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All Journal ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika EMITTER International Journal of Engineering Technology JURNAL INTEGRASI Jurnal Teknologi dan Riset Terapan (JATRA) Journal of Applied Electrical Engineering Jurnal Rekayasa elektrika Jurnal Rekayasa Energi
Handri Toar
Politeknik Negeri Batam
Aerospace Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering Other

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Journal : emitter international journal of engineering technology

 1 
Stator Flux Estimator Using Feed-Forward Neural Network for Evaluating Hysteresis Loss Curve in Three Phase Induction Motor Praharsena, Bayu; Purwanto, Era; Jaya, Arma; Rusli, Muhammad Rizani; Toar, Handri; wk, Ridwan
EMITTER International Journal of Engineering Technology Vol 6, No 1 (2018)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v6i1.263

Abstract

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’s hard to direct sensored this properties because of limited airgap space and costly to install 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 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 satisfying because accurately 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 become 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.
Stator Flux Estimator Using Feed-Forward Neural Network for Evaluating Hysteresis Loss Curve in Three Phase Induction Motor Praharsena, Bayu; Purwanto, Era; Jaya, Arma; Rusli, Muhammad Rizani; Toar, Handri; wk, Ridwan
EMITTER International Journal of Engineering Technology Vol 6 No 1 (2018)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (704.235 KB) | DOI: 10.24003/emitter.v6i1.263

Abstract

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’s hard to direct sensored this properties because of limited airgap space and costly to install 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 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 satisfying because accurately 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 become 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.
Co-Authors Abdillah Aziz Muntashir Adlian Jefiza Aji Sanjaya angga wahyu aditya APRIYANTO, RADEN AKBAR NUR Arif Febriansyah Juwito Aryeni, Illa BASUKI, GAMAR Bestari Simanjuntak, Chrystin Budiana, Budiana Daniel Sutopo Pamungkas, Daniel Sutopo Dedid Cahya Happyanto Didi Istardi Diono, Diono Era Purwanto Fakhruddin, Hanif Hasyier Fauzun Atabiq Fitriyanti Nakul Gindo Leonard Manahan Simanjuntak Hana Mutialif Maulidiah Hary Oktavianto Hasnira Hasnira Ilham Ridha Alamsyah Illa Aryeni Irwanto Zarma Putra Jaya, Arma Jaya, Arma M. Prihadi Eko M. Syafei Gozali Manurung, Anjunius Maulidiah, Hana Mutialif Micko Tomas Muammar Khadapi Arif Nasution Muhammad Fajar Ar Rakhman Ghifari Muhammad Jaka Wimbang Wicaksono Muhammad Khoirun Nash Muhammad Lathif Muhammad Naufal Airlangga Diputra Muhammad Prihadi Eko Wahyudi Muhammad Syafei Gozali Nanta Fakih Prebianto Nasution, Muammar Khadapi Arif Novianti Yuliarmas Novrian Eka Sandhi Nur Sakinah Asaad Nurfaizah M Praharsena, Bayu Praharsena, Bayu Qoriatul Fitriyah Renaldy Aritha RIA ANGGRAINI Ridwan Ridwan Ridwan W.K. Rusli, Muhammad Rizani Siti Aisyah Sumantri K Risandriya Veithzal Rivai Zainal Wasdoni Alfi Wicaksono, Muhammad Jaka Wimbang Widya Rika Puspita wk, Ridwan wk, Ridwan