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In this article, we propose an interactive visualization method for motor design. We have proposed a visualization system for education using augmented reality (AR) and virtual reality (VR). As a further development of this, we are working on motor design as an industrial application. There are two issues in achieving high-speed interactivity. One is a fast mesh modification method in finite element analysis, and the other is a fast solving method. We propose a high-speed mesh modification method that utilizes regularly arranged grid points and coordinate transformation. In the proposed design system, the user can immediately observe the analysis result of the design change. Furthermore, if the proposed system is executed in cooperation with the projector, designers can change the design of the motor with their fingers and discuss it on the board. Furthermore, since this system can be executed on a Web browser, it can also be executed on a smartphone or tablet PC. [ABSTRACT FROM AUTHOR]

We have previously been proposed a novel adaptive finite-element method (FEM) based on a magnetic field conservation indicator and a non-conforming mesh-refinement technique. However, we have applied to a very simple model consisting of a single permanent magnet for basic verification of the proposed method. In this paper, we have improved an error indicator, and tried to apply a newly proposed adaptive FEM to more complicated models, where ferromagnetic material is included. The newly proposed method is superior in torque error estimation to the Zienkiewicz-Zhu error estimation method in a 3-D permanent magnet motor model. [ABSTRACT FROM AUTHOR]

Mesh quality strongly affects the solution accuracy in electromagnetic finite-element analysis. Hence, the realization of adequate mesh generation becomes a very important task. Several adaptive meshing methods for automatic adjustments of the mesh density in accordance with the shape and complexity of the analyzed problem have been proposed. However, the most of them are not enough robust, some are quite laborious and could not be universally used for adaptive meshing of complex analysis models. In this paper, a new adaptive mesh refinement method based on magnetic field conservation at the border between finite elements is proposed. The proposed error estimation method provides easy mesh refinements, and generates smaller element within regions with large curvature of the magnetic flux lines. The proposed adaptive mesh refinement method based on non-conforming edge finite elements, which could avoid generation of flat or ill-shaped elements, was applied to a simple magnetostatic permanent magnet model. To confirm the validity and accuracy, the obtained results were compared with those obtained by means of the Zienkiewicz–Zhu (ZZ) error estimator. The results show that the computational error using the proposed method was reduced down to 1% compared with that of the ZZ method, which yields error of 8.6%, for the same model. [ABSTRACT FROM AUTHOR]

In this paper, we propose a real-time visualization system utilizing Augmented Reality Technology for electromagnetics education. It gives an image of magnetic field generated by a bar magnet with a piece of iron in real-time, however the bar magnet and the piece of iron are represented by mock ones. In the newly proposed visualization system, these mocks are captured by a web camera, and mesh needed in the calculation of magnetic field is deformed. Subsequently, a finite element analysis is carried out in very short time and then the magnetic field is immediately visualized. Thereby, it is, in real-time, observable that magnetic flux lines generated by the bar magnet are attracted to a piece of iron. Moreover, when a user moves the mocks, the magnetic flux lines are immediately depicted according to the position of the mocks. [ABSTRACT FROM PUBLISHER]

To solve electromagnetic field problems by the finite element method, it is necessary for a user to make a mesh in preprocess. However, the made mesh is usually different from that made by the other users, since it depends on the user's experience and knowledge. The mesh strongly affects the accuracy of the analysis result. The adaptive finite element method has been researched in order to address this problem. In this paper, we propose a new mesh generation method utilizing magnetic flux lines in two-dimensional electromagnetic field problem. Utilizing the magnetic flux lines computed with a rough mesh, it is possible to distribute elements with different densities suitable for the electromagnetic field distribution. [ABSTRACT FROM PUBLISHER]

The finite-element analysis is widely used in design stage of electromagnetic apparatuses. The analysis accuracy depends on the characteristics of the finite-element mesh, e.g., number of nodes, number of elements and shape of elements. Recently, the adaptive finite-element analysis is one of the most promising numerical analysis techniques. In process of the adaptive finite-element method, the error evaluation is one of the important schemes. In this paper, a new error evaluation scheme, which is suitable for electromagnetic problems, is proposed. The proposed error evaluation method is then applied to two-dimensional and three-dimensional magnetostatic field problems for its verification. [ABSTRACT FROM AUTHOR]

Permanent magnet motors have been widely used. In recent years, from the point of view of energy saving, it is required to improve the efficiency of permanent magnet motors by applying an optimal design method. In this paper, we propose an adjusting technique of the supply voltage of permanent magnet motor when carrying out the optimal design by adopting voltage driven finite element method and genetic algorithm. In calculation for the optimal design, it is difficult to keep a desirable balance of the supply voltage and the induced electromotive force. By using the proposed method, the supply voltage is appropriately decided to generate the rated torque. Owing to adopting this adjusting technique, the computation time for the optimal design can be reduced and the solution can escape from local minima because the needless computations can be drastically reduced. [ABSTRACT FROM AUTHOR]