This paper describes a reluctance network based dynamic analysis method used in the field of power magnetics, which is called reluctance network analysis (RNA). It is based on the magnetic circuit method and has some advantages for simulating electrical machinery such as a simple analytical model, high calculation accuracy, and easy to combine with an electric circuit, motion and thermal dynamics. First, the basis of the magnetic circuit method is described. Next, two case studies of RNA, one is a permanent magnet (PM) motor and the another is a switched reluctance (SR) motor, are presented.

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This paper describes a three-dimensional reluctance network analysis (RNA) of an EIE-core variable inductor, which can be applied as a reactive power compensator in electric power systems. First, a three-dimensional RNA model of an EIE-core considering the magnetic saturation and iron loss is presented. Using the proposed RNA model with external electric circuits, operating characteristics of the variable inductor including the iron loss are calculated accurately. Next, high performance of a 6.6 kV-300 kVA reactive power compensator using the EIE-core variable inductor is demonstrated in a distribution system.

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This paper describes a circuit analysis of a magnetic oscillation type sinusoidal inverter. The inverter is connected to an ac voltage source such as the line power, and can supply electric power easily to the ac voltage source. The inverter utilizes a magnetic oscillation circuit constructed with power transistors and a nonlinear magnetic core. In order to quantitative analysis, we present a simulation model of the magnetic oscillation circuit based on a general purpose circuit simulation program “SPICE”. The simulation results of the oscillation voltage and current waveforms agree well with experimental ones.

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This paper studies the nonlinear response of a parallel ferroresonant circuit. To carry out a transient analysis in parallel ferroresonant circuit, we apply Chua-type magnetization model to an inductance exhibiting saturation and hysteretic nonlinear properties of ferromagnetic materials, deriving a state variable equation and solutions by the backward Euler method with automatic modification. The characteristic values of the state transition matrix are calculated in each calculation step of Euler method in order to extract the chaotic characteristics. As a result, it is clarified that the chaotic behavior in the ferroresonant circuit is greatly concerned with the magnetic aftereffect of ferromagnetic materials.

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A laminated core parametric induction motor has desirable features and the planer structure to make it possible to reduce the production cost of the motor by mass production. In the past work, we showed the validity to apply the two-dimensional reluctance network analytical model to the dynamic analysis of the motor while the rotor is driving. In this paper, we investigate the improvement the accuracy of the analytical method of the motor by using new reluctance network analytical model of the motor. In this model, the magnetic circuits of the stator and the rotor are connected by the variable reluctances that are expressed as the function of the rotating angle.

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Feedback signals of rotor speed and motor torque are essential in most of Switched Reluctance (SR) motor control applications. An SR motor has highly nonlinear characteristic that does not allow to be modeled by simple equations. In Direct Torque Control (DTC) drive, which enables easy control of torque ripple in the SR motor, position sensor is employed to obtain the feedback signals. Position sensor causes DTC drive not only less reliable but also more expensive. Estimation of feedback signals is required in order to eliminate position sensor. This paper concerns about sensorless speed estimation under the DTC condition and presents a simple method. Simple sensorless speed estimation is proposed based on inductance vector angle. The inductance vector angle is obtained by applying α-β transformation to the phase inductances. A relay triggers a speed calculation circuit according to its band limits and the inductance vector angle. Inside the circuit, triggering time is kept in a memory until the next triggering. Rotor pole pitch is divided by the time difference between two consecutive triggerings. Finally, the estimation circuit outputs the rotor speed. Sensorless speed estimation is simulated and verified experimentally to show its validity.

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Switched Reluctance(SR) motors have several advantages for industrial applications. However, their drive circuits are not necessarily suitable. The drive circuit of a 3-phase SR motor has 6 switches and 6 diodes such as general 3-phase inverter, but its connection is different. So, a general 3-phase power module such as Intelligent Power Module(IPM) can't be used. We proposed a novel drive circuit for SR motors, which can be constructed using general a 3-phase power module without external inductors or devices. This drive method has several advantages including low cost, high efficiency, and compactness. It was simulated on SPICE including the controller and the driving performances were investigated. The new drive circuit allowed phase current to flow bi-directionally. So, the reluctance torque of SR motors is not affected by current direction. Then, we developed the new drive circuit for a 6/4 SR motor using a conventional 3-phase IPM. The results of the experiments indicated same performances as conventional way and higher efficiency than conventional way.

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This paper discusses the deterioration mechanism of magnetic properties of cores due to punching and proposes the modeling, as the best design of motors, considering manufacturing motors, is important in order to improve the high performance of motors corresponding to energy saving. In producing motors, magnetic cores with laminated steel sheets are made of punched sheets, and then the magnetic properties of steel sheets are deteriorated by plastic deformation and the induced residual stress due to punching. In this paper, the punching deterioration mechanism is investigated by observing magnetic domains at steel surfaces near sheared parts. Tensile and compressive stresses induced at cut steel edges deteriorate the magnetic properties of punched steel sheets in high flux densities as the compression deterioration is stronger than the tension improvement, and improve permeabilities at low magnetic field because the increases in permeabilities with tensile stresses are emphasized. Therefore, it is necessary to model the magnetic properties of motor magnetic cores, taking account of these magnetic phenomena.

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This paper proposes a method of 3-D Lissajous diagram for signal processing of a differential coil type magnetic sensor. Overlapping several Lissajous diagrams between the sensor input and output signals yields a three-dimension or grayscale image whose height or tone reveals a number of overlapped points. This conversion from the time-domain sensor signals to an image provides the differences in frequency, amplitude, phase, distortion, etc. Employing image cognition methodology to this three-dimension image makes it possible to identify each of the signals stored in a database. We demonstrate the renmarkable cognition results by our magnetc sensor signals processing strategy.

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This paper describes a new type variable inductor and its applications to reactive power controller for use in electric power system. We present a 6.6kV-300kVA magnetic flux control type reactor (MFCR) for reactive power compensator based on the EIE-core type variable inductor. The MFCR has good control characteristics, simple structure and high reliability, low level harmonic currents , high-speed response and low cost.

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A circuit model was developed to analyze the electromagnetic field in ferrites, for contribution to the design of power circuits by taking into account the power loss in the high-frequency region. The ferrite power loss in the high-frequency region consists of the hysteresis loss and the dynamic magnetic loss. This paper proposes a novel model for electromagnetic field analysis, which is able to compute the magnetic, eddy current and displacement current losses, based on the spatial network method. The validity of the method is verified by comparing the computed power losses with those obtained by the finite element method.

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An increase in platinum catalyst utilization in polymer electrolyte fuel cells (PEFCs) is necessary to improve performance and reduce costs. We have previously proposed a novel electrode preparation method, based on the process of grafting a proton-conducting agent onto platinum-supported carbon before the conventional electrode fabrication process. In the present study, platinum-supported carbon grafted with methylsulfonic acid groups (-CH₂SO₃H) and platinum-supported carbon grafted with polyacrylamide tert-butylsulfonic acid groups (Poly-ATBS) were mixed in fabricating the membrane electrode assembly (MEA). The PEFCs' performance of the MEA made from our novel ionomer-grafted platinum-supported carbon material was superior to that of an MEA made using the conventional method using Nafion as an ionomer. The current density at 0.7 V of the MEA using grafted proton-conducting groups on catalyst-supported carbon was 600 mA/cm², which is twice as large as the MEA using nongrafted catalyst-supported carbon.

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