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The principle of microwave characterization of dielectric materials using open-ended coaxial line probe is to link the dielectric properties of the sample under test to the measurements of the probe admittance (Y(f) = G(f)+ jB(f )). The purpose of this paper is to develop an alternative inversion tool able to predict the evolution of the complex permittivity (ε = ε′ – jε″) on a broad band frequency (f from 1 MHz to 1.8 GHz).

The inverse problem is solved using adaptive network based fuzzy inference system (ANFIS) which needs the creation of a database for its learning. Unfortunately, train ANFIS using f, G and B as inputs has given unsatisfying results. Therefore, an inputs selection procedure is used to select the three optimal inputs from new inputs, created mathematically from original ones, using the Jang method.

Inversion results of measurements give, after training, in real time the complex permittivity of solid and liquid samples with a very good accuracy which prove the applicability of ANFIS to solve inverse problems in microwave characterization.

The originality of this paper consists on the use of ANFIS with input selection procedure based on the Jang method to solve the inverse problem where the three optimal inputs are selected from 26 new inputs created mathematically from original ones (f, G and B).

This paper aims to deal with the electromagnetic simulation of a microwave discharge excited by a surface wave in a large diameter (12 cm) cylindrical plasma reactor. It seeks to focus both on the optimization of the power coupling in the discharge and on the discharge homogeneity.

The CST microwave studio 3D commercial code was used, which solves Maxwell equations using the finite integration technique. The power coupling is investigated by studying the influence of a short‐circuit position, whereas the discharge homogeneity is investigated by studying the influence of the discharge diameter.

A short‐circuit position was found for which the power coupling is perfectly optimised (reflected power around 1 per cent), and it is shown that the 12 cm diameter cylindrical reactor is multi‐mode at 2.45 GHz, with a dominant m=3 hexapolar mode.

The electromagnetic modelling of this reactor is a first step; now the plasma has to be taken into account. Research is in progress to develop a 2D fluid model of the plasma.

The electromagnetic simulation of a plasma reactor turns out to be very useful for the optimization in terms of energy coupling and spatial homogeneity prediction.

The results and a similar approach can be used for the conception of new plasma reactors.

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.

The paper aims to estimate the thermal impact of temperature dependency of material characteristics on induction machines, for which a coupled electromagnetic thermal analysis is carried out.

Both electromagnetic and thermal fields are calculated using a weak coupled finite element analysis algorithm. The electromagnetic behavior of the induction motor is obtained by coupling the field equations to the voltage equations of the windings. The nonlinearity due to the saturation of the iron core and the temperature dependency of the electrical conductivity are taken into account. When the heat sources are evaluated the temperature distribution in the induction motor is obtained. In order to improve the accuracy of the formulation, thermal contact resistances, external and internal convection are considered.

The results presented in this paper prove that the temperature dependency of electric material characteristics must be considered, to accurately simulate the behavior of the induction motors during the design stage.

The presented field‐circuit coupling completes the two‐dimensional finite element analysis by introducing the possibility to take into account the three‐dimensional part of the motor (R_tête, L_tête). Another advantage is the ability to include voltage sources. Consequently, a realistic approach for the electromagnetic and thermal behavior of the electrical machine is achieved.

Eddy current testing (ECT) is a nondestructive testing method for the detection of flaws that uses electromagnetic induction to find defects in conductive materials. In this method, eddy currents are generated in a conductive material by a changing magnetic field. A defect is detected when there is a disruption in the flow of the eddy current. The purpose of this paper is to develop a new noniterative inversion methodology for detecting degradation (defect characterization) such as cracking, corrosion and erosion from the measurement of the impedance variations.

The methodology is based on multi-output support vector machines (SVM) combined with the adaptive database schema design method (SDM). The forward problem was solved numerically using finite element method (FEM), with its accuracy experimentally verified. The multi-output SVM is a statistical learning method that has good generalization capability and learning performance. FEM is used to create the adaptive database required to train the multi-output SVM and the genetic algorithm is used to tune the parameters of multi-output SVM model.

The results show the applicability of multi-output SVM to solve eddy current inverse problems instead of using traditional iterative inversion methods which can be very time-consuming. With the experimental results the authors demonstrate the accuracy which can be provided by the multi-output SVM technique.

The work allows extending the capability of the experimentation ECT defect characterization system developed at LGEP.

A new inversion method is developed and applied to ECT defect characterization. This new concept introduces multi-output SVM in the context of ECT. The real data together with estimated one obtained by multi-output SVM model are compared in order to evaluate the effectiveness of the developed technique.

The dielectric properties of materials (complex permittivity) can be deduced from the admittance measured at the discontinuity plane of a coaxial open‐ended probe. This implies the implementation of an inversion procedure. The purpose of this paper is to develop a new non‐iterative inversion methodology in the field of microwave characterization allowing reducing the computation cost comparatively to iterative procedures.

The inversion methodology combines the support vector machine (SVM) technique and the finite element method (FEM). The SVM are used as inverse models. They show good approximation and generalization capabilities. FEM allows the generation of the data sets required by the SVM parameter adjustment. A data set is constituted of input (complex admittance and frequency) and output (complex permittivity) pairs.

The results show the applicability of SVM to solve microwave inverse problems instead of using traditional iterative inversion methods which can be very time‐consuming. The experimental results demonstrate the accuracy which can be provided by the SVM technique.

The paper allows extending the capability of microwave characterization cells developed at Laboratoire de Génie Électrique de Paris.

A new inversion method is developed and applied to microwave characterization. This new concept introduces SVM in the context of microwave characterization. SVM results and iterative inversion procedure results are compared in order to evaluate the effectiveness of the developed technique.

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.

Taking a 2,000 r/min 10 kW permanent magnet motor as an example, the purpose of this paper is to study the influence of driving modes on the performance of permanent magnet motor at limit conditions, and researched the variation mechanism of motor performance influenced by different driving modes.

A two-dimensional electromagnetic field model of the permanent magnet motor was established, and a rectangular-wave driving circuit was built. By using the finite element method, the electromagnetic field, current, harmonic content and eddy current loss were calculated when the motor operated at rated load and limit load. On the basis of the motor loss calculation, the temperature field of the motor operating at rated condition and limit condition was researched, and the factors that influence motor limit overload capacity were analyzed. By analyzing the motor loss variation at different load conditions, the change mechanism of the motor temperature field was determined further. Combined with the related experiments, the correctness of the above analysis was verified.

Permanent magnet synchronous motor (PMSM) driven by sine wave is better compared with brushless direct current motor (BLDCM) driven by rectangular wave in reducing the magnetic field harmonics, motor losses and optimizing the temperature distribution in the motor. The method driven by sine wave could improve the motor output performance including the motor efficiency and the motor overload capacity. The winding temperature is the most important factor that limits the output capability of PMSM operating for a long time. However, because of the large rotor eddy current losses, the permanent magnet temperature is the most important factor that limits the output capability of BLDCM operating for a long time.

The influence of driving modes on the motor magnetic field, losses and temperature distribution, efficiency and overload capacity was determined, and the influence mechanism was also analyzed. Combined with the analysis of the electromagnetic and temperature fields, the advantages of different driving modes were presented. This study could provide an important basis for the design of permanent magnet motors with different driving modes, and it also provides reference for the application of permanent magnet motor.

This paper presents the influence of driving modes on permanent magnet motors. The limit output capacity of the motor with different driving modes was studied, and the key factors limiting the motor output capability were obtained.

This paper presents a detailed review of the numerical modeling of inductively coupled air plasmas under local thermodynamic equilibrium and under chemical non‐equilibrium. First, the physico‐chemical models are described, i.e. the thermodynamics, transport phenomena and chemical kinetics models. Particular attention is given to the correct modelling of ambipolar diffusion in multi‐component chemical non‐equilibrium plasmas. Then, the numerical aspects are discussed, i.e. the space discretization and iterative solution strategies. Finally, computed results are presented for the flow, temperature and chemical concentration fields in an air inductively coupled plasma torch. Calculations are performed assuming local thermodynamic equilibrium and under chemical non‐equilibrium, where two different finite‐rate chemistry models are used. Besides important non‐equilibrium effects, we observe significant demixing of oxygen and nitrogen nuclei, which occurs due to diffusion regardless of the degree of non‐equilibrium in the plasma.

The purpose of this paper is to investigate a five-phase permanent-magnet synchronous machine (PMSM) that features high-power density and high-fault-tolerant capability for electric vehicles (EVs).

The five-phase 20-slot/18-pole PMSM is designed by finite-element method. Two typical rotor structures which include Halbach array and rotor eccentricity are compared to achieve sinusoidal back electromotive force (EMF). The influence of slot dimensions on leakage inductance and short-circuit current is analyzed. The method to reduce eddy current loss of permanent magnets (PMs) is investigated. The machine performances under both healthy and fault conditions are evaluated. Finally, thermal behavior of the machine is studied by Ansys.

With both no-load and load performances considered, rotor eccentricity is proposed to reduce the harmonic contents of EMF. Increasing slot leakage inductance is an effective way to limit the short-circuit current. By segmenting PMs in circumferential direction, the PM eddy current loss is reduced and the machine efficiency is improved. With proper fault-tolerant control strategy, acceptable torque performance can be achieved under fault conditions. The proposed machine can safely operate under Class F insulation.

So far, many researches focus on multiphase PMSMs used in aviation fields, such as fuel pump and electric actuator. Differing from PMSMs used in aviation applications, machines for EVs require characteristics like wide speed ranges and variable operating conditions. Hence, this paper proposes a five-phase 20-slot/18-pole PMSM for EVs. The proposed design methodology is applicable to multiphase PMSMs with different slot/pole combinations.