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Journal : Jurnal EECCIS

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One Pulse Vector Control Inverter Control Design for Fast Train Traction Motor Torque Control Pramudita Pamungkas; Mochammad Rusli; Wijono
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 18 No. 2 (2024)
Publisher : Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jeeccis.v18i2.1712

Abstract

Current technology is increasingly developing, one of which is inverter control for high-speed train traction motor drives. Currently, the train driver is an AC electric motor. Inverters typically operate in the high-speed region. In this paper, it aims to drive the speed rotation of a 3-phase AC motor. The inverter is used to control the rotational speed of the motor, the vector control provides control of the speed and torque of the motor load for the 3 phase ac motor running at high speed. The vector control design is with the Arduino microcontroller program. The design of the inverter is in the form of a module that contains several components, namely IC drivers, resistors, mosfets, capacitors. The results of the PWM inverter were obtained in a waveform with a voltage of 4.72 volts, a frequency of 224.0 Hz and a duty cycle of 33.3%. The results of this study show the variation of the rotational speed of the motorcycle, the rotational speed of the motor with a value of 360 RPM the load torque response shows a value of 72.8 Nm, to the rotational speed of the motor of 960 RPM, the load torque response shows a value of 19.6 Nm. Based on the results of the inverter control research on motor torque control with the vector control method, the load torque response is able to follow the variation in the speed of rotation of the motor. The higher the rotational speed of the motorcycle, the lower the load torque respons.
Analysis on Leakage Inductance and Winding Resistance of High Frequency Toroidal Transformer with Interleaved Winding and Litz Wire Siregar, Dody Yunus Putra; Wijono; Muhammad Aziz Muslim
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 18 No. 3 (2024)
Publisher : Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jeeccis.v18i3.1752

Abstract

High-frequency transformers offered numerous advantages but also presented several challenges. As frequency increased, the dimensions of the transformer decreased, making parasitic parameters more dominant and unavoidable. Leakage inductance disrupted the converter circuit by storing energy that impacted the switching devices. Additionally, increased winding resistance contributed to higher winding losses, resulting in decreased transformer efficiency. This paper proposed the use of interleaved winding and litz wire as solutions to reduce parasitic parameters, such as leakage inductance and winding resistance, in toroidal transformers. Analysis and verification were conducted using 3D finite element analysis (FEA) simulations. The results demonstrated that interleaved winding significantly reduced leakage inductance by up to 98.9% as frequency increased. The distribution of leakage magnetic fields in conventional windings was effectively minimized by altering the winding arrangement. Furthermore, winding resistance was notably reduced when using litz wire, leading to a more even distribution of current density across the conductor plane, which equivalently reduced the skin effect.
Analysis of Rotor-Side Control and Grid-Side Controls for Grid Voltage Improvement in a DFIG-Based Wind Turbine System Alsabah, Mus Ali; Rini Nur Hasanah; Wijono; Corina Martineac
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 17 No. 2 (2023)
Publisher : Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jeeccis.v17i2.1651

Abstract

Wind Power Plant (PLTB) has received a lot of attention from the public, researchers, and the government because of its advantages and role in reducing the causes of environmental damage due to the generation of electrical energy. Unlike power plants that use primary energy from fossil fuels, PLTB uses wind kinetic energy to generate electricity. Many problems arise because the wind speed is always changing every time. The resulting output voltage instability in the generator can affect the electric power system where the output electricity of the generator is injected. This paper describes how to analyze the generator output voltage control at PLTB. The generator used is a type of induction generator with two inputs (Double-Fed Induction Generator, DFIG). while the method of analysis is carried out using the PSIM simulation tool from Powersim, Inc. Control is carried out both on the rotor side (Rotor Side Converter, RSC) and on the grid side (Grid Side Converter), with the aim of maintaining the output voltage injected into the power grid with a certain level of voltage oscillation. The control results show that the generator output voltage can be maintained as desired.
DE-Optimized Hybrid ARIMA-LSTM for Long Term Electricity Load Forecasting Mardotillah, Nanda Azizah; Hasanah, Rini Nur; Wijono
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 19 No. 2 (2025)
Publisher : Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jeeccis.v19i2.1813

Abstract

Accurate long-term electricity load forecasting was essential for efficient energy planning and infrastructure development. This study addressed forecasting challenges in rapidly growing regions, such as East Java, where electricity demand was influenced by both linear and non-linear patterns. Conventional forecasting models, such as the Autoregressive Integrated Moving Average (ARIMA) effectively captured linear trends but failed to model non-linear dynamics, whereas networks with Long Short-Term Memory (LSTM) excelled with non-linear data but were often less effective when used alone. This research developed and evaluated an ARIMA-LSTM hybrid model optimized with the Differential Evolution (DE) algorithm to forecast electricity load until 2026. The model was trained and validated using historical daily load data from 2021 to 2023 from PT PLN UP2B East Java. This hybrid methodology first used ARIMA to model the linear components of the time series. The resulting residual errors, which contained non-linear patterns, were then modeled using an LSTM network. The DE algorithm was used to automatically optimize hyperparameters for both the ARIMA (p, d, q) and LSTM (units, learning rate, drop out etc.) components. The suggested hybrid model's performance was contrasted with that of the independent LSTM and ARIMA models. The results showed that the DE-optimized hybrid model achieved higher accuracy, yielding a Mean Absolute Percentage Error (MAPE) of 3.97 %, which was significantly better than the ARIMA model (12.39 % MAPE) and the LSTM model (4.50 % MAPE) on the validation set. According to these results, the suggested hybrid model was a dependable and extremely accurate instrument for predicting long-term loads, offering a solid basis for strategic energy planning.
Co-Authors Alsabah, Mus Ali Corina Martineac Dary Rafi Brafianto Dio Alif Airlangga Daulay Donny Ardi Kusuma Hadi Suyono Mardotillah, Nanda Azizah Mochammad Rusli Muhammad Aziz Muslim Muhammad Iqbal Muhammad Kharis Fajar Nurwati, Tri Pramudita Pamungkas Rini Nur Hasanah Rizky Muhammad Sidik Siregar, Dody Yunus Putra Tri Setyo Utami Tutur Jatmiko Waru Djuriatno. Yusril Amir Abdullah Hakim,