Gabriel Khoury, Ragi Ghosn, Flavia Khatounian, Maurice Fadel and Mathias Tientcheu
In the need to optimize the energy efficiency, control structures can have a positive effect by tracking the optimal operating point according to the speed and mechanical load of…
Abstract
Purpose
In the need to optimize the energy efficiency, control structures can have a positive effect by tracking the optimal operating point according to the speed and mechanical load of the motor. The purpose of this paper is to present an energy-efficient scalar control for squirrel-cage induction motors (IMs), taking into consideration the effect of core losses.
Design/methodology/approach
The proposed technique is based on the modification of the stator flux reference, to track the best efficiency point. The optimal flux values are computed through an improved model of the IM including core losses, then stored in a look-up table.
Findings
Simulations of the proposed scalar control are carried out, and results show the efficiency improvement when the flux is optimized especially at low load cases. Results were validated experimentally on two motors compliant with different efficiency standards.
Practical implications
The proposed approach can be used in several fields and applications using the scalar-controlled IM with a proper implementation in variable speed drives, as in the cases of pumps, compressors and blowers.
Originality/value
The proposed technique is compared to existing optimization methods in literature, and the results show an improvement in the dynamic performance and in the response delays. The approach is also compared to an optimization technique used in industries like Leroy-Somer for variable speed drives, and efficiency improvements are shown.
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A. Benabou, L. Vandenbossche, J. Gyselinck, S. Clenet, L. Dupré and P. Dular
Mechanical stress can heavily affect the magnetic behaviour law in ferromagnetic materials. This paper, aims to take into account the effect of mechanical stress into a…
Abstract
Purpose
Mechanical stress can heavily affect the magnetic behaviour law in ferromagnetic materials. This paper, aims to take into account the effect of mechanical stress into a hystreresis model. This model is implemented in a finite element analysis code and tested in the case of a simple system.
Design/methodology/approach
A simple extension of the classical Preisach model is proposed, in which a function linked to the Preisach density is parameterized using the mechanical stress as a supplementary parameter. The methodology is based on experimental measurements for identifying the required function. As a first approach, a linear interpolation is used between the measurements in order to have a continuous evolution of the magneto‐mechanical behaviour. This model has been tested in the case of a steel sheet in which width is not constant in order to obtain a non‐uniform distribution of stress and magnetic flux density.
Findings
The model can predict the magneto‐mechanical behaviour with a good accuracy in the case of tensile stress. Implementation of the model in finite element analysis has shown that the model can predict the behaviour of steel sheet subject to a non‐uniform stress distribution.
Originality/value
This paper shows that a classical hysteresis model can be extended to take into account the magneto‐mechanical behaviour. This is useful for the design of electrical machines which are subject to non‐negligible mechanical stress.
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Valentin Ionita, Lucian Petrescu and Emil Cazacu
The electrical machines connected to modern electric power grids are non-sinusoidal excited, and their augmented losses, including iron losses, limit their working…
Abstract
Purpose
The electrical machines connected to modern electric power grids are non-sinusoidal excited, and their augmented losses, including iron losses, limit their working characteristics. This paper aims to propose a prediction method for iron losses in non-oriented grains (NO) FeSi sheets under non-sinusoidal voltage, involving an inverse classical Preisach hysteresis model and the time-integration of each loss component.
Design/methodology/approach
The magnetic history management in inverse Preisach model is optimized and a numerical Everett function is identified from measured symmetrical hysteresis cycles. The experimental data for sinusoidal waveforms obtained by a single sheet tester were also used to identify the parameters involved in Bertotti’ losses separation method. The non-sinusoidal magnetic induction waveform, corresponding to a measured voltage in an industrial electrical grid, was the input for Preisach model, the output magnetic field being accurately computed. The hysteresis, classical and excess losses are calculated by time-integration and the total losses are compared with those obtained for sinusoidal excitation.
Findings
The proposed method allows to estimate the iron losses for non-sinusoidal magnetic induction, using carefully identified parameters of FeSi NO sheets, using experimental data from sinusoidal regimes.
Originality/value
The method accuracy is assured by using a numerical Everett function, a variable Preisach grid step (adapted for the high non-linearity of FeSi sheets) and high-order fitting polynomials for the microscopic parameters involved in the excess loss estimation. The procedure allows a better design of magnetic cores and an improved estimation of the electric machine derating for non-sinusoidal voltages.
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Peter Sergeant, Guillaume Crevecoeur, Luc Dupré and Alex Van den Bossche
The first purpose of this paper is to identify – by an inverse problem – the unknown material characteristics in a permanent magnet synchronous machine in order to obtain a…
Abstract
Purpose
The first purpose of this paper is to identify – by an inverse problem – the unknown material characteristics in a permanent magnet synchronous machine in order to obtain a numerical model that is a realistic representation of the machine. The second purpose is to optimize the machine geometrically – using the accurate numerical model – for a maximal torque to losses ratio. Using the optimized geometry, a new machine can be manufactured that is more efficient than the original.
Design/methodology/approach
A 2D finite element model of the machine is built, using a nonlinear material characteristic that contains three parameters. The parameters are identified by an inverse problem, starting from torque measurements. The validation is based on local BH‐measurements on the stator iron.
Findings
Geometrical parameters of the motor are optimized at small load (low‐stator currents) and at full load (high‐stator currents). If the optimization is carried out for a small load, the stator teeth are chosen wider in order to reduce iron loss. An optimization at full load results in a larger copper section so that the copper loss is reduced.
Research limitations/implications
The identification of the material parameters is influenced by the tolerance on the air gap – shown by a sensitivity analysis in the paper – and by 3D effects, which are not taken into account in the 2D model.
Practical implications
The identification of the material parameters guarantees that the numerical model describes the real material properties in the machine, which may be different from the properties given by the manufacturer because of mechanical stress and material degradation.
Originality/value
The optimization is more accurate because the material properties, used in the numerical model, are determined by the solution of an inverse problem that uses measurements on the machine.
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Romus Noufelie, Cosmas Bernard Meka'a and Astride Claudel Njiepue Nouffeussie
The aim of this study is to investigate the determinants of Inequalities of Opportunity (IOP) among the young in Cameroonian labour market. IOP are the differences in outcomes…
Abstract
The aim of this study is to investigate the determinants of Inequalities of Opportunity (IOP) among the young in Cameroonian labour market. IOP are the differences in outcomes which are explained by the circumstance factors, meaning that the variables which are beyond individual controls. For this purpose, this study performs the Human Opportunity Index (HOI) in order to quantify the IOP among employee over 10- to 25-year-olds. Using the data from the Fourth Cameroon Household Survey (FCHS4) carried out in 2014 by Statistical National Institute, IOP is quantified for each of 14 Cameroonian’s geographical areas. Based on the Dissimilarity index (D-Index) value, two main trends are outlined: a spatial subgroup including North-West, East and the urban regions which is characterized by a higher D-Index; meaning that IOP is relatively significant. In contrast, a more homogeneous subgroup with a lower IOP is found in rural, North and East regions. Moreover, regarding on the one hand the Shapley-Shorrock’s decomposition method, it appears that the mayor circumstances contributing to the D-index are socio-professional category, primary education and religious obedience of the household head which explain from 51% to 79% the overall IOP. While on the other hand, the Blinder-Oaxaca decomposition shows that 80% of the gap in D-Index is explained by disparities in circumstances, rather than individual efforts. Finally, our conclusions argue in favour of effective decentralization, for a more inclusive employment policy that takes into account local labour market features.
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Mitja Garmut and Martin Petrun
This paper presents a comparative study of different stator-segmentation topologies of a permanent magnet synchronous machine (PMSM) used in traction drives and their effect on…
Abstract
Purpose
This paper presents a comparative study of different stator-segmentation topologies of a permanent magnet synchronous machine (PMSM) used in traction drives and their effect on iron losses. Using stator segmentation allows one to achieve more significant copper fill factors, resulting in increased power densities and efficiencies. The segmentation of the stators creates additional air gaps and changes the soft magnetic material’s material properties due to the cut edge effect. The aim of this paper is to present an in-depth analysis of the influence of stator segmentation on iron losses. The main goal was to compare various segmentation methods under equal excitation conditions in terms of their influence on iron loss.
Design/methodology/approach
A transient finite element method analysis combined with an extended iron-loss model was used to evaluate discussed effects on the stator’s iron losses. The workflow to obtain a homogenized airgap length accounting for cut edge effects was established.
Findings
The paper concludes that the segmentation in most cases slightly decreases the iron losses in the stator because of the overall reduced magnetic flux density B due to the additional air gaps in the magnetic circuit. An increase of the individual components, as well as total power loss, was observed in the Pole Chain segmentation design. In general, segmentation did not change the total iron losses significantly. However, different segmentation methods resulted in the different distortion of the magnetic field and, consequently, in different iron loss compositions. The analysed segmentation methods exhibited different iron loss behaviour with respect to the operation points of the machine. The final finding is that analysed stator segmentations had a negligible influence on the total iron loss. Therefore, applying segmentation is an adequate measure to improve PMSMs as it enables, e.g. increase of the winding fill factor or simplifying the assembly processes, etc.
Originality/value
The influence of stator segmentation on iron losses was analysed. An in-depth evaluation was performed to determine how the discussed changes influence the individual iron loss components. A workflow was developed to achieve a computationally cheap homogenized model.
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Martin Marco Nell, Benedikt Schauerte, Tim Brimmers and Kay Hameyer
Various iron loss models can be used for the simulation of electrical machines. In particular, the effect of rotating magnetic flux density at certain geometric locations in a…
Abstract
Purpose
Various iron loss models can be used for the simulation of electrical machines. In particular, the effect of rotating magnetic flux density at certain geometric locations in a machine is often neglected by conventional iron loss models. The purpose of this paper is to compare the adapted IEM loss model for rotational magnetization that is developed within the context of this work with other existing models in the framework of a finite element simulation of an exemplary induction machine.
Design/methodology/approach
In this paper, an adapted IEM loss model for rotational magnetization, developed within the context of the paper, is implemented in a finite element method simulation and used to calculate the iron losses of an exemplary induction machine. The resulting iron losses are compared with the iron losses simulated using three other already existing iron loss models that do not consider the effects of rotational flux densities. The used iron loss models are the modified Bertotti model, the IEM-5 parameter model and a dynamic core loss model. For the analysis, different operating points and different locations within the machine are examined, leading to the analysis of different shapes and amplitudes of the flux density curves.
Findings
The modified Bertotti model, the IEM-5 parameter model and the dynamic core loss model underestimate the hysteresis and excess losses in locations of rotational magnetizations and low-flux densities, while they overestimate the losses for rotational magnetization and high-flux densities. The error is reduced by the adapted IEM loss model for rotational magnetization. Furthermore, it is shown that the dynamic core loss model results in significant higher hysteresis losses for magnetizations with a high amount of harmonics.
Originality/value
The simulation results show that the adapted IEM loss model for rotational magnetization provides very similar results to existing iron loss models in the case of unidirectional magnetization. Furthermore, it is able to reproduce the effects of rotational flux densities on iron losses within a machine simulation.
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Jan Karthaus, Simon Steentjes, Nora Leuning and Kay Hameyer
The purpose of this paper is to study the variation of the specific iron loss components of electrical steel sheets when applying a tensile mechanical load below the yield…
Abstract
Purpose
The purpose of this paper is to study the variation of the specific iron loss components of electrical steel sheets when applying a tensile mechanical load below the yield strength of the material. The results provide an insight into the iron loss behaviour of the laminated core of electrical machines which are exposed to mechanical stresses of diverse origins.
Design/methodology/approach
The specific iron losses of electrical steel sheets are measured using a standardised single-sheet tester equipped with a hydraulic pressure cylinder which enables application of a force to the specimen under test. Based on the measured data and a semi-physical description of specific iron losses, the stress-dependency of the iron loss components can be studied.
Findings
The results show a dependency of iron loss components on the applied mechanical stress. Especially for the non-linear loss component and high frequencies, a large variation is observed, while the excess loss component is not as sensitive to high mechanical stresses. Besides, it is shown that the stress-dependent iron loss prediction approximates the measured specific iron losses in an adequate way.
Originality/value
New applications such as high-speed traction drives in electric vehicles require a suitable design of the electrical machine. These applications require particular attention to the interaction between mechanical influences and magnetic behaviour of the machine. In this regard, knowledge about the relation between mechanical stress and magnetic properties of soft magnetic material is essential for an exact estimation of the machine’s behaviour.
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Zhiyong Zeng, Xiaoliang Jin and Rongxiang Zhao
The model for digitally controlled three-phase pulse width modulation (PWM) boost rectifiers is a sampled data model, which is different from the continuous time domain models…
Abstract
Purpose
The model for digitally controlled three-phase pulse width modulation (PWM) boost rectifiers is a sampled data model, which is different from the continuous time domain models presented in previous studies. The controller, which is tuned according to the model in continuous time domain and discretized by approximation methods, may exhibit some unpredictable performances and even result in unstable systems under some extreme situations. Consequently, a small-signal discrete-time model of digitally controlled three-phase PWM boost rectifier is required. The purpose of this paper is to provide a simple but accurate small-signal discrete-time model of digital controlled three-phase PWM boost rectifier, which explains the effect of the sampling period, modulator and time delays on system dynamic and improves the control performance.
Design/methodology/approach
Based on the Laplace domain analysis and the waveforms of up-down-count modulator, the small signal model of digital pulse width modulation (DPWM) in the Laplace domain is presented. With a combination of state-space average and a discrete-time modeling technique, a simplified large signal discrete time model is developed. With rotation transformation and feed-forward decoupling, the large-signal model is decoupled into a single input single output system with rotation transformation. Then, an integrated small signal model in the Laplace domain is constructed that included the time delay and modulation effect. Implementing the modified z-transform, a small-signal discrete-time model is derived from the integrated small signal model.
Findings
In a digital control system, besides the circuit parameters, the location of pole of open-loop transfer function is also related to system sampling time, affecting the system stability, and the time delay determines the location of the zero of open-loop transfer function, affecting the system dynamic. In addition to the circuit parameters discussed in previous literature, the right half plane (RHP) zero is also determined by the sampling period and the time delay. Furthermore, the corner frequency of the RHP zero is mainly determined by the sampling period.
Originality/value
The model developed in this paper, accounting for the effect of the sampling period, modulator and time delays on the system dynamic, give a sufficient insight into the behavior of the digitally controlled three-phase PWM rectifier. It can also explain the effect of sampling period and control delay time on system dynamic, accurately predict the system stability boundary and determine the oscillation frequency of the current loop in critical stable. The experimental results verify that the model is a simple and accurate control-oriented small-signal discrete-time model for the digitally controlled three-phase PWM boost rectifier.
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Charles A. Donnelly, Sushobhan Sen, John W. DeSantis and Julie M. Vandenbossche
The time-varying equivalent linear temperature gradient (ELTG) significantly affects the development of faulting and must therefore be accounted for in pavement design. The same…
Abstract
Purpose
The time-varying equivalent linear temperature gradient (ELTG) significantly affects the development of faulting and must therefore be accounted for in pavement design. The same is true for faulting of bonded concrete overlays of asphalt (BCOA) with slabs larger than 3 x 3 m. However, the evaluation of ELTG in Mechanistic-Empirical (ME) BCOA design is highly time-consuming. The use of an effective ELTG (EELTG) is an efficient alternative to calculating ELTG. In this study, a model to quickly evaluate EELTG was developed for faulting in BCOA for panels 3 m or longer in size, whose faulting is sensitive to ELTG.
Design/methodology/approach
A database of EELTG responses was generated for 144 BCOAs at 169 locations throughout the continental United States, which was used to develop a series of prediction models. Three methods were evaluated: multiple linear regression (MLR), artificial neural networks (ANNs), and multi-gene genetic programming (MGGP). The performance of each method was compared, considering both accuracy and model complexity.
Findings
It was shown that ANNs display the highest accuracy, with an R2 of 0.90 on the validation dataset. MLR and MGGP models achieved R2 of 0.73 and 0.71, respectively. However, these models consisted of far fewer free parameters as compared to the ANNs. The model comparison performed in this study highlights the need for researchers to consider the complexity of models so that their direct implementation is feasible.
Originality/value
This research produced a rapid EELTG prediction model for BCOAs that can be incorporated into the existing faulting model framework.