cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
-
Editorial Address
-
Location
Kota yogyakarta,
Daerah istimewa yogyakarta
INDONESIA
Bulletin of Electrical Engineering and Informatics
Published by Universitas Ahmad Dahlan
ISSN : -     EISSN : -     DOI : -
Core Subject : Engineering,
Electrical & Electronics Engineering
Bulletin of Electrical Engineering and Informatics (Buletin Teknik Elektro dan Informatika) ISSN: 2089-3191, e-ISSN: 2302-9285 is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world. The journal publishes original papers in the field of electrical, computer and informatics engineering.
Arjuna Subject : -
Articles 75 Documents
 1   2   3   4   5 
Search results for , issue "Vol 14, No 6: December 2025" : 75 Documents clear
Beyond a simple filter: transient and steady state analysis of first-order resistor-resistor-capacitor circuits Djelaila, Soumia; Abderrazak Tadjeddine, Ali; Ilyas Bendjillali, Ridha; Sofiane Bendelhoum, Mohammed
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.10166

Abstract

This paper presents a quantitative analysis of a first-order resistor-resistor-capacitor (RRC) circuit, detailing its transient, steady state, and frequency-domain behaviors through computational modeling. The study confirms that the circuit's time constant (τ) governs its dynamic response, with the capacitor charging to 63.2% of its final voltage in one τ. The key finding is the circuit's fundamental distinction from a simple resistor-capacitor (RC) filter: under a 100 V step excitation, the RRC topology stabilizes with a non-zero steady-state current of 0.35 A, following a controlled transient inrush of 1.0 A. Frequency analysis further characterizes the circuit as a stable low-pass filter with a predictable -20 dB/decade roll-off. This work elucidates a critical engineering trade-off, demonstrating that the RRC's components dually define its transient speed and its final steady state operating point, providing a quantitative framework for advanced power management and signal conditioning applications.
Application of traction force observer and sliding mode controller for speed in enhancing the stability of electric vehicles Thi Hoai Thu Anh, An; Van Hoa, Nguyen
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.9653

Abstract

With the rapid advancement of electric vehicle (EV) technology, optimizing control and stability has become a key research focus. One major challenge is efficiently distributing traction force while minimizing disturbances under real-world conditions. This paper proposes a traction force observation method combined with a sliding mode speed controller to enhance EV performance. The observation method estimates the traction force from the motor to the wheels and detects disturbances affecting force transmission. This enables optimal traction force distribution among the wheels, reducing slip, improving road grip, and enhancing stability in complex driving conditions. Meanwhile, the sliding mode controller flexibly adjusts traction force as the vehicle navigates various terrains, ensuring stability and safety in hazardous situations. Simulations conducted using MATLAB Simulink and CarSim demonstrate that the proposed system significantly improves EV stability and control performance. Although these results are promising, further studies are necessary to address real-world implementation challenges and optimize the method for practical applications, including parameter tuning, sensor integration, and experimental validation. Overall, this research provides a practical framework for enhancing traction control and vehicle dynamics in future intelligent electric mobility systems.
Improvement of load frequency control performance for shipboard microgrid system Nguyen, Cong-Trang; Nghia Tin, Nguyen; Pham Thien Hao, Thai; Tan Liem, Phan
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.9920

Abstract

This research studies the shipboard microgrid (MG) scheme's frequency fluctuations problem contrary to the impulsiveness of renewable resources, load instabilities, and the uncertainty of the parameters in the ship MG plant. A shipboard MG system consists of some of the renewable energy resource s (RESs) such as photovoltaic (PV), wind turbine generator (WTG), battery energy storage system (BESS), ship diesel generator (DG), fuel cell (FC), aqua electrolyzer (AE), and loads. A new fuzzy proportional integral derivative (FPID) controller is established to attain the desired frequency stability for the shipboard MG system. Additionally, various scenarios are executed in this research to validate the robustness of the anticipated controller to various load disturbances, parameter changes of plant, and fluctuations of solar irradiance and wind speed. The numerical simulation results obtained in three scenarios compared with those of the conventional PID controller and the existing time-varying derivative fractional order PID (TVD-FOPID) controller in literatures to validate the high usefulness and applicability of the planned control strategy. In brief, the established load frequency controller (LFC) based on FPID technique can improve frequency deviation in shipboard MG plant effectively.
A high-efficiency transformerless buck-boost inverter with fuzzy logic control for grid-connected solar PV systems Venkata Rajanna, Bodapati; Rama Krishnaiah, Kondragunta; Ramaiah, Veerlapati; Ahammad, Shaik Hasane; Najumunnisa, Mohammad; Inthiyaz, Syed; Rao Kolukula, Nitalaksheswara; Sudhakar, Ambarapu
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.10752

Abstract

Transformerless inverters are increasingly favored in grid-connected photovoltaic (PV) systems due to their higher efficiency, reduced size, and lower cost. This paper presents a novel transformerless inverter topology that integrates buck boost conversion with an advanced fuzzy logic controller (FLC) to enhance energy extraction and power quality under dynamically changing solar conditions. The proposed system employs a sine triangle pulse width modulation (PWM) scheme in conjunction with the FLC to improve waveform quality and system responsiveness. By dynamically adapting to variations in irradiance and load, the control strategy reduces the total harmonic distortion (THD) from 36.51% to 1.51%, significantly enhancing compliance with international grid standards. Additionally, a novel grounding technique is implemented to mitigate common mode leakage currents, a typical issue in transformerless systems, without the need for galvanic isolation. Comprehensive MATLAB/Simulink simulations validate the inverter’s performance, demonstrating superior dynamic behavior, harmonic suppression, and overall reliability. The proposed architecture offers a compact, cost effective, and high performance solution for next generation grid integrated solar PV systems.
Path planning and obstacle avoidance for UAVs using Theta* and modulated velocity obstacle avoidance with 2D LiDAR Tran, Hoang Thuan; Tran, Dong LT.; Vo, Chi Thanh
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.10594

Abstract

This paper proposes a novel framework for autonomous unmanned aerial vehicle (UAV) navigation in complex environments, seamlessly integrating Theta* for global path planning with a simplified modulated velocity obstacle avoidance (MVOA) algorithm for local obstacle avoidance. Theta* generates optimal, smooth paths, while MVOA processes 2D LiDAR data as a single obstacle block to compute modulated velocities, enabling efficient avoidance of static and dynamic obstacles with minimal computational overhead. Compared to MVOA-only navigation, the integration of Theta* and MVOA produced shorter trajectories and faster mission completion with smoother velocity adjustments, demonstrating clear improvements in efficiency and stability. Simulation results show the framework maintains a 0.6 m safety distance and operates at 10 Hz, underscoring its robustness and reliability. The resulting control velocity is transmitted to an ArduPilot-based flight controller via MAVLink, ensuring precise, real-time execution. The current implementation focuses on 2D navigation in a planar environment as a foundation for future 3D expansion, with all results obtained through high-fidelity simulation. Building on these findings, the framework shows strong potential for real-time applications such as swarm UAV coordination, terrain surveying, and indoor navigation, offering a scalable solution for autonomous systems in dynamic settings.
Mapping global research trends in power quality for industrial electrical systems: a bibliometric analysis (2016–2024) Noriega Angarita, Eliana; Sousa Santos, Vladimir; D. Donolo, Pablo; Solorio Aguila, Edgar; Garcia Garcia, Endy; Hernandez Tomas, Johan; Garduno Leon, Victor; Rivera Ramos, Jose
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.10700

Abstract

This paper analyzes trends in electrical power quality (PQ) in industrial systems through a bibliometric approach to identify key topics, prominent authors, and patterns of international collaboration that may guide future research. PQ disturbances can significantly affect operational continuity, energy efficiency, and equipment lifespan in industrial electrical systems (IES), making it essential to map the research landscape to support technological and strategic responses. The study reviews 103 articles from the Scopus database for the period 2016–2024, applying relevance and currency criteria. VOSviewer® was used to conduct the analysis, employing keyword co-occurrence networks and bibliographic coupling to visualize thematic, collaborative, and citation relationships. Results indicate a strong research focus on harmonic distortion, voltage disturbances, and artificial intelligence applications for diagnosis and mitigation. India leads in scientific production, while IEEE Access is the most influential source. Despite growing interest, the study identifies limited international collaboration and thematic fragmentation, which may hinder comprehensive solutions. The findings highlight the need to expand collaboration networks, standardize methodologies, and integrate underexplored topics into mainstream PQ studies, strengthening the ability of industrial systems to address emerging challenges and improve performance, resilience, and reliability.
Evaluating random–Nyquist sampling ratios in combined compressed sensing magnetic resonance imaging Khanh Pham, Duc; Tran, Duc-Tan; Quang Tran, Anh
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.10333

Abstract

Compressed sensing (CS) has been widely applied in magnetic resonance imaging (MRI) to accelerate the image acquisition without significantly reducing its image quality. In Cartesian MRI, acquisition time can be reduced by skipping phase-encoding steps for faster data acquisition. However, the balance between random under-sampling and Nyquist sampling at the k-space center strongly determines image quality. In this study, we systematically evaluate the impact of different random-to-Nyquist sampling ratios for both single-coil (CS-MRI) and multi-coil (CS-pMRI) reconstructions. Simulation results reveal that dense Nyquist sampling around the k-space center is essential for maintaining image fidelity, whereas reconstruction quality deteriorates sharply when random sampling exceeds approximately 60% of the total under-sampled data. Moreover, CS-pMRI consistently outperforms CS-MRI under equivalent under-sampling factors, benefiting from additional coil sensitivity information that improves resilience against aliasing and noise. These findings provide practical guidelines for hybrid under-sampling design, emphasizing that sufficient Nyquist sampling coverage of central k-space is crucial for achieving high-quality reconstructions while enabling high acceleration in CS-MRI.
Machine learning based annual solar energy forecasting for enhanced grid integration of photovoltaic systems K. Krishnamurthy, Nandini; Kumar Pandey, Anubhav; Sreenivasa Rao, Sumana
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.10215

Abstract

The increase in electricity demand is witnessed by many nations due to the rise in population and ongoing developments. To cope with energy requirements, countries are looking towards cleaner alternatives to reduce overreliance on energy generation from conventional resources. The introduction of artificial intelligence (AI) in real-world applications is acknowledged positively by experts as it enhances the performance and efficiency of the system. This paper reports the advancement of AI in harnessing renewable energy sources (RESs) to their true potential by leveraging their response when the grid is not able to fulfill the power requirement from conventional resources. Moreover, the prediction also remains a challenge with renewables due to their volatile behavior, especially with solar-based energy generation. This issue is also addressed by interfacing AI-enabled applications and the difference between true and predicted values for one year is observed. The result reveals that the true response aligns with the predicted response, which ensures the ability of AI to harness solar energy by consuming minimal time. The proposed approach is also promising from the utility operators’ and end users’ perspectives in designing any large-scale renewable projects for sustainable development and also encourages the utilization of renewables to a larger extent.
Intelligent maximum power point tracking control for solar photovoltaic systems using fuzzy and neuro-fuzzy techniques Venugopal, Mohankumar; Mahadevaswamy, Madhusudhan; Bimbitha Swarna Gowri, Manjunath
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.10735

Abstract

A solar-photovoltaic (PV) system cannot optimize power transfer from the generator to the load due to the nonlinear characteristics of the PV arrays. Maximum power point tracking (MPPT) approaches are necessary to optimize the power output of PV arrays. This study introduces a dual intelligent MPPT framework using fuzzy-logic controller (FLC) and neuro-fuzzy controller (NFC) to enhance solar PV efficiency under dynamic environmental conditions. The FLC uses 49 fuzzy rules with seven membership functions (MFs) in a fuzzy interface system (FIS). The NFC is an extension of FLC and is constructed using the artificial neuro-fuzzy interface system (ANFIS). The work analyzes the simulation results and performance realization, including % power loss, system efficiency, and MPPT efficiency under variable irradiance and temperatures. The solar-PV system utilizes FLC and NFC to achieve MPPT efficiencies of 97.89% and 98.61%, respectively. Similarly, the solar-PV system employing FLC and NFC yields system efficiencies of 98.24% and 99.23% respectively. The proposed system using both FLC and NFC is compared with existing MPPT approaches, with better improvement in system efficiency.
MVC in machine learning: a decade of algorithmic advances, challenges, and applications–a systematic review Kumar, Pankaj; Agrawal, Rashmi
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.11137

Abstract

This systematic review evaluates the developments in multi-view clustering (MVC), its challenges, and applications from 2009 to 2024 and synthesizes 157 studies selected according to preferred reporting items for systematic reviews and meta-analyses (PRISMA) 2020 guidelines. MVC overcomes the shortcomings of the traditional single-view approaches by using complementary information provided by heterogeneous data sources. We used a strict search strategy in the ACM Digital Library, IEEE Xplore, and Scopus, and then carefully examined the quality of the found articles. The significant results suggest that the MVC research has grown explosively, with China as the major contributor and IEEE/Elsevier as the leading publishers. Developments in algorithms include deep learning, graph-based models, and factorization. Ongoing issues include managing incomplete views, scalability, successful fusion strategies, and interpretability. The review points out the wide range of applications of MVC in various areas, including bioinformatics, social network analysis, and multimedia. Future research must create adaptive frameworks, improve the interpretability of models, and develop strong evaluation measures, thus unlocking the full potential of MVC in real-life data applications.

Page 1 of 8 | Total Record : 75

 1   2   3   4   5 

Filter by Year

2025 2025


Reset
Filter By Issues
All Issue Vol 14, No 6: December 2025 Vol 14, No 5: October 2025 Vol 14, No 4: August 2025 Vol 14, No 3: June 2025 Vol 14, No 2: April 2025 Vol 14, No 1: February 2025 Vol 13, No 6: December 2024 Vol 13, No 5: October 2024 Vol 13, No 4: August 2024 Vol 13, No 3: June 2024 Vol 13, No 2: April 2024 Vol 13, No 1: February 2024 Vol 12, No 6: December 2023 Vol 12, No 5: October 2023 Vol 12, No 4: August 2023 Vol 12, No 3: June 2023 Vol 12, No 2: April 2023 Vol 12, No 1: February 2023 Vol 11, No 6: December 2022 Vol 11, No 5: October 2022 Vol 11, No 4: August 2022 Vol 11, No 3: June 2022 Vol 11, No 2: April 2022 Vol 11, No 1: February 2022 Vol 10, No 6: December 2021 Vol 10, No 5: October 2021 Vol 10, No 4: August 2021 Vol 10, No 3: June 2021 Vol 10, No 2: April 2021 Vol 10, No 1: February 2021 Vol 9, No 6: December 2020 Vol 9, No 5: October 2020 Vol 9, No 4: August 2020 Vol 9, No 3: June 2020 Vol 9, No 2: April 2020 Vol 9, No 1: February 2020 Vol 8, No 4: December 2019 Vol 8, No 3: September 2019 Vol 8, No 2: June 2019 Vol 8, No 1: March 2019 Vol 7, No 4: December 2018 Vol 7, No 3: September 2018 Vol 7, No 2: June 2018 Vol 7, No 1: March 2018 Vol 6, No 4: December 2017 Vol 6, No 3: September 2017 Vol 6, No 2: June 2017 Vol 6, No 1: March 2017 Vol 5, No 4: December 2016 Vol 5, No 3: September 2016 Vol 5, No 2: June 2016 Vol 5, No 1: March 2016 Vol 4, No 4: December 2015 Vol 4, No 3: September 2015 Vol 4, No 2: June 2015 Vol 4, No 1: March 2015 Vol 3, No 4: December 2014 Vol 3, No 3: September 2014 Vol 3, No 2: June 2014 Vol 3, No 1: March 2014 Vol 2, No 4: December 2013 Vol 2, No 3: September 2013 Vol 2, No 2: June 2013 Vol 2, No 1: March 2013 Vol 1, No 4: December 2012 Vol 1, No 3: September 2012 Vol 1, No 2: June 2012 Vol 1, No 1: March 2012 List of Accepted Papers (with minor revisions) More Issue