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Reducing eddy current losses in magnets of electrical machines can be obtained by means of several techniques. The magnet segmentation is the most popular one. It imposes the least restrictions on machine performances. This paper investigates the effectiveness of the magnet circumferential segmentation technique to reduce these undesirable losses. The full and partial magnet segmentation are both studied for a frequency range from few Hz to a dozen of kHz. To increase the efficiency of these techniques to reduce losses for any working frequency, an optimization strategy based on coupling of finite elements analysis and genetic algorithm is applied. The purpose of this paper is to define the parameters of the total and partial segmentation that can ensure the best reduction of eddy current losses.

First, a model to analyze eddy current losses is presented. Second, the effectiveness of full and partial magnet circumferential segmentation to reduce eddy loss is studied for a range of frequencies from few Hz to a dozen of kHz. To achieve these purposes a 2-D finite element model is developed under MATLAB environment. In a third step of the work, an optimization process is applied to adjust the segmentation design parameters for best reduction of eddy current losses in case of surface mounted permanent magnets synchronous machine.

In case of the skin effect operating, both full and partial magnet segmentations can lead to eddy current losses increases. Such deviations of magnet segmentation techniques can be avoided by an appropriate choice of their design parameters.

Few works are dedicated to investigate partial magnet segmentation for eddy current losses reduction. This paper studied the effectiveness and behaviour of partial segmentation for different frequency ranges. To avoid eventual anomalies related to the skin effect an optimization process based on the association of the finite elements analysis to genetic algorithm method is adopted.

This paper aims to introduce a computationally efficient hybrid analytical–finite element (FE) methodology for loss evaluation in electric vehicle (EV) permanent magnet (PM) traction motor applications. In this class of problems, eddy current losses in PMs and iron laminations constitute an important part of overall drive losses, representing a key design target.

Both surface mounted permanent magnet (SMPM) and double-layer interior permanent magnet (IPM) motor topologies are considered. The PM eddy losses are calculated by using analytical solutions and Fourier harmonic decomposition. The boundary conditions are based on slot opening magnetic field strength tangential component in the air gap in the SMPM topology case, whereas the numerically evaluated normal flux density variation on the surface of the outer PM is implemented in the IPM case. Combined analytical–loss evaluation technique has been verified by comparing its results to a transient magnetodynamic two-dimensional FE model ones.

The proposed loss evaluation technique calculated the total power losses for various operating conditions with low computational cost, illustrating the relative advantages and drawbacks of each motor topology along a typical EV operating cycle. The accuracy of the method was comparable to transient FE loss evaluation models, particularly around nominal speed.

The originality of this paper is based on the development of a fast and accurate PM eddy loss model for both SMPM and IPM motor topologies for traction applications, combining effectively both analytical and FE techniques.

The purpose of this paper is to propose a new outer‐rotor permanent‐magnet flux‐switching machine (ORPMFSM) for electric vehicle (EV) in‐wheel propulsion. The paper documents both the design procedure and performance investigation of this novel machine.

The topology and preliminary sizing equations of the ORPMFSM are introduced. The rotor poles are optimized, whilst the machine losses are particularly investigated, using 2‐D finite element analysis (FEA).

An ORPMFSM, with 12 stator poles and 22 rotor poles, is most suitable for the proposed EV application. The analytical sizing equations are quite efficient with a sufficient accuracy for the preliminary design. The optimal rotor pole width from the FEA results is nearly 1.3 times the original value which was proposed in early literatures. The efficiency of the proposed machine under rated load is slightly low, as a result of significant eddy current losses in the permanent magnets. The losses can be effectively suppressed with the technique of magnet segmenting. The predicted outstanding performance implies that by adopting magnet segmentation the proposed machine is a leading contender for EV direct drives.

The outer‐rotor structure of PMFSM was not addressed in early literatures. This paper provides designers with the technical background and an alternative candidate for the EV propulsion.

The introduction of stochastic deviations due to production faults into the finite element (FE) simulation of electrical machines requires suitable error-model. These models should describe the occurring deviations from the ideal case. Permanent magnets, which can be used as rotor excitations in synchronous machines (PMSM), are one out of many possible sources for the aforementioned stochastic production variations. Fitting measured magnet variations to simulation models with the aim of describing the occurring production deviations, however, poses a problem due to two reasons: to begin with, only data of measured flux-densities are available. Second, a solution of the inverse problem is required to obtain data about changes inside the magnet. This paper, therefore, presents two solutions to this problem.

Two error-models, one based on knowledge about the magnetisation process, the other one built upon principal component analysis, are presented. Both models are evaluated by parametrising them, using a set of measured flux-density data from magnets. Afterwards, each model's applicability and reproduction quality is assessed.

Both models still have some drawbacks. While the first model seems to be too coarse grained for certain variations, the second model lacks applicability for a high reproduction quality.

The comparison of both methods reveals guidelines, which methodology should be applied for predicting which variations. Furthermore, solutions are shown, how to mitigate the problems of the two presented models.

Fractional slot permanent magnet (PM) brushless machines having concentrated non‐overlapping windings have been the subject of research over last few years. They have already been employed in the commercial hybrid electric vehicles (HEVs) due to high‐torque density, high efficiency, low‐torque ripple, good flux‐weakening and fault‐tolerance performance. The purpose of this paper is to overview recent development and research challenges in such machines in terms of various structural and design features for electric vehicle (EV)/HEV applications.

In the paper, fractional slot PM brushless machines are overviewed according to the following main and sub‐topics: first, machine topologies: slot and pole number combinations, all and alternate teeth wound (double‐ and single‐layer windings), unequal tooth structure, modular stator, interior magnet rotor; second, machine parameters and control performance: winding inductances, flux‐weakening capability, fault‐tolerant performance; and third, parasitic effects: cogging torque, iron loss, rotor eddy current loss, unbalanced magnetic force, acoustic noise and vibration.

Many fractional slot PM machine topologies exist. Owing to rich mmf harmonics, fractional slot PM brushless machines exhibit relatively high rotor eddy current loss, potentially high unbalanced magnetic force and acoustic noise and vibration, while the reluctance torque component is relatively low or even negligible when an interior PM rotor is employed.

This is the first overview paper which systematically reviews the recent development and research challenges in fractional‐slot PM machines. It summarizes their various structural and design features for EV/HEV applications.

The purpose of this paper is to study the performance and efficiency of two different permanent magnet (PM) machine rotor configurations under magnetic core saturation conditions.

Since the accuracy of conventional analytical methods is limited under saturation conditions, a finite element model of the machine is built; which is used to predict the various losses over its operating range such as eddy current, hysteresis, copper and magnet losses. Using this model, the efficiency map of the machine is derived which is used to investigate its efficiency corresponding to a heavy vehicle drive cycle. The performance of two different rotor designs are studied and the efficiency of each design is compared under the considered drive cycle.

It has also been proved that the performance advantage due to reluctance torque in the v-shaped interior PM (IPM) machine is offset by its core steel saturation at higher current/torque levels. The magnitude of iron losses in the IPM is higher than that in the surface PM (SPM) machine, however, the magnet loss in the SPM is higher than in the IPM.

An investigation of the performance of the IPM design in comparison with the SPM∼design under magnetic saturation conditions is not known to the authors. Hence, in this paper, it will be determined if the assumed performance advantage of the IPM over the SPM still holds true under these conditions.

This paper aims to show a complete optimization tool that can be used for the design of coaxial magnetic gears. In the first part, the paper deals with the semi-analytic modelling of these machines and also discusses how to reduce the computational efforts. In the second part, an optimization algorithm is adopted for finding the Pareto optimal geometries.

The machine is subdivided into a set of domains according to their physical and geometrical properties, and the potential distribution is found semi-analytically in them under some simplifying hypothesis. A loss estimation is performed for both ferromagnetic and permanent magnet regions. A stochastic differential evolution (DE) algorithm for multi-objective constrained problems is then applied.

It is shown that the presented design tool gives results in accordance to finite element method (FEM)-based analysis keeping the advantages of robustness and simplicity of the analytical methods. The DE-based strategy performs well on the magnetic gear optimization problem.

The proposed tool appears to be a good starting point when designing coaxial magnetic gears. The optimal Pareto points can be used as initial seeds of FEM-based optimizations, resulting in a cheaper computational method with respect to a full FEM optimization.

This paper takes inspiration from recent works on magnetic gear modelling and completes the design procedure with a suitable efficiency estimation. The paper also shows how to use mature optimization strategies to solve the constrained multi-objective magnetic gear design problem.

Based upon a study of between fifty to sixty case examples of new venture start‐ups, the author presents a screening procedure for entrepreneurs to use when evaluating whether a proposed low‐budget marketing strategy for a new venture shows promise of being successful. The procedure consists of four sets of screening conditions. A well‐designed marketing strategy should have a reasonably good chance of being successful if it (1) will tightly integrate the product/service and price offerings, the intended distribution method, and the intended promotion plan with the new venture’s designated target market, (2) will encounter no serious marketing strategy execution difficulties which cannot be resolved, (3) uses marketing concepts which can be executed with a small marketing budget, and (4) displays three characteristics believed to be strongly associated with marketing strategies that are successful over the long term.

Brain tumor is one of the most dangerous and life-threatening disease. In order to decide the type of tumor, devising a treatment plan and estimating the overall survival time of the patient, accurate segmentation of tumor region from images is extremely important. The process of manual segmentation is very time-consuming and prone to errors; therefore, this paper aims to provide a deep learning based method, that automatically segment the tumor region from MR images.

In this paper, the authors propose a deep neural network for automatic brain tumor (Glioma) segmentation. Intensity normalization and data augmentation have been incorporated as pre-processing steps for the images. The proposed model is trained on multichannel magnetic resonance imaging (MRI) images. The model outputs high-resolution segmentations of brain tumor regions in the input images.

The proposed model is evaluated on benchmark BRATS 2013 dataset. To evaluate the performance, the authors have used Dice score, sensitivity and positive predictive value (PPV). The superior performance of the proposed model is validated by training very popular UNet model in the similar conditions. The results indicate that proposed model has obtained promising results and is effective for segmentation of Glioma regions in MRI at a clinical level.

The model can be used by doctors to identify the exact location of the tumorous region.

The proposed model is an improvement to the UNet model. The model has fewer layers and a smaller number of parameters in comparison to the UNet model. This helps the network to train over databases with fewer images and gives superior results. Moreover, the information of bottleneck feature learned by the network has been fused with skip connection path to enrich the feature map.

The purpose of this paper is to present a new optimal design for integral slot permanent magnet synchronous motors (PMSMs) to shape the air-gap magnetic field in sinusoidal and to reduce the cogging torque, simultaneously.

For obtaining this new optimal design, the influence of different magnetizations of permanent magnets (PMs), including radial, parallel and halbach magnetization is investigated on the performance of one typical PMSM by using the conformal mapping (CM) method. To reduce the cogging torque even more, the technique of slot opening shift is also implemented on the stator slots of analyzed PMSM without reduction in the main performance, including the air-gap magnetic field, the average torque and back-electromotive force (back-EMF).

Finally, an optimal configuration including the Hat-type magnet poles with halbach magnetization on the rotor and shifted slot openings on the stator is obtained through the CM method, which shows the main reduction in cogging torque and the harmonic content of air-gap magnetic field.

The obtained optimal design is completely practical and is validated by comparing with the corresponding results obtained through finite element method.

This paper presents a new optimal design for integral slot PMSMs, which can include different design considerations, such as the reduction of cogging torque and the total harmonic distortion of air-gap magnetic field by using the CM method.