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In this paper, the multi-objective topology optimizations of wireless power transfer (WPT) devices with two different coil geometries are proposed for obtaining the designs with good balance between transfer efficiency and safety. For this purpose, the proposed method adopts the normalized Gaussian network (NGnet) and Non-dominated Sorting Genetic Algorithm II (NSGA-II). In addition, the optimization under the different constraint on ferrite volume is carried out to verify its influence on optimization results. It has been shown that the proposed method successfully provides the Pareto solution to the design problem of the WPT device.

This paper presents three-dimensional topology optimization of magnetic cores for wireless power transfer with double-sided winding coils. In this optimization, the magnetic core shape is represented by the linear combination of the normalized Gaussian functions. The core shape is optimized so that the coupling coefficient between the transmitting and receiving coils is maximized. Moreover, robustness against misalignment between the coils is taken into account in the optimization. It is found that the optimized core shape effectively increases the net magnetic flux interlinked with the receiving coil, and outperforms the conventional core shapes.

This paper presents a new topology optimization of interior permanent magnet (IPM) motors using the genetic algorithm with aid of the deep leaning. The data composed of the rotor shape of an IPM motor and its performance, obtained by a prior topology optimization process, is input to a convolutional neural network (CNN). After the learning process, CNN is shown to provide fairly accurate estimate of the motor performance. During the posterior topology optimization, the finite element analysis (FEA) is carried out only for the limited number of individuals; probability that FEA is performed increases with the motor performance evaluated by CNN. It is shown that the computing time is reduced to about 1/10 without deterioration of the optimization performance with aid of the deep learning.

This paper introduces a new method for fast computing of the iron and copper losses in electromagnetic systems. In the method, the finite element equation is reduced to the equivalent Cauer circuit via model order reduction. The nonlinear property due to core saturation is pre-computed and included in the Cauer circuit. While the copper loss is computed as the Jule loss in the circuit, the iron loss is computed in the post process by restoring the field distribution from the solution to the circuit equation with aid of the proper orthogonal decomposition.

This paper presents the current and thermal phenomena of multi-stacked No-Insulation (NI) REBa2 Cu3O7-x (REBCO, RE = Rare Earth) pancake coils during a local normal-state transition. An NI winding technique is expected to enhance the thermal stability of REBCO pancake coils, and it was verified in numerical simulations on a single pancake coil. However, a multi-stack of pancake coils are used to generate a high magnetic field in practical applications. When a normal-state transition occurs in one of multi-stacked pancake coils, it may deteriorate the stability of the other pancake coils. Therefore, we have developed a numerical simulation code to clarify the current and thermal behaviors of multi-stacked NI REBCO pancake coils using a partial element equivalent circuit model and a thermal finite element method.

The chaotic vibration energy harvester (CVEH) converts vibration of constructions to electric energy in wide frequency. It needs large computational cost for evaluation of the magnetic force between the moving magnets and magnetic material embedded in the stator coils of CVEH when using finite element method (FEM). This paper presents magnetic circuit modeling of CVEH to reduce computational burden. It is shown that the frequency responses of CVEH computed by the present method is in good agreement with those obtained by FEM. This result is validated through the experiment.

This paper presents optimal shape design of planar array antennas for microwave energy harvesters. The topology optimization of the C-4-symmetric array antenna is conducted to maximize their isotropic gain and minimize the return losses in a frequency band ranging from 1.5 to 3.5 GHz. Then, we design the rectifier by varying the circuit parameter based on measurement results to realize the impedance matching between the optimized antenna and rectifier. It is shown by experiment that the harvester composed of the optimized array antenna and rectifier has higher receiving voltage in comparison with the single one. Moreover, the resultant harvester is found to start operating when the arrival electric field is greater than 0.1 V/m.

It is known that the proper orthogonal decomposition (POD), which is one of the effective approaches for model order reduction (MOR), can effectively reduce computational time for finite element method (FEM). This paper proposes a new method for generation of equivalent circuits based on POD-based FEM. In this method, the circuit parameters are determined by genetic algorithm so that the input impedance of the equivalent circuit is coincident with that computed by POD-based finite element method (FEM). For test of the proposed method, POD-based FEM is applied to analysis of a dipole antenna which is loaded with the Cockcroft Walton circuit. It is shown that this method can reduce the computational time to generate the equivalent circuit without deterioration of accuracy.