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JAREE (Journal on Advanced Research in Electrical Engineering)
Published by Institut Teknologi Sepuluh Nopember Surabaya
ISSN : -     EISSN : 25796216     DOI : https://doi.org/10.12962/j25796216.v4.i2.116
Core Subject : Engineering,
Control & Systems Engineering Electrical & Electronics Engineering
JAREE is an Open Access Journal published by the Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember (ITS), Surabaya – Indonesia. Published twice a year every April and October, JAREE welcomes research papers with topics including power and energy systems, telecommunications and signal processing, electronics, biomedical engineering, control systems engineering, as well as computing and information technology.
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 175 Documents
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Design And Simulation Of 10 kW BLDC Motor Speed Control For Electric Vehicles Using FOC Based On Fuzzy Logic Control Rizqulloh, Mochamad Shofwan; Pamuji, Feby Agung; Suryoatmojo, Heri
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 8, No 1 (2024): January
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v8i1.386

Abstract

The use of electric vehicles in the current era has begun to spread evenly. Apart from the issue of air pollution produced by ICE vehicles, the ease and practicality of using electric vehicles is the reason why the public is starting to become interested in electric vehicles. Electric vehicle manufacturers are currently choosing BLDC motors for their production vehicles because they are considered suitable for applications that require high power and torque output. However, BLDC motors require more complicated control techniques than other DC motors. The commonly used BLDC motor speed control methods are trapezoidal scalar control and field oriented control. FOC is a type of BLDC motor control with a vector control method which has advantages in terms of efficiency compared to scalar control methods. Many studies on implementing FOC as speed control for BLDC motors, but the research that has been carried out still uses PI control as a basis, where it is known that PI control has shortcomings in the form of complexity in its design. Fuzzy Logic Control is known to be easy to design and reliable in control, so this paper will show the performance of Fuzzy-PI based FOC control as speed control for 10kW BLDC motor in simulation using Simulink program. The simulation results of proposed Fuzzy-PI based FOC method have better response than PI based FOC in terms of starting response with 6.43 times faster rise time, 2.45 times faster settling time, 96.31% lower overshoot value and reliability in overcoming disturbances up to 78.05% lower overshoot value and 2.33 times faster recovery time.
Analysis of Breakdown Characteristics in Nanofluid Insulation Materials with Metal Particle Contamination Mubarok, Abdul Fattah; Asfani, Dimas Anton; Negara, I Made Yulistya; Fahmi, Daniar; Subekti, Hakim
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 8, No 2 (2024): July
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v8i2.408

Abstract

Optimal insulation in transformers is essential to maintain their performance and reliability. However, insulation-related problems, particularly transformer oil contamination, often result in premature transformer failure. To address this issue, a solution has been proposed in the form of a nanofluid, a mixture of transformer oil, and nanoparticles. This study aims to investigate the impact of metal particle contamination on the breakdown and levitation voltage characteristics of nanofluids as liquid insulating materials. The nanofluids were prepared by mixing mineral oil with Fe3O4 nanoparticles at three different concentrations. Tests were conducted to evaluate the AC breakdown and levitation voltages for various contaminant metal particle sizes. The experimental results demonstrate that contaminant particle size has a significant impact on the breakdown voltage. The nanofluid with a concentration of 0.008% Fe3O4 exhibited superior breakdown voltage performance compared to mineral oil and 0.016% Fe3O4 nanofluid. Furthermore, an increase in the levitation stress was observed as the contaminant particle size increased. The findings of this study emphasize the importance of controlling contamination and selecting the appropriate concentration of nanoparticles to enhance transformer insulation performance. This study also highlights the necessity of monitoring the size of contaminant particles to prevent potential damage. Consequently, this study makes a significant contribution to the advancement of more reliable and efficient transformer insulation technology.
An Autoregressive Model of Electromagnetic Disturbances in An Autonomous Electric Vehicle’s Route Trihatmo, Sardjono; Hendrantoro, Gamantyo; Septiawan, Reza; Setijadi, Eko; Rufiyanto, Arief
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 8, No 1 (2024): January
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v8i1.387

Abstract

Electromagnetic Interference (EMI) can cause a malfunction of on-board electronic circuits in an autonomous electric vehicle and supporting electronic devices located in the environment of autonomous electric vehicles as well. In order to navigate an autonomous electric vehicle safely, it is important to have electromagnetic field characteristic in the environment. Since the information of electromagnetic field characteristic is hard to find, it needs to be modeled. This paper presents a model of electromagnetic field characteristic that is generated by using autoregression in order to estimate potential EMI. The EMI estimation is based on electromagnetic characteristic in an environment. Unlike other applications that use time history of data to build a model, we present a spatial electromagnetic field strength data in a previous route to estimate the future data in a new route. To obtain historical data for auto-regression process, we measured electric field strengths along a circular route in a campus near Jakarta. This surrounding environment represents a typical area of suburbs. The input variables for auto-regression process are the first 27 correlated data of 155 measured data. The result shows that the use of 13 predictor coefficient produces a variance of prediction error near to zero, with an improvement from maximum prediction error of 15.1257 to prediction error of 0.1862.
Azimuth Angle and Magnetic Declination to Maximize Solar Panel Efficiency (Solar Tracking System) Saeed, Zubair; Shahzad, Waseem; Ur Rehman, Asad; Ali, Syeda Zuriat e Zehra; Zaman, Shah; Shehzad, Faheem
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 8, No 1 (2024): January
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v8i1.357

Abstract

This study presents the idea of power production through the solar which depends on the light intensity that falls on the solar panel. This project utilizes dual axis solar tracking system based on intensity of light using Arduino UNO. The hardware implementation includes an Arduino UNO and four LDR sensor for sensing the maximum intensity of light. Two DC motors are used, one motor is used for horizontal rotation and the second motor is used for the vertical rotation. This system includes the implementation of MPPT. It controls the charge and stores it in a battery. Battery provides 12V to inverter where DC voltages convert into AC voltages. SPWM inverter is designed over push pull topology. In conclusion, the proposed system operates on low input power and delivers high efficiency in output.
Controlling a Quadcopter with Static Loads and Dynamic Wind Disturbances using a Fuzzy Inference System Azka, Aida; Santoso, Ari; Agustinah, Trihastuti
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 8, No 2 (2024): July
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v8i2.410

Abstract

Maneuverability, hover, and simple mechanical design are the advantages of quadcopters. However, because quadcopters are smaller and lighter, they are more susceptible to wind than manned aircraft. The winds that cause air accidents are divided into several categories, namely downburst, turbulent wind, wind shear, and wind vortices. Disturbances and uncertainties, such as wind gusts, can result in difficulties in executing a mission on an accurate flight path. Quadcopter resilience is an important topic for UAV. Especially if the quadcopter is in terrain that is difficult for humans to reach. Hence, the system is susceptible and experiences reduced stability. Controlling a quadcopter with a cube-shaped static load to withstand turbulent wind gusts in this research uses robust Fuzzy Inference System control and trajectory control using LQR with Command-Generator Tracking. The results achieved through fuzzy control can fortify the quadcopter against half of the overall turbulent wind gusts with an RMSE of 0.0546. In contrast with the LQR-CGT control, which still exhibits an RMSE of 0.0795.
Depth Image Assisted Aiming for Scoring Goal in Wheeled Soccer Robot Kusuma, Hendra; Samhan, Dzulfikar Ahmad; Tasripan, Tasripan; Dikairono, Rudy
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 8, No 2 (2024): July
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v8i2.268

Abstract

Wheeled soccer robot, as an automatic robot, required to have an advanced decision making system based on information it grasp from its surrounding. One of the most crucial decision making ability is to determine aiming angle when it is scoring goal.This research will enhance the aiming ability for scoring goal by predicting unguarded area of goal. Combination of depth image and RGB image information will be used to predict the position of unguarded space in goal. This position will be converted into aiming angle for the robot. Intel Realsense D435i depth camera will be used to get RGB and depth image simultaneouslyBy using this method, the system is capable to predict unguarded area in all of 60 test points, with 1.3% average error for the predicted coordinate.
Tracking Socer Player Based on Deepsort Algorithm with YOLOV8 FrameWork Khabibullah, Zein Bilal; Yuniarno, Dr. Eko Mulyanto; Rachmadi, Reza Fuad
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 9, No 1 (2025): January
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v9i1.413

Abstract

Abstract—Tracking is a set procedure that entails assigninganidentificationtoacertainobjectandsubsequentlycon-sistently recognizing that object without altering the assignedidentification over a sequence of frame images and associatingitaccordingly.Whenperformingresearchonobjecttracking,especially in sports where the object of interest is a human, aresilient technology is necessary to facilitate the tracking process.When the state-of-the-art object detection approach, YOLOV8,is combined with the DeepSORT algorithm, it is anticipated toproduce highly accurate and exact outcomes in the trackingand detection of objects. Challenges in multi-object trackinginclude robustness, oculusion, and identity shifts. In our research,we take advantage of a fusion of YOLOV8 and DeepSORTalgorithmstoachieveahighlyreliableandprecisetrackingsolution. The implementation of the Kalman filter-based motionprediction in DeepSORT allows for the achievement of smoothtrajectories, whereas the YOLOV8 deep neural network usedassists in precisely recognizing the appearance of objects on thefield. The result of our experiment shown the tracking we get is38% HOTA, 47% DetA, 31% AssA, 68% DetPre, 35% AssRE,61% AssPr amd 79% LOcA.Index Terms—Tracking, DeepSORT, YOLO, MOT, Socce
Design Battery Charger With CC-CV Method for Series Connected Lithium-Ion Batteries Using Fuzzy Logic Controller Sutedjo, Sutedjo; Rakhmawati, Renny; Putih, Bening Putri Permata; Adila, Ahmad Firyal; Irianto, Irianto; Yanaratri, Diah Septi
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 9, No 1 (2025): January
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v9i1.389

Abstract

Considering the many human needs, the existence of solar energy is considered very appropriate to help meet the energy needs consumed by humans. All the energy produced by solar panels can be stored using batteries which can then be converted into electrical energy. The battery will work when the energy stored in the battery is fulfilled, but if the use of the battery is carried out continuously it causes the energy in the battery to run out, so that the battery energy must be recharged immediately so that it can still be used again. charging which is used to recharge battery energy at this time unfortunately it still takes quite a long time to be recharged. Through the description of the problem, so that in study this is a tool fast charging use buck converter by using the method (Constant Current) CC-CV (Constant Voltage) on a Lithium-Ion battery. Buck converter This is necessary because the source used in this study is a solar panel which produces a very high voltage, so the voltage needs to be lowered by using buck converter. Using a 11.1V / 2.2 Ah LithiumIon battery. To keep the current and voltage constant, the charging process is carried out charging this current and voltage the output will be stabilized by Fuzzy Logic Controller (FLC). From the simulation results that have been carried out, it appears that the FLC has been able to stabilize the charging current of 2.2Ah and 11.1V.
Reducing Operational Costs in Sulselbar’s 150 kV System with Electromagnetic Field and Sine-Cosine Optimization Ikhsan, Rifki Rahman Nur; Marsuki, Aminah Indahsari; Wijaya, I Gede Putu Oka Indra
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 9, No 1 (2025): January
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v9i1.458

Abstract

Dynamic economic dispatch (DED) is a crucial task in modern power systems, requiring efficient optimization to minimize generation costs while satisfying operational constraints. This study introduces a Hybrid Electromagnetic Field Optimization with Sine-Cosine Algorithm (EMFO-SCA) tailored to address the unique challenges of the Sulselbar 150 kV power system. Specifically, the algorithm is designed to handle non-linear cost functions, complex constraints, and dynamic load variations across a 24-hour scheduling period. EMFO-SCA achieves a balanced integration of global exploration (via Electromagnetic Field Optimization) and local exploitation (via the Sine-Cosine Algorithm), resulting in robust optimization performance. Applied to a system with seven active generator buses, EMFO-SCA demonstrates an average operational cost reduction of 0.27% compared to the Kho-Kho Algorithm (KKA). This improvement translates to measurable cost savings while maintaining strict adherence to generation limits, ramp rate constraints, and power balance at all intervals. For instance, during peak demand at 521.52 MW (hour 12), the method effectively minimizes costs without compromising operational reliability. The dual-phase design of EMFO-SCA enables faster convergence and higher accuracy than conventional methods, making it a scalable solution for real-world DED challenges. By optimizing power generation schedules dynamically and reliably, this study establishes EMFO-SCA as a significant advancement in energy system optimization, with clear potential for practical deployment in similar power systems.
Smart Microgrid : Power Monitoring And Management System With Self-Healing Ability Dintika, Arief Fajariandi; Penangsang, Ontoseno; Aryani, Ni Ketut
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 9, No 1 (2025): January
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v9i1.427

Abstract

This research presents a smart microgrid power monitoring and management system with self-healing ability. Solar power plants have been integrated into the microgrid, which previously relied on DG and PLN power supply. However, the system’s monitoring and control are limited. This study develops an effective, efficient and reliable smart microgrid using integration of online monitoring and control system, power management system and self-healing ability. Online monitoring and control system is effectively to monitor and control the microgrid, can detect and analyze potential fault on grid at ease. Power management system is necessary to enhance efficiency and reliability to optimize power distribution. Then, with self-healing ability, enable to detect, to prevent, to isolate and to recover fault on grid automatically, make the smart microgrids more efficient and reliable. Through the Siemens TIA Portal, the study compared the simulation results of a conventional microgrid system with a smart microgrid system incorporate with online monitoring and control system, power management system, self-healing ability. Using some fault scenarios, MTTD value, MTTR value and Availability Rate value are obtained. As result, the applied smart microgrid system decrease the duration to detect and to recover fault on microgrid efficiently, thus the reliability also increased significantly.

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