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Discusses the 27 papers in ISEF 1999 Proceedings on the subject of electromagnetisms. States the groups of papers cover such subjects within the discipline as: induction machines; reluctance motors; PM motors; transformers and reactors; and special problems and applications. Debates all of these in great detail and itemizes each with greater in‐depth discussion of the various technical applications and areas. Concludes that the recommendations made should be adhered to.

Presents a review on implementing finite element methods on supercomputers, workstations and PCs and gives main trends in hardware and software developments. An appendix included at the end of the paper presents a bibliography on the subjects retrospectively to 1985 and approximately 1,100 references are listed.

Thirteen computer codes developed by eleven groups are applied to the benchmark problem 20 (3‐D static force problem) for the TEAM Workshop. The solutions are compared with each other and with experimental results.

This paper aims to present a data-processing methodology combining kernel change detection (KCD) and efficient global optimization algorithms for solving inverse problem in eddy current non-destructive testing. The main purpose is to reduce the computation cost of eddy current data inversion, which is essentially because of the heavy forward modelling with finite element method and the non-linearity of the parameter estimation problem.

The KCD algorithm is adapted and applied to detect damaged parts in an inspected conductive tube using probe impedance signal. The localization step allows in reducing the number of measurement data that will be processed for estimating the flaw characteristics using a global optimization algorithm (efficient global optimization). Actually, the minimized objective function is calculated from data related to defect detection indexes provided by KCD.

Simulation results show the efficiency of the proposed methodology in terms of defect detection and localization; a significant reduction of computing time is obtained in the step of defect characterization.

This study is the first of its kind that combines a change detection method (KCD) with a global optimization algorithm (efficient global optimization) for defect detection and characterization. To show that such approach allows to reduce the numerical cost of ECT data inversion.

This paper aims to give a perspective about the variety of techniques which are available and are being further developed in the area of coupled field formulations, with selective bibliography and practical examples, to help postgraduate students, researchers and designers working in design or analysis of electrical machinery.

This paper reviews the recent trends in coupled field formulations. The use of these formulations for designing and non‐destructive testing of electrical machinery is described, followed by their classifications, solutions and applications. Their advantages and shortcomings are discussed.

The paper gives an overview of research, development and applications of coupled field formulations for electrical machinery based on more than 160 references. All landmark papers are classified. Practical engineering case studies are given which illustrate wide applicability of coupled field formulations.

Problems which continue to pose challenges to researchers are enumerated and the advantages of using the coupled‐field formulation are pointed out.

This paper gives a detailed description of the application of the coupled field formulation method to the analysis of problems that are present in different electrical machines. Examples of analysis of generators and transformers with this formulation are presented. The application examples give guidelines for its use in other analyses.

The coupled‐field formulation is used in the analysis of rotational machines and transformers where reference data are available and comparisons with other methods are performed and the advantages are justified. This paper serves as a guide for the ongoing research on coupled problems in electrical machinery.

The design of electrical machines includes the computation of several requirements and, in general, the improvement of one requirement implies in a degradation of another one: this is a typical multi‐objective scenario. The paper focuses on the multi‐optimization analysis of a special switched reluctance motor.

Two design requirements were analyzed: the average torque and the ripple torque. The electromagnetic field computation was performed by the finite element method and the torque was computed by the Coulomb's Virtual Work for several positions. This allows us to calculate the average torque and the ripple torque. Three different methods were used to obtain the Pareto set: a min‐max approach, the non‐dominated sorting genetic algorithm (NSGA) and the strength Pareto evolutionary algorithm (SPEA). In order to save the computation time, the objective functions (the average torque and the ripple torque) were replaced with surrogate functions. Kriging models were used as surrogate functions.

The evolutionary methods (NSGA and SPEA) have a similar performance. The min‐max has not the same performance. It could have the same performance only if some unconstrained optimization problems are solved before the multi‐objective optimization. The maximum relative deviation between the approximated function (Kriging model) and the same value calculated by the finite element method was equal to 0.8 percent for the average torque and 1.2 percent for the ripple torque. The ripple torque, considered as the difference between the maximum and the minimum values in the 0‐90° region, has reduced while its frequency has doubled. This last characteristic provides a better mechanical stability for the driven load because its inertia softens the ripple effects at the double the frequency. The optimized prototype presents higher torques in the region θ<0° and this allows the electronic drive to switch in a broader range rendering the motor operation more flexible.

The use of surrogate functions save the computation time with high accuracy. This is very important on the design of electrical machines, a typical multi‐objective scenario. Evolutionary methods seem to be well suited to solve this class of problem.

The purpose of this paper is the presentation of an electrical equivalent circuit for inductive components as well as the methodology for electrical parameter extraction by using a 3 D finite element analysis (FEA) tool.

A parameter extraction based on energies has been modified for three dimensions. Some simplifications are needed in a real model to make the 3 D finite element method (FEM) analysis operative for design engineers. Material properties for the components are modified at the pre-modeling step and a corrector factor is used at the post-modeling step to achieve the desired accuracy.

The current hardware computational limitations do not allow the 3 D FEA for every magnetic component, and due to the component asymmetries, the 2 D analysis are not precise enough. The application of the new methodology for three dimensions to several actual components has shown its usefulness and accuracy. Details concerning model parameters extration are presented with simulation and measurement results at different operation frequencies from 1 kHz to 1 GHz being the range of switching frequencies used by power electronic converters based on Si, SiC or GaN semiconductors.

This new model includes the high-frequency effects (skin effect, proximity effect, interleaving and core gap) and other effects can be only analyzed in 3 D analysis for non-symmetric components. The electrical parameters like resistance and inductance (self and mutual ones) are frequency-dependent; thus, the model represents the frequency behavior of windings in detail. These parameters determine the efficiency for the inductive component and operation capabilities for the power converters (as in the voltage boost factor), which define their success on the market.

The user can develop 3 D finite element method (FEM)-based analyses with geometrical simplifications, reducing the CPU time and extracting electrical parameters. The corrector factor presented in this paper allows obtaining the electrical parameters when 3D FE simulation would have developed without any geometry simplications. The contribution permits that the simulations do not need a high computational resource, and the simulation times are reduced drastically. Also, the reduced CPU time needed per simulation gives a potential tool to optimize the non-symmetric components with 3 D FEM analysis.

The purpose of this paper is to develop and systemize the 3D finite element (FE) description of electromagnetic field in electrical machines.

3D FE models of electrical machines are considered. The model consists of FE equations for the magnetic field, equations describing eddy currents and equations, which describe the currents in the machine windings. The FE equations are further coupled by the electromagnetic torque to the differential equation of motion. In the presented field‐circuit model, the flux linkages with the windings are expressed by two components. Attention is paid to the description of machine winding. Both scalar and vector potential formulations are analysed. The FE equations are derived by using the notation of circuit theory. The methods of movement simulation and torque calculation in FE models are discussed.

Proposed circuit description of electromagnetic field in electrical machines conforms to the applied method of electric and magnetic circuit analysis. The advantage of the presented description is that the equations of field model can be easy associated with the other equations of the electric drive system.

The applied analogies between the FE formulation and the equivalent magnetic and electric network models help formulate efficient field models of electrical machines. The developed models after coupling to the models of supply and control system can be successfully used in the analysis and design electric drives.

This paper compares three different radial basis function neural networks, as well as the diffuse element method, according to their ability of approximation. This is very useful for the optimization of electromagnetic devices. Tests are done on several analytical functions and on the TEAM workshop problem 25.

This paper aims to present the use of magnetic gradient, and magnetic potential measurements in the specific case of magnetization identification for a thin sheet. Usually, induction measurements are only used.

After a brief description of the magnetic gradient and magnetic scalar potential notions, methods to calculate them are presented and validated. These two kinds of measurements are tested for a numerical identification case. Then, virtual measurements can be generated and used for inverse problem resolution. Advantages of using induction, magnetic gradient or magnetic potential measurements are then discussed.

A previous method to solve inverse problem based on induction measurement has been increased by the capability of using other kind of measurements. A numerical approach has allowed to validate the use of magnetic gradient or magnetic scalar potential measurement as information sources.

Usually, induction measurements are only used. Inversion resolution using other kind of measurements than the induction can be made. An experimental validation has been done for gradient measurements.