Article Per Year (5 Year)
p-Index From 2021 - 2026
1.836
P-Index
This Author published in this journals
All Journal Teknika: Jurnal Sains dan Teknologi Setrum : Sistem Kendali-Tenaga-elektronika-telekomunikasi-komputer ELINVO (Electronics, Informatics, and Vocational Education) CESS (Journal of Computer Engineering, System and Science) EMITTER International Journal of Engineering Technology Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Teknologi Elekterika Jurnal INOVTEKSeri Elektro Technologic Jurnal Nasional Teknik Elektro dan Teknologi Informasi J-Innovation Jurnal Rekayasa elektrika
Endro Wahjono
Departemen Teknik Elektro, Politeknik Elektronika Negeri Surabaya
Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering

Published : 18 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 18 Documents
Search

 1   2 
Implementasi Maximum Power Point Tracker Berbasis Fuzzy Logic Controller dengan Zeta Converter Afifuddin Rizqi; Sutedjo; Endro Wahjono
J-Innovation Vol. 10 No. 1 (2021): Jurnal J-Innovation
Publisher : Politeknik Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (715.102 KB) | DOI: 10.55600/jipa.v10i1.16

Abstract

Implementation of photovoltaics as a renewable energy source is growing rapidly. The cost of implementing photovoltaic is very high therefore it is necessary to control the optimization of the PV. The V-I aspect of solar cells is nonlinear, changing with the intensity of sunlight and the surface temperature of the photovoltaic, causing the output power of the photovoltaic to vary. This research will use the zeta converter as a DC chooper controlled by MPPT based on fuzzy logic controller. Software Power Simulation (PSIM) is used to simulate MPPT. The MPPT fuzzy logic controller will be compared with the MPPT human psychology optimization (HPO). The simulation results show that MPPT fuzzy gets the same accuracy as MPPT HPO and is better than the average accuracy without MPPT which is 99,98%. Then the speed in finding the maximum MPPT fuzzy point gets a better time tracking when compared to the MPPT HPO which is 0,0283 seconds. MPPT fuzzy is able to exceed the maximum power at varying sunlight intensity and temperature.
Sistem Baterai Cell Balancing Pasif Menggunakan Kontrol Logika Fuzzy Tipe Mamdani untuk Baterai Pack Lithium Moh Rifqi Faqih; Novie Ayub Windarko; Endro Wahjono
J-Innovation Vol. 10 No. 2 (2021): Jurnal J-Innovation
Publisher : Politeknik Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (486.215 KB) | DOI: 10.55600/jipa.v10i2.111

Abstract

Lithium-ion batteries have been widely used in energy storage for electric vehicle and hybrid vehicle applications. After several cycles of charging and discharging, there is one cell whose performance and capacity decreases, causing the performance and capacity of the battery pack to decrease so that it cannot work optimally. So it is necessary to design a cell voltage balancing system to minimize cell voltage imbalance in the charging process. Passive balancing is widely implemented because of its simplicity, reliability, and relatively low cost. The balancing process must be carried out as quickly as possible as the battery is charging, so a PWM ignition technique using mamdani fuzzy is needed to discharge an unbalanced battery cell. The result are compared with no balancing system, fixed balancing 50% duty cycle system, and sugeno fuzzy logic balancing system. From the simulation result, using mamdani fuzzy the final delta voltage value is 0.0344 volt, energy charged is 58.18 Wh and the final State of Charge is 74%. When compared with other balancing method, it shows that using mamdani fuzzy logic method is more optimal because the final of delta voltage value is very small and the battery capacity charged is larger than other method.
BLDC Motor Drives with A Programmable Simplified C-Block to Generate Accurate Six-Step PWM Based on STM32 Microcontroller Muhammad Rizani Rusli; Mentari Putri Jati; Mochamad Ari Bagus Nugroho; Ony Asrarul Qudsi; Indhana Sudiharto; Farid Dwi Murdianto; Endro Wahjono
Elinvo (Electronics, Informatics, and Vocational Education) Vol 7, No 2 (2022): November 2022
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1164.041 KB) | DOI: 10.21831/elinvo.v7i2.52992

Abstract

This paper presents a digital implementation of a brushless direct current motor (BLDCM) drive with a six-step pulse width modulation (PWM) using a programmable simplified C-block based on the STM32 microcontroller. The implementation is conducted through the PSIM simulation platform, which is commonly used for power electronics and motor control. This approach combines the benefits of using a programmable simplified C-block for precise and flexible programming with the PWM concepts of the STM32 microcontroller. The PWM method used on the BLDCM drive is the unipolar upper PWM technique (H~PWM_L~ON). The performance of the PWM implementation is analyzed in detail, including the accuracy of the PWM generation using a Fast Fourier Transform (FFT), the gating of the IGBTs in the three-phase inverter, and the effect of the duty cycle on the BLDCM's speed, phase voltage, and phase current. 
Pendeteksian Harmonisa Arus Berbasis Feed Forward Neural Network Secara Real Time Endro Wahjono; Dimas Okky Anggriawan; Achmad Luki Satriawan; Aji Akbar Firdaus; Eka Prasetyono; Indhana Sudiharto; Anang Tjahjono; Anang Budikarso
Jurnal Rekayasa Elektrika Vol 16, No 1 (2020)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (869.076 KB) | DOI: 10.17529/jre.v16i1.15093

Abstract

The development of power electronics converters has been widespread in the industrial, commercial, and home applications. The device is considered to produce harmonics in non-linear loads. Harmonics cause a decrease in power quality in the electric power system. To prevent a decrease in power quality caused by harmonics in the power system, the detection of harmonics has an important role. Therefore, this paper proposed feed forward neural network (FFNN) for harmonic detection. The design of harmonic detection device is designed with a feed forward neural network method that it has two stages of information processing, namely the training stage and the testing stage. FFNN has input harmonics and THDi as output. To detect harmonics, frst training is conducted to recognize waveform patterns and calculate the fast fourier transform (FFT) process offline. Prototype using the AMC1100DUB current sensor, microcontroller and display. To validate the proposed algorithm, compared by standard measurement tool and FFT. The results show the proposed algorithm has good performance with the average percentage error compared by standard measurement tool and FFT of 5.33 %.
Identification of Power Quality Disturbances Based on Fast Fourier Transform and Artificial Neural Network Dimas Okky Anggriawan; Endro Wahjono; Indhana Sudiharto; Anang Budikarso
Jurnal Rekayasa Elektrika Vol 19, No 1 (2023)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (911.405 KB) | DOI: 10.17529/jre.v19i1.27120

Abstract

This paper presents the proposed algorithms for the identification of Short Duration RMS Variations and Long Duration RMS Variations combined with harmonic. The proposed algorithms are Fast Fourier Transform (FFT) and Artificial Neural Network (ANN). The Algorithms identify nine types of Power Quality (PQ) disturbances such as normal signal, voltage sag, voltage swell, under voltage, over voltage, voltage sag combined harmonic, voltage swell combined harmonic, undervoltage combined harmonic, and over voltage combined harmonic. FFT is used to obtain the frequency spectrum of each PQ disturbance with frequency sampling of 1000 Hz, data length of 200. Output FFT is used to input data for ANN. Output ANN is a type of nine PQ disturbances. The result shows that proposed algorithms (FFT combined ANN) are effective for identification, which ANN with 20 neurons in the hidden layer has an accuracy of approximately 99.95 %
Identification of Power Quality Disturbances Based on Fast Fourier Transform and Artificial Neural Network Dimas Okky Anggriawan; Endro Wahjono; Indhana Sudiharto; Anang Budikarso
Jurnal Rekayasa Elektrika Vol 19, No 1 (2023)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v19i1.27120

Abstract

This paper presents the proposed algorithms for the identification of Short Duration RMS Variations and Long Duration RMS Variations combined with harmonic. The proposed algorithms are Fast Fourier Transform (FFT) and Artificial Neural Network (ANN). The Algorithms identify nine types of Power Quality (PQ) disturbances such as normal signal, voltage sag, voltage swell, under voltage, over voltage, voltage sag combined harmonic, voltage swell combined harmonic, undervoltage combined harmonic, and over voltage combined harmonic. FFT is used to obtain the frequency spectrum of each PQ disturbance with frequency sampling of 1000 Hz, data length of 200. Output FFT is used to input data for ANN. Output ANN is a type of nine PQ disturbances. The result shows that proposed algorithms (FFT combined ANN) are effective for identification, which ANN with 20 neurons in the hidden layer has an accuracy of approximately 99.95 %
Pendeteksian Harmonisa Arus Berbasis Feed Forward Neural Network Secara Real Time Endro Wahjono; Dimas Okky Anggriawan; Achmad Luki Satriawan; Aji Akbar Firdaus; Eka Prasetyono; Indhana Sudiharto; Anang Tjahjono; Anang Budikarso
Jurnal Rekayasa Elektrika Vol 16, No 1 (2020)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v16i1.15093

Abstract

The development of power electronics converters has been widespread in the industrial, commercial, and home applications. The device is considered to produce harmonics in non-linear loads. Harmonics cause a decrease in power quality in the electric power system. To prevent a decrease in power quality caused by harmonics in the power system, the detection of harmonics has an important role. Therefore, this paper proposed feed forward neural network (FFNN) for harmonic detection. The design of harmonic detection device is designed with a feed forward neural network method that it has two stages of information processing, namely the training stage and the testing stage. FFNN has input harmonics and THDi as output. To detect harmonics, frst training is conducted to recognize waveform patterns and calculate the fast fourier transform (FFT) process offline. Prototype using the AMC1100DUB current sensor, microcontroller and display. To validate the proposed algorithm, compared by standard measurement tool and FFT. The results show the proposed algorithm has good performance with the average percentage error compared by standard measurement tool and FFT of 5.33 %.
Desain dan Impelementasi Multilevel Inverter Tiga Tingkat Untuk Mereduksi Harmonisa Bagus Afif Nasrudin; Sutedjo Sutedjo; Endro Wahjono
Setrum : Sistem Kendali-Tenaga-elektronika-telekomunikasi-komputer Vol 12, No 2 (2023): Edisi Desember 2023
Publisher : Fakultas Teknik Elektro - Universitas Sultan Ageng Tirtayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36055/setrum.v12i2.16638

Abstract

Suplai kualitas daya listrik yang baik merupakan elemen yang sangat dibutuhkan bagi peralatan listrik. Umumnya inverter konvensional menghasilkan THD tegangan dan arus yang cukup tinggi yang mana berpengaruh pada meningkatnya rugi-rugi akibat harmonisa sehingga efisiensi yang dihasilkan semakin turun. Oleh karena itu diusulkan sebuah sistem terdiri dari baterai sebagai sumber dc yang digunakan untuk mensuplai multilevel inverter yang merupakan salah satu jenis inverter yang memiliki bentuk gelombang tegangan maupun arus yang bertingkat. Multilevel inverter dimodulasi dengan metode Alternate Phase Opposition Disposition (APOD-PWM) yang mana teknik modulasi ini membutuhkan masing-masing dari empat bentuk sinyal pembawa untuk bentuk gelombang keluaran inverter tiga tingkat dengan masing-masing sinyal pembawa digeser fasanya sebesar 120˚ dari sinyal yang berdekatan secara bergantian. Dari data hasil pengujian, multilevel inverter 3 tingkat dapat mengubah 36 VDC  menjadi 15.6 Vrms AC yang kemudian dinaikkan tegangannya oleh trafo step-up menjadi 215 Vrms AC dengan persentase error 2.2%. Keluaran dari multilevel inverter tiga tingkat setelah melalui filter dengan beban lampu pijar 400 Watt menghasilkan THD tegangan sebesar 7,4% dan THD arus sebesar 7.6%.
Co-Authors Abdul Rahman Wachid Achmad Luki Satriawan Ade Rochmanu Afifuddin Rizqi Afifuddin Rizqi Aidin Amsyar Anang Budikarso Anang Tjahjono, Anang Bagus Afif Nasrudin Dimas Okky Anggriawan Eka Prasetyono, Eka Era Purwanto Farid Dwi Murdianto Firdaus, Aji Akbar Indhana Sudiharto Irianto Irianto Lugiana Nur Fitriah Rhamadani Lugiana Mentari Putri Jati MOCHAMAD ARI BAGUS NUGROHO Moh Rifqi Faqih Muhammad Nur Sururi Novie Ayub Windarko Ony Asrarul Qudsi Qudsi, Ony Asrarul Rifadil, Mochammad Machmud Rusli, Muhammad Rizani Sutedjo sutedjo Sutedjo Syechu Dwitya Nugraha Teguh Tri Arvianto Vania Kurnia Alvi