Evaluation of hysteresis loss and eddy-current loss in induction motor stator cores using the excitation inner core method

Oka, M.; Enokizono, Masato

doi:10.1109/icelmach.2016.7732751

Cited by 3 publications

(2 citation statements)

References 9 publications

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“…However, a general method of evaluating the iron loss of the stator core has not been yet established. Therefore, we developed the excitation inner core method to evaluate the circumferential and axial distribution of the iron loss of the actual stator core [6][7][8]. In this study, we are presenting two variations on of the excitation inner core method.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of frame-induced compressive stress on the magnetic properties of stator cores using the excitation inner core method

Oka

Enokizono²

2018

Journal of Electrical Engineering

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To improve the efficiency of electric motors, we developed the excitation inner core method to evaluate the magnetic properties such as the iron loss of the actual stator core. After preparing two stator cores with a frame, we examined the frames influence of compressive stress by applying the standard and small excitation inner core methods to evaluate the iron loss of both stator cores having a frame. After removing the frames of the two stator cores, we evaluated the iron loss of two stator cores without the frames again by applying both methods.

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Section: Introductionmentioning

confidence: 99%

Evaluation of frame-induced compressive stress on the magnetic properties of stator cores using the excitation inner core method

Oka

Enokizono²

2018

Journal of Electrical Engineering

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“…Herzog and Buechelr [14] discuss modeling complex inductance for plotted iron loss of permanent magnet induction motor. Enokizono & Oka evaluate hysteresis loss and eddy current loss on stator core induction motor using excitation inner core method [15]. The scientific literature [16] [17] offers more accurate space vector dynamic models to consider B and H on rotating machine.…”

Section: Introductionmentioning

confidence: 99%

Stator Flux Estimator Using Feed-Forward Neural Network for Evaluating Hysteresis Loss Curve in Three Phase Induction Motor

Praharsena

Purwanto

Jaya

et al. 2018

emitter

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The operation of induction motors with high performance contributes significantly to the global energy savings but hysteresis loss is one of the factors causing decreased performance. Stator flux density (B) and magnetic field intensity (H) must be plotted to know hysteresis loss quantity. Unfortunately, since the rotor rotates in time series, the stator flux density is unmeasurable quantities. It is hard to directly detect this properties because of limited airgap space and costly installation of additional instrument The purpose of this paper is to evaluate the hysteresis loss quantity in induction motor using a novel method of multilayer perceptron Feed Forward Neural Network (FFNN) as stator flux estimator and magnetizing current model as magnetic field intensity properties. This method is effective because it's non-destructive method, without an additional instrument, low cost, and suitable for real-time motor drive systems. The FFNN estimator response is satisfied because it is accurate to estimate stator flux density for evaluating hysteresis loss quantity including its magnitude and phase angle. By using the proposed model, the stator flux density and magnetizing current can be plotted to be hysteresis loss curve. The performance of flux response, speed response, torque response and error deviation of stator flux estimator has been presented, investigated, compared and verified in Simulink Matlab.

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Computation of Eddy Current Loss in a Ferromagnetic Core with Single Excitation

Venkadesan¹,

Sedhuraman²

2018

2018 Ieee International Conference on System, Computation, Automation and Networking (Icscan)

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Evaluation of hysteresis loss and eddy-current loss in induction motor stator cores using the excitation inner core method

Cited by 3 publications

References 9 publications

Evaluation of frame-induced compressive stress on the magnetic properties of stator cores using the excitation inner core method

Evaluation of frame-induced compressive stress on the magnetic properties of stator cores using the excitation inner core method

Stator Flux Estimator Using Feed-Forward Neural Network for Evaluating Hysteresis Loss Curve in Three Phase Induction Motor

Computation of Eddy Current Loss in a Ferromagnetic Core with Single Excitation

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