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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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Dennis Albert, Lukas Daniel Domenig, Philipp Schachinger, Klaus Roppert and Herwig Renner
The purpose of this paper is to investigate the applicability of a direct current (DC) hysteresis measurement on power transformer terminals for the subsequent hysteresis model…
Abstract
Purpose
The purpose of this paper is to investigate the applicability of a direct current (DC) hysteresis measurement on power transformer terminals for the subsequent hysteresis model parametrization in transformer grey box topology models.
Design/methodology/approach
Two transformer topology models with two different hysteresis models are used together with a DC hysteresis measurement via the power transformer terminals to parameterize the hysteresis models by means of an optimization. The calculated current waveform with the derived model in the transformer no-load condition is compared to the measured no-load current waveforms to validate the model.
Findings
The proposed DC hysteresis measurement via the power transformer terminals is suitable to parametrize two hysteresis models implemented in transformer topology models to calculate the no-load current waveforms.
Originality/value
Different approaches for the measurement and utilization of transformer terminal measurements for the hysteresis model parametrization are discussed in literature. The transformer topology models, derived with the presented approach, are able to reproduce the transformer no-load current waveform with acceptable accuracy.
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V. Chowdary Boppana and Fahraz Ali
This paper presents an experimental investigation in establishing the relationship between FDM process parameters and tensile strength of polycarbonate (PC) samples using the…
Abstract
Purpose
This paper presents an experimental investigation in establishing the relationship between FDM process parameters and tensile strength of polycarbonate (PC) samples using the I-Optimal design.
Design/methodology/approach
I-optimal design methodology is used to plan the experiments by means of Minitab-17.1 software. Samples are manufactured using Stratsys FDM 400mc and tested as per ISO standards. Additionally, an artificial neural network model was developed and compared to the regression model in order to select an appropriate model for optimisation. Finally, the genetic algorithm (GA) solver is executed for improvement of tensile strength of FDM built PC components.
Findings
This study demonstrates that the selected process parameters (raster angle, raster to raster air gap, build orientation about Y axis and the number of contours) had significant effect on tensile strength with raster angle being the most influential factor. Increasing the build orientation about Y axis produced specimens with compact structures that resulted in improved fracture resistance.
Research limitations/implications
The fitted regression model has a p-value less than 0.05 which suggests that the model terms significantly represent the tensile strength of PC samples. Further, from the normal probability plot it was found that the residuals follow a straight line, thus the developed model provides adequate predictions. Furthermore, from the validation runs, a close agreement between the predicted and actual values was seen along the reference line which further supports satisfactory model predictions.
Practical implications
This study successfully investigated the effects of the selected process parameters - raster angle, raster to raster air gap, build orientation about Y axis and the number of contours - on tensile strength of PC samples utilising the I-optimal design and ANOVA. In addition, for prediction of the part strength, regression and ANN models were developed. The selected ANN model was optimised using the GA-solver for determination of optimal parameter settings.
Originality/value
The proposed ANN-GA approach is more appropriate to establish the non-linear relationship between the selected process parameters and tensile strength. Further, the proposed ANN-GA methodology can assist in manufacture of various industrial products with Nylon, polyethylene terephthalate glycol (PETG) and PET as new 3DP materials.
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Shichao Jiang, Xinliang Lu, Hongliang Wang, Kai Song and Yuanyuan Jiang
Detection of hidden defects of aluminum alloy plate with damping coating is a challenging problem. At present, only a few non-destructive testing methods exist to address this…
Abstract
Purpose
Detection of hidden defects of aluminum alloy plate with damping coating is a challenging problem. At present, only a few non-destructive testing methods exist to address this engineering problem. Without the restriction of skin effect, remote field eddy current (RFEC) overcomes the interference caused by the damping coating. The RFEC, which has potential advantages for detecting the hidden defects of aluminum plate with damping coating, can penetrate the metal plate to detect buried depth defects. This study aims to test how thick the RFEC sensor can penetrate the metal plate to detect the buried defects.
Design/methodology/approach
The magnetic field distribution characteristics are analyzed, the magnetic field intensity distribution is calculated, and the structure and parameters of the coil, magnetic circuit and shielding damping are determined through the two- and three-dimensional finite element simulation methods. Optimal excitation frequency is obtained, and the distance between the excitation coil and detection coil is determined by analyzing the relationship between excitation frequency and remote field points.
Findings
Simulation and experimental results verify the feasibility of applying the RFEC detection technology in detecting the hidden defects of aluminum alloy plate with damping coating.
Originality/value
In this paper, the RFEC testing model of hidden defects in aluminum plate sample with damping coating is established by using the finite element method.
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Serena Summa, Alex Mircoli, Domenico Potena, Giulia Ulpiani, Claudia Diamantini and Costanzo Di Perna
Nearly 75% of EU buildings are not energy-efficient enough to meet the international climate goals, which triggers the need to develop sustainable construction techniques with…
Abstract
Purpose
Nearly 75% of EU buildings are not energy-efficient enough to meet the international climate goals, which triggers the need to develop sustainable construction techniques with high degree of resilience against climate change. In this context, a promising construction technique is represented by ventilated façades (VFs). This paper aims to propose three different VFs and the authors define a novel machine learning-based approach to evaluate and predict their energy performance under different boundary conditions, without the need for expensive on-site experimentations
Design/methodology/approach
The approach is based on the use of machine learning algorithms for the evaluation of different VF configurations and allows for the prediction of the temperatures in the cavities and of the heat fluxes. The authors trained different regression algorithms and obtained low prediction errors, in particular for temperatures. The authors used such models to simulate the thermo-physical behavior of the VFs and determined the most energy-efficient design variant.
Findings
The authors found that regression trees allow for an accurate simulation of the thermal behavior of VFs. The authors also studied feature weights to determine the most relevant thermo-physical parameters. Finally, the authors determined the best design variant and the optimal air velocity in the cavity.
Originality/value
This study is unique in four main aspects: the thermo-dynamic analysis is performed under different thermal masses, positions of the cavity and geometries; the VFs are mated with a controlled ventilation system, used to parameterize the thermodynamic behavior under stepwise variations of the air inflow; temperatures and heat fluxes are predicted through machine learning models; the best configuration is determined through simulations, with no onerous in situ experimentations needed.
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The simulation of eddy currents in laminated iron cores by the finite element method (FEM) is of great interest in the design of electrical devices. Modeling each laminate by…
Abstract
Purpose
The simulation of eddy currents in laminated iron cores by the finite element method (FEM) is of great interest in the design of electrical devices. Modeling each laminate by finite elements leads to extremely large nonlinear systems of equations impossible to solve with present computer resources reasonably. The purpose of this study is to show that the multiscale finite element method (MSFEM) overcomes this difficulty.
Design/methodology/approach
A new MSFEM approach for eddy currents of laminated nonlinear iron cores in three dimensions based on the magnetic vector potential is presented. How to construct the MSFEM approach in principal is shown. The MSFEM with the Biot–Savart field in the frequency domain, a higher-order approach, the time stepping method and with the harmonic balance method are introduced and studied.
Findings
Various simulations demonstrate the feasibility, efficiency and versatility of the new MSFEM.
Originality/value
The novel MSFEM solves true three-dimensional eddy current problems in laminated iron cores taking into account of the edge effect.
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Carolina Bermudo Gamboa, Sergio Martín Béjar, Francisco Javier Trujillo Vilches and Lorenzo Sevilla Hurtado
The purpose of this study is to cover the influence of selected printing parameters at a macro and micro-geometrical level, focusing on the dimensions, geometry and surface of…
Abstract
Purpose
The purpose of this study is to cover the influence of selected printing parameters at a macro and micro-geometrical level, focusing on the dimensions, geometry and surface of printed parts with short carbon fibers reinforced PLA. For this case study, a hollow cylindrical shape is considered, aiming to cover the gap detected in previous works analyzed.
Design/methodology/approach
Nowadays, additive manufacturing plays a very important role in the manufacturing industry, as can be seen through its numerous research and applications that can be found. Within the engineering industry, geometrical tolerances are essential for the functionality of the parts and their assembly, but the variability in three-dimensional (3D) printing makes dimensional control a difficult task. Constant development in 3D printing allows, more and more, printed parts with controlled and narrowed geometrical deviations and tolerances. So, it is essential to continue narrowing the studies to achieve the optimal printed parts, optimizing the manufacturing process as well.
Findings
Results present the relation between the selected printing parameters and the resulting printed part, showing the main deviations and the eligible values to achieve a better tolerance control. Also, from these results obtained, we present a parametric model that relates the geometrical deviations considered in this study with the printing parameters. It can provide an overview of the piece before printing it and so, adjusting the printing parameters and reducing time and number of printings to achieve a good part.
Originality/value
The main contribution is the study of the geometry selected under a 3D printing process, which is important because it considers parts that are created to fit together and need to comply with the required tolerances. Also, we consider that the parametric model can be a suitable approach to selecting the optimal printing parameters before printing.
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