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Comparative Study of Modulation-Based Individual Inverter Techniques for Direct and Inverse by using Star-Connection Induction Motor in Extra Low Voltage Application Wishnuprakasa, Ardhia; Purwanto, Era; Windarko, Novie Ayub
EMITTER International Journal of Engineering Technology Vol 4 No 2 (2016)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (3191.69 KB) | DOI: 10.24003/emitter.v4i2.154

Abstract

In this study, the IEEE 519 Standard as a basis benchmarking for voltage (THDV) and current (THDI) in draft performance. Comparative Study based onthree-techniques of 2-Level Converter (2LC) by using a Star-Connection Induction Motor (Y-CIM) in ExtraLow Voltage (ELV) Configuration.For the detail explanation, a primary inverter as Direct-Inverterby PWMdirect (PWM) degreesand asecondary inverter as Inverse-Inverterby PWMinverse(PWM + PI) degrees. It tends a modified algorithm,for eachof SPWM in six rules, and FHIPWM in 5th harmonics Injectedin standard modulation as the purpose for the Open-Ends of Pre-Dual Inverter in Decoupled SPWM for twelve rules, and Decoupled FHIPWM in combination of 5th harmonics Injectedin combination of two-standard-modulation. Those techniques are the purpose of two-inverter combination, which namelythe Equal Direct-Inverse (EDI) algorithmproduct of prototyping in similarities. The observation is restricted in voltage scope between Simulation by using Power Simulator (PSIM)and Application by using Microcontroller ARM STM32F4 Discovery.
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.
Smart adaptive CC-CV charger with PSO-accelerated load identification and fuzzy duty-cycle regulation Indhana Sudiharto; Era Purwanto; Muhamad Milchan; Alifian Nur Rahmadika
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v17.i2.pp1045-1057

Abstract

This paper presents an adaptive constant-current/constant-voltage (CC-CV) charger architecture, meticulously designed to address a key challenge in smart chargers. This challenge involves recognizing various battery types and applying the appropriate charging profile expeditiously, without requiring user intervention. The system integrates a particle swarm optimization (PSO) algorithm for ultra-fast load identification with a Mamdani-type fuzzy logic controller for precise duty cycle regulation. The PSO mechanism is capable of determining the optimal initial duty cycle in less than 500 milliseconds. Subsequent to this preliminary initiation, the fuzzy logic controller guarantees the effectiveness of current and voltage regulation during the charging phases. The simulation results obtained from this study validate the system's robustness, as evidenced by the consistent maintenance of voltage ripple below ±0.06 V and current ripple below ±0.04 A. These findings demonstrate the efficacy of the proposed approach in achieving fast, stable, and safe multi-load battery charging. The chemistry-agnostic design of the battery pack is extendable to any battery pack following the CC-CV paradigm, making it highly suitable for practical applications that demand flexibility and high reliability.
Design and Implementation of a Transformer Winding Machine with Buck-Boost Converter-Based DC Motor Drive Muhammad Rizani Rusli; Gigih Prabowo; Taufiqurrahman Taufiqurrahman; Arman Jaya; Syechu Dwitya Nugraha; Era Purwanto
Rekayasa Vol 19, No 1: 2026
Publisher : Universitas Trunodjoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/rekayasa.v19i1.27486

Abstract

This research presents the design and implementation of a high-frequency transformer winding machine driven by a DC motor with a Buck-Boost converter to produce transformers accurately and efficiently. The system integrates a DC motor controlled by a Buck-Boost converter, which regulates the voltage to the motor, ensuring stable performance during the winding process. The winding machine design includes a stable mechanical platform, a V-belt mechanism for power transmission, and optocoupler sensors for real-time monitoring of winding turns. The Buck-Boost converter stabilizes voltage fluctuations, allowing smooth motor operation under various input conditions, thereby improving machine efficiency and reliability. Experimental tests on the rectifier, Buck-Boost converter, and DC motor demonstrate high efficiency and stable performance, with minimal deviation between calculated and experimental results. Test results show that this machine can perform precise winding across different duty cycles, with optimal speed control and stable operation. Compared to existing transformer winding machines using induction motors or stepper motors, this system offers better control, faster winding speeds, and greater adaptability to different production conditions. The developed machine significantly contributes to industries such as transformer manufacturing and power electronics, with increased productivity, reduced production costs, and improved transformer quality, especially in high-frequency applications such as renewable energy systems and electric vehicle charging.
Design of a Model Predictive Control for Speed Control of a Motor Drive System in an Electric Oil Palm Cutter Indra Ferdiansyah; Fifi Hesty Sholihah; Gigih Prabowo; Era Purwanto; Hairul Faizi Hairulnizam
Agroindustrial Technology Journal Vol. 9 No. 2 (2025): Agroindustrial Technology Journal [ATJ]
Publisher : Universitas Darussalam Gontor

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study presents the design of a speed control system for a Motor Drive Permanent Magnet Synchronous Motor (MDPMSM) to achieve a faster and more stable dynamic response in an electric oil palm cutter, supporting the harvesting process of oil palm fruit. Conventional control methods such as Proportional-Integral (PI) controllers, which are commonly applied, still face challenges in parameter tuning and exhibit high sensitivity to speed variations in cutting operations. To overcome these limitations, this research proposes a Model Predictive Control (MPC)-based speed regulation system integrated into a Field-Oriented Control (FOC) structure for a encoderless MDPMSM. The mathematical model of the motor serves as the foundation for designing the predictive algorithm, which can estimate motor speed behavior in real time. Performance evaluation was conducted through simulations under step-response conditions involving sudden speed changes, as well as ramp-response conditions. The simulation results were compared with those of the PI controller to assess the system’s ability in achieving steady-state time, overshoot, and undershoot. The results demonstrate that the MPC-based controller significantly enhances system performance, achieving up to a 60% reduction in settling time, an 84% decrease in overshoot, and a 58% improvement in recovery capability. Moreover, under ramp-response testing, the MPC-based system exhibited a more linear and responsive speed-tracking performance. Therefore, the proposed MPC control design proves to be effective in improving the accuracy and stability of encoderless MDPMSM speed control systems and serves as a reliable alternative for high-precision motor drive control applications, particularly in electric oil palm cutting systems.
Co-Authors A'yun, Rifki Qurotul Abdillah Aziz Muntashir Abdullah Aziz Muntashir Ade Rochmana Ade Rochmanu Aditya Ilham Pradana Adoe, Cenneth Paolo Anderson Bai Agustian, Singgih Ainur Rofiq Akbar, Gilang Ekavigo Astafil Alifian Nur Rahmadika Amrinsani, Farid Ananto Mukti Wibowo angga wahyu aditya Apriyanto, R. Akbar Nur APRIYANTO, RADEN AKBAR NUR Ardhia Wishnuprakasa Aries Alfian Prasetyo Arman Jaya Bambang Sumantri Bambang Sumantri Bambang Sumantri BASUKI, GAMAR Bayu Praharsena Dedid Cahya Happyanto Diah Septi Y. Dimas Okky Anggriawan Eka Prasetyono, Eka Endro Wahjono Endro Wahjono, Endro Erawati, Fera Fachrurozy, Fachrurozy Fakhruddin, Hanif Hasyier Farid Amrinsani Farid Dwi Murdianto Fathur Zaini Rachman Fera Erawati Ferdiansyah, Indra Fifi Hesty Sholihah GAMAR BASUKI Gamar Basuki Gigih Prabowo Gigih Prabowo Hairul Faizi Hairulnizam Handri Toar Hanif Hasyier FAkhruddin HANIF HASYIER FAKHRUDDIN Hanif Hasyier Fakhruddin Hary Oktavianto Hendik Eko Hadi Suharyanto I Dewa Gede Hari Wisana Indhana Sudiharto Indra Ferdiansyah Intan Sholikha Jaya, Arma Jaya, Arma Kadek Reda Setiawan Suda Karisma Trinanda Putra, Karisma Trinanda Lucky Pradigta S.R. Makoto Chiba Margo P Mauridhi Heri Purnomo Mauridhi Heri Purnomo Mauridhi Hery Purnomo Mentari Putri Jati MOCHAMAD ARI BAGUS NUGROHO Mohammad Ashary Mohammad Ashary, Mohammad Mohammad Jauhari Mr. Sukamto Muhamad Milchan Muhammad Aditya Ardiansyah Muhammad Irfan Zaidan Muhammad Wahyudi Muna, M. Faza Zidnal Nibras Syarif Ramadhan Novie Ayub Windarko Novrian Eka Sandhi Nugroho, Syechu Dwitya Nur Yanti, Nur Nurwahidah Jamal Pradana, Aditya Ilham Pradigta S.R., Lucky Praharsena, Bayu Praharsena, Bayu Putu Agus Mahadi Putra Qudsi, Ony Asrarul R. Akbar Nur Apriyanto R. Akbar Nur Apriyanto R. Akbar Nur Apriyanto R. Oktav Yama Hendra Raden Akbar Nur Apriyanto Ramadhan, Nibras Syarif Ramdani, Dicky Rivaldo Renny Rakhmawati, Safira Nur Hanifah, Renny Rakhmawati, Ridwan Ridwan Ridwan W.K. Rifqi Dary Suryanto Rochmana, Ade Rochmanu, Ade Rusli, Muhammad Rizani Safa Aulia Zerlina Saputra, Gilang Rizki SATO Yukihiko Septi Y., Diah Setiawan Suda, Kadek Reda Sindu Muhammad Imam Taufik Singgih Agustian Siswoyo, Charis Faridchie Soebagio Soebagio Sri Muntiah Andriami Subagio subagio Subagio Subagio Subagio Subagio, Subagio Suda, Kadek Reda Setiawan Sulis Wanto sutedjo Sutedjo Sutedjo Sutedjo Syahwir, Irawati Dewi Syamsul Arifin Syamsul Rohman Syechu Dwitya Nugraha Syechu Dwitya Nugroho Taufik, Sindu Muhammad Imam Taufiqurrahman Taufiqurrahman Utomo, Bedjo Wanto, Sulis Waras, Nandang Gunawan Tungga Wardhana, Dimas Aditya Putra Wildan Maulana Akbar Wishnuprakasa, Ardhia Wishnuprakasa, Ardhia wk, Ridwan wk, Ridwan Yeheskiel Rante Payung Yunanto, Bagus Yunanto, Prasetyo Wibowo Zahro Zachari Zerlina, Safa Aulia