• Journal of Electrical Engineering and Technology
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• v.1 no.2
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• pp.185-191
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• 2006

In this paper, a novel stator hybrid excited doubly salient permanent magnet (SHEDS-PM) brushless machine with a special magnetic bridge is proposed for the first time. The originality of this machine is purposely to add a magnetic bridge in shunt with each PM pole, which not only maintains the stator lamination in its entireness, but also amplifies the effect of DC field flux on PM flux. An equivalent magnetic circuit is presented to clarify the novelty. Based on the 2-D finite element analysis, the static characteristics of the SHEDS-PM machine, namely phase flux linkage, back-EMF, cogging torque, winding inductance and static torque are deduced. The corresponding results on a prototype machine illustrate that the proposed machine is promising for application to electric vehicles.

• Journal of IKEEE
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• v.22 no.3
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• pp.759-766
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• 2018

This paper presents a high-speed axial-flux machine which utilizes the idea of sinusoidal shaped pole combined with a consequent iron-pole. The target of the proposed machine is the cost reduction of the relatively expensive Samarium-Cobalt (SmCo) permanent magnet (PM) material and the torque per PM volume improvement by using sinusoidal consequent-pole rotor. The effectiveness of the proposed machine is validated by comparing it with conventional consequent-pole and with conventional PM machines using 3-D finite element method (FEM) simulations. The comparison and analysis is done in terms of back electro-motive force (back-EMF) harmonic contents, torque per PM volume and torque ripple characteristics. The simulation results show that the proposed machine is suitable and cost-effective for high-speed and high torque per PM volume applications. Furthermore, due to the consequent pole, the magnetic flux saturation and the overload current torque-capability are also presented and discussed in the paper.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.9
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• pp.127-134
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• 1998

This paper describes the design of a 6-component force/moment calibration machine with having the maximum capacities of 500 N in forces and 50 Nm in moments. To be used for the characteristic of a multi-component load cell. this machine consists of a body, a fixture, a force generating system, a moment generating system and weights. We have also evaluated the accuracy of the calibration machine. Test results show that the expanded relative uncertainty for force components $\pmFx,\;\pmFy\;and\;moment\;components\;\pmMx,\;\pmMy\;are\;less\; than\;8.6\times10^{-4}$, and force components +Fz, -Fz and moment components $\pmMz\;is\;less\;than\;1.6\times10^{-3},\;2.0\times10^{-5},\;1.7\times10^{-3}$ respectively.

• Journal of Power Electronics
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• v.19 no.3
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• pp.744-750
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• 2019

A new type of auto-rotary PM mechanical flux-varying PM machine (ARPMMFVPMM) is proposed in this paper, which can overcome the problem where the air-gap magnetic field of a PM machine is difficult to freely adjust. The topology structures of the machine and the mechanical flux-adjusting device are given. In addition, the operation principle of flux-adjusting is analyzed in detail. Furthermore, the deformation of a spring with the speed variation is obtained by virtual prototype technology. Electromagnetic characteristics including the flux distribution, air gap flux density, flux linkage, electromagnetic-magnetic-force (EMF), and flux weakening ability are computed by 2D finite element method (FEM). Results show that the machine has some advantages such as the good field control ability.

• Industrial Engineering and Management Systems
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• v.7 no.2
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• pp.113-125
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• 2008

This paper presents a model for designing cellular manufacturing systems (CMS) by integrating system cost, machine reliability, and preventive maintenance (PM) planning. In a CMS, a part is processed using alternative process routes, each consisting of a sequence of visits to machines. Thus, a level of 'system reliability' is associated with the machines along the process route assigned to a part type. Assuming machine reliabilities to follow the Weibull distribution, the model assigns the machines to cells, and selects, for each part type, a process route which maximizes the overall system reliability and minimizes the total costs of manufacturing operations, machine underutilization, and inter-cell material handling. The model also incorporates a reliability based PM plan and an algorithm to implement the plan. The algorithm determines effective PM intervals for the CMS machines based on a group maintenance policy and thus minimizes the maintenance costs subject to acceptable machine reliability thresholds. The model is a large mixed integer linear program, and is solved using LINGO. The results point out that integrating PM in the CMS design improves the overall system reliability markedly, and reduces the total costs significantly.

• Environmental and Resource Economics Review
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• v.28 no.4
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• pp.467-495
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• 2019

Uncertainty of renewable energy such as photovoltaic(PV) power is detrimental to the flexibility of the power system. Therefore, precise prediction of PV power generation is important to make the power system stable. The purpose of this study is to forecast PV power generation using meteorological data including particulate matter(PM). In this study, PV power generation is predicted by support vector machine using RBF kernel function based on machine learning. Comparing the forecasting performances by including or excluding PM variable in predictor variables, we find that the forecasting model considering PM is better. Forecasting models considering PM variable show error reduction of 1.43%, 3.60%, and 3.88% in forecasting power generation between 6am~8pm, between 12pm~2pm, and at 1pm, respectively. Especially, the accuracy of the forecasting model including PM variable is increased in daytime when PV power generation is high.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.857_858
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• 2009

On account of small size and light weight, a high-speed machine is regarded as a key technology for many future applications of drive systems. In high-speed applications, permanent magnet (PM) synchronous motors have a number of merits such as high efficiency and high power density. Accordingly, they are suitable for driving the air-blower of a fuel cell electric vehicle (FCEV) where space and energy savings are critical. Particularly, a surface-mounted PM motor of them is mainly used as a high-speed machine. However, the motor has a fatal flaw owing to a retaining can to maintain the mechanical integrity of a rotor assembly. The can results in the increase of magnetic air-gap length in the surface-mounted PM motor. Thus, in this paper, an interior PM motor is designed in order to drive the air-blower of FCEV instead of the surface-mounted PM motor, and the experimental results of two models are compared to verify the capability of the interior PM motor for a high-speed machine.

• Journal of Magnetics
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• v.21 no.3
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• pp.399-404
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• 2016

This paper presents a new permanent magnet (PM) assisted topology for a recently introduced brushless wound rotor synchronous machine (BL-WRSM) [1]. The BL-WRSM had a dual-inverter configuration for generating a composite magneto motive force (MMF) with a fundamental component and a subharmonic component. The subharmonic component of the MMF is used for brushless excitation of the rotor. In this paper, additional PMs were introduced on the rotor of the BL-WRSM, making it a hybrid BL-WRSM. We also discussed the flux weakening operation for the hybrid BL-WRSM. The hybrid BL-WRSM offered advantages for starting the machine and provided better performance under full-load conditions. The finite element method (FEM) was used to analyze the performance of the hybrid BL-WRSM, and we compared its performance with BL-WRSM. Finally, prototypes were built with and without the PM-assistance, and experiments were conducted to demonstrate their performance.

• Communications for Statistical Applications and Methods
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• v.31 no.2
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• pp.235-246
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• 2024

In high-dimensional data analysis, sufficient dimension reduction (SDR) has been considered as an attractive tool for reducing the dimensionality of predictors while preserving regression information. The principal support vector machine (PSVM) (Li et al., 2011) offers a unified approach for both linear and nonlinear SDR. This article comprehensively explores a variety of SDR methods based on the PSVM, which we call principal machines (PM) for SDR. The PM achieves SDR by solving a sequence of convex optimizations akin to popular supervised learning methods, such as the support vector machine, logistic regression, and quantile regression, to name a few. This makes the PM straightforward to handle and extend in both theoretical and computational aspects, as we will see throughout this article.

• Journal of Electrical Engineering and Technology
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• v.11 no.1
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• pp.150-156
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• 2016

This paper compares the performances of permanent-magnet synchronous (PMS) and permanent-magnet vernier (PMV) machines for low-speed and high-torque applications. For comparison with the PMS machines, we consider two types of the PMV machine. The first one has surface-mounted permanent magnets (PMs) on the rotor and the other has PMs inserted on both sides of the stator and rotor. The PMS and PMV machines are designed to meet the condition of equal output power per unit volume. We analyze the magnetic fields of the machines using a two-dimensional finite element analysis (FEA). We then compare their performances in terms of the generated torque characteristics, power factor, loss, and efficiency.