the SP260D electric aircraft motor has not been done earlier. A novel alternative derivation of the widely applied Dowell’s formula (Dowell, 1966) is presented for the estimation of proximity losses in square winding conductors.

Churning power losses of a gearbox with spiral bevel geared transmission

Abstract To predict the churning power losses in a gearbox with spiral bevel geared transmission, based on the Computational Fluid Dynamics (CFD) method, a numerical simulation model for the splash lubrication of the intermediate gearbox of a helicopter including gear box housing, a spiral bevel gear pair and an oil guide device is established and validated by the churning power losses prediction of experiments showing a good agreement. With the model, churning power losses of a gearbox with spiral bevel geared transmission are obtained; influences of gear rotational speed, oil fill level, oil temperature, oil dynamic viscosity, oil density, and tilt angle of the helicopter, on the churning power losses are analyzed.

Prediction‐Oriented Model Selection in Partial Least Squares Path Modeling

ABSTRACTPartial least squares path modeling (PLS‐PM) has become popular in various disciplines to model structural relationships among latent variables measured by manifest variables. To fully benefit from the predictive capabilities of PLS‐PM, researchers must understand the efficacy of predictive metrics used. In this research, we compare the performance of standard PLS‐PM criteria and model selection criteria derived from Information Theory, in terms of selecting the best predictive model among a cohort of competing models. We use Monte Carlo simulation to study this question under various sample sizes, effect sizes, item loadings, and model setups. Specifically, we explore whether, and when, the in‐sample measures such as the model selection criteria can substitute for out‐of‐sample criteria that require a holdout sample. Such a substitution is advantageous when creating a holdout causes considerable loss of statistical and predictive power due to an overall small sample. We find that when the researcher does not have the luxury of a holdout sample, and the goal is selecting correctly specified models with low prediction error, the in‐sample model selection criteria, in particular the Bayesian Information Criterion (BIC) and Geweke–Meese Criterion (GM), are useful substitutes for out‐of‐sample criteria. When a holdout sample is available, the best performing out‐of‐sample criteria include the root mean squared error (RMSE) and mean absolute deviation (MAD). We recommend against using standard the PLS‐PM criteria (R2, AdjustedR2, andQ2), and specifically the out‐of‐sample mean absolute percentage error (MAPE) for prediction‐oriented model selection purposes. Finally, we illustrate the model selection criteria's practical utility using a well‐known corporate reputation model.