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29,922 Article Results

Fuzzy logic controller-based protection of direct current bus using solid-state direct current breaker

10.11591/ijaas.v14.i3.pp859-868
Eswaraiah Giddalur , Askani Jaya Laxmi
Low-voltage direct current (LVDC) microgrids are increasingly utilized due to their efficiency and compatibility with distributed energy resources (DERs) and direct current (DC) loads, eliminating the need for multiple energy conversions. However, the protection of LVDC systems presents significant challenges, including high fault currents and the vulnerability of electronic devices. Traditional electromechanical circuit breakers are inadequate due to their slow response times. This work presents a protection approach for the DC bus in LVDC microgrids that combines a fuzzy logic controller (FLC) with a solid-state circuit breaker (SSCB). The FLC is designed to detect and respond to faults rapidly by processing input variables such as current magnitude and rate of change of current. The FLC controls the SSCB, which interrupts fault currents quickly and reliably. The proposed system demonstrates optimized fault-clearing times within milliseconds, significantly enhancing the protection and reliability of LVDC microgrids. This novel solution protects critical electronic components while also ensuring the microgrid's operational integrity. The FLC approach is utilized for optimizing fault-clearing duration within milliseconds.
Volume: 14
Issue: 3
Page: 859-868
Publish at: 2025-09-01

Synchronous generator system identification via dynamic simulation using PSS/E: Malaysian case

10.11591/ijpeds.v16.i3.pp1658-1672
Saleh Baswaimi , Renuga Verayiah , Tan Yi Xu , Nagaraja Rupan Panneerchelvan , Aidil Azwin Zainul Abidin , Marayati Marsadek , Agileswari K. Ramasamy , Izham Zainal Abidin , W. Mohd Suhaimi Wan Jaafar
The synchronous generator (SG) plays a crucial role in power systems by serving as a stable and reliable source of electrical energy. The performance of an SG hinges on its standard parameters, which can be derived through dynamic tests. This study introduces a method for determining the standard parameters of an SG from dynamic tests conducted via power system simulation for engineering (PSS/E). The proposed method entails conducting several key tests on the generator, including a direct-load rejection test, excitation removal test, quadrature-axis load rejection test, arbitrary axis load rejection test, and open-circuit saturation test. The results obtained from these tests are then utilized to calculate the standard parameters of the SG accurately. To validate the effectiveness of the method, simulation data from the SG, as well as the designed initial data, are utilized. Statistical analysis reveals that the maximum relative error is equal to or less than 2.7% of the design values for all standard parameters, emphasizing the robustness and accuracy of the proposed method. The methodology presented in this study can complement field or site measurements, as it enables the verification of system parameters through dynamic simulations.
Volume: 16
Issue: 3
Page: 1658-1672
Publish at: 2025-09-01

ToLatin application acceptability evaluation to support Balinese script transliteration learning

10.11591/ijaas.v14.i3.pp804-816
Luh Joni Erawati Dewi , Gede Indrawan , I Made Agus Oka Gunawan , I Wayan Sutaya , Sariyasa Sariyasa
This work supported Indonesia's research focus area on information and communication technology (ICT) content improvement for information data on various forms of local wisdom. As one of the various forms of local wisdom, the Balinese script was supported by the ToLatin application that transliterates Balinese script into Latin text. It has been used to support Balinese script learning at the high school level in Buleleng Regency, Bali, Indonesia. To determine the acceptability of this application, which had not been studied before, a user acceptance evaluation was conducted using a combination of acceptance variables from the technology acceptance model (TAM) and success variables from DeLone & McLean. This study used a quantitative method with data collection through questionnaires from 385 respondents. The data analysis used the importance-performance analysis (IPA) method through suitability, gap, and quadrant analyses. The study results indicated that the acceptability of ToLatin could be more optimal. The suitability analysis revealed an average score of 87.91%, indicating the need for improvement in system quality, particularly the innovative indicator (SysQ3), based on the quadrant analysis. The gap analysis revealed an average score of -0.54 from 7 acceptance variables, indicating the need to improve system performance to meet user expectations.
Volume: 14
Issue: 3
Page: 804-816
Publish at: 2025-09-01

Single photovoltaic panel constant regulated voltage based on modified DC-DC buck-boost converter topology

10.11591/ijape.v14.i3.pp620-630
Ro’ad Baladi Al Komar , Arwindra Rizqiawan
This research proposes a single photovoltaic panel constant regulated voltage based on novel topology. A modified DC-DC buck-boost converter was chosen because characteristics of voltage boost and low input current ripple. A comprehensive analysis of the proposed converter cells was elaborated in this study. Furthermore, a control technique is designed for the proposed converter. A double-loop control method using proportional integral (PI) is employed in this research. The outer loop controls the output voltage, while the inner loop is used to control the inductor current. By employing double-loop control, the presence of ripple current and voltage can be reduced even further. Simulation and experimental results validate the converter’s effectiveness, demonstrating stable voltage output under varying input voltage (33-36 V) and load conditions, maintaining a 40 V output with an overshoot within ±5%. The results show that the modified buck-boost converter can achieve improved efficiency and ripple reduction compared to conventional models, making it a viable solution for renewable energy systems.
Volume: 14
Issue: 3
Page: 620-630
Publish at: 2025-09-01

Solar photovoltaic based cascaded multilevel inverter with 33-levels using phase opposition disposition control method

10.11591/ijaas.v14.i3.pp928-935
Chandolu Sai Deepak , Madhu Babu Thiruveedula , Bandari Rahul Teja , Supe Gowtham , Sthambhampally Vivek , Panuganti Yeshwanth Kumar
A cascaded multilevel inverter (MLI) tailored for photovoltaic (PV) networks, aiming to improve power quality and support transformer-less operation. The symmetric MLI design is selected for its effectiveness in minimizing harmonics and enhancing fault tolerance in high-power scenarios, where the use of power semiconductor converters can introduce complications. The proposed inverter configuration achieves thirty-three voltage levels, optimizing power quality while using insulated gate bipolar transistor (IGBT) semiconductor switches. The phase opposition disposition (POD) control method is applied to trigger necessary switching signals for the inverter's components. To ensure high output voltage for the MLI, a boost converter is employed, and the overall system is tested with an R load. The effectiveness of the design is validated through MATLAB/Simulink simulations, which demonstrate a notable reduction in total harmonic distortion (THD). 
Volume: 14
Issue: 3
Page: 928-935
Publish at: 2025-09-01

Effectiveness of dashboard as a work progress scheduling, monitoring, and decision-making in construction projects

10.11591/ijaas.v14.i3.pp878-885
Putri Lynna Adelina Luthan , Nathanael Sitanggang
Scheduling, monitoring, and decision-making are important factors in determining the general achievement of sustainable construction. Therefore, this study was conducted to determine the effectiveness of a dashboard as a measuring tool for construction project scheduling, monitoring, and decision-making. A survey with a Likert scale (5 scale) on each viewpoint, including planning, oversight, and independent direction, of 15 respondents from project executors and 7 respondents from supervisors was used as instrumentation. The results showed that the dashboard was evaluated with a value of 92.25 among executors and supervisors linked to product characteristics. Executors also used the scheduling dashboard with a value of 91.73, and the feature of employing the concept for supervision was appropriate as a measuring instrument, scoring 92.15. Furthermore, the final step was the aspect of using the dashboard for decision-making, which was tested and used with a value of 88.14. The use dashboard model is an effective tool for work progress scheduling, monitoring, and decision-making in construction projects.
Volume: 14
Issue: 3
Page: 878-885
Publish at: 2025-09-01

Implementing fuzzy control for a DC-DC boost converter using FPGA

10.11591/ijape.v14.i3.pp656-665
V. Radhika , Karuppannan Srinivasan , R. Kiruba
This research explores the use of field programmable gate arrays (FPGA) to mitigate static voltage errors and reduce voltage spikes in DC-DC boost converters. Given the dynamic nature of the load impedance in these converters, FPGA is well-suited for designing systems with adaptive behavior. The study implements a fuzzy control algorithm on FPGA in a simulation environment with a small sampling period. The parallel processing capability of FPGA enables the simultaneous execution of fuzzy control algorithms, enhancing the system's responsiveness to rapid changes in load conditions. This approach minimizes voltage overshoot and effectively suppresses voltage spikes. By leveraging FPGA’s high-speed parallelism and flexibility, the research demonstrates significant improvements in the dynamic performance of the DC-DC boost converter. The results highlight FPGA’s potential as a robust platform for controlling power electronic systems, ensuring improved stability and efficiency under varying load conditions.
Volume: 14
Issue: 3
Page: 656-665
Publish at: 2025-09-01

Gated dilated causal convolution-based encoder-decoder network for IoT intrusion detection

10.11591/ijape.v14.i3.pp722-732
Aarthi Gopalakrishnan , Sharon Priya Surendran , Aisha Banu Wahab
The internet of things (IoT) is perhaps the greatest modern development, as it affects our daily lives and is rapidly expanding in its application zones. The IoT is used in everyday activities, so security is more crucial because intrusion detection will introduce and eliminate attacks. In this paper, a novel deep learning based intrusion detection technique (DEBIT) has been proposed that detects the intrusion using deep learning techniques efficiently. Initially, the data from IoT user is preprocessed and classified using the novel gated dilated casual convolution based encoder-decoder (GDCC-ED) method, which classifies the data into attack and non-attack. The proposed DEBIT framework has been assessed using a MATLAB simulator. The performance of the proposed DEBIT framework has been assessed based on specific parameters, including recall, detection rate, accuracy, F1 score, and precision. Based on experimental results, the suggested method is 99.5% more accurate than pigeon-inspired optimization (PIO), Res-TranBiLSTM, and blockchain-based African buffalo (BbAB), which are 85.4%, 92.5%, and 85%, respectively.
Volume: 14
Issue: 3
Page: 722-732
Publish at: 2025-09-01

Pitch extraction using discrete cosine transform based power spectrum method in noisy speech

10.11591/ijaas.v14.i3.pp955-965
Humaira Sunzida , Nargis Parvin , Jafrin Akhter Jeba , Sulin Chi , Md. Shiplu Ali , Moinur Rahman , Md. Saifur Rahman
The pitch period is a key component of many speech analysis research projects. In real-world applications, voice data is frequently gathered in noisy surround- ings, therefore algorithms must be able to manage background noise well in order to estimate pitch accurately. Despite advancements, many state-of–the-art algorithms struggle to deliver adequate results when faced with low signal-to- noise ratios (SNRs) in processing noisy speech signals. This research proposes an effective concept specifically designed for speech processing applications, particularly in noisy conditions. To achieve this goal, we introduce a fundamen- tal frequency extraction algorithm designed to tolerate non-stationary changes in the amplitude and frequency of the input signal. In order to improve the extrac- tion accuracy, we also use a cumulative power spectrum (CPS) based on discrete cosine transform (DCT) rather than conventional power spectrum. We enhance extraction accuracy of our method by utilizing shorter sub-frames of the input signal to mitigate the noise characteristics present in speech signals. According to the experimental results, our proposed technique demonstrates superior per- formance in noisy conditions compared to other existing state-of-the-art meth- ods without utilizing any kind of post-processing techniques.
Volume: 14
Issue: 3
Page: 955-965
Publish at: 2025-09-01

AI-driven solutions for Li-ion battery performance and prediction

10.11591/ijape.v14.i3.pp569-578
Sthitprajna Mishra , Chinmoy Kumar Panigrahi , Subhra Debdas , Atri Bandyopadhyay , Srikanth Velpula , Amit Kumar Sahoo , Pabitra Kumar Tripathy
Batteries serve as crucial power sources for essential portable devices like electric vehicles, smartphones, and laptops. The widespread adoption of Li-ion batteries, while beneficial, has unfortunately led to a surge in adverse incidents. The sudden failure of batteries in both industrial and lightweight applications poses significant economic risks across various industries. Consequently, researchers are intensifying their focus on enhancing battery state estimation, management systems, and predicting remaining useful life (RUL). This paper is structured into three main sections. Firstly, it delves into the acquisition of battery data, encompassing both commercially available and freely accessible Li-ion battery datasets. Secondly, the exploration extends to techniques for estimating battery states through advanced battery management systems. The paper investigates battery RUL estimation, categorizing and evaluating diverse prognostic methods applied to Li-ion batteries based on crucial performance parameters. The review includes scrutiny of commercially and publicly available datasets for various battery models and conditions, considering different battery states and the role of advanced battery management system (BMS). In the final section, the paper concludes with a comparative analysis of Li-ion battery RUL prediction, incorporating exploration into various RUL prediction algorithms, and mathematical models, and introducing an AI-based cloud monitoring system.
Volume: 14
Issue: 3
Page: 569-578
Publish at: 2025-09-01

Large language models and retrieval-augmented generation-based chatbot for adolescent mental health

10.11591/ijaas.v14.i3.pp849-858
Andi Riansyah , Imam Much Ibnu Subroto , Intan Nur'aini , Ratna Supradewi , Suyanto Suyanto
Access to fast and efficient information is crucial in today's digital era, especially for teenagers in obtaining mental health services. The manual method used by Youth Information and Counselling Centre (PIK R) to provide mental health information requires significant time and effort. This research presents an AI-based solution by developing a chatbot system using retrieval-augmented generation (RAG) and large language models (LLM). This chatbot is designed to provide accurate and effective mental health information for teenagers throughout the day. An analysis of a dataset consisting of articles on teenage mental health and data from the Alodokter website was used as the basis for the development of this chatbot. The research results show that the chatbot is capable of providing relevant and accurate information, with evaluations using the recall-oriented understudy for gisting evaluation (ROUGE) score method yielding an average of ROUGE-1 with a precision of 87.8%, recall of 83.0%, and F1-measure of 84.0%; ROUGE-2 with a precision of 82.8%, recall of 76.8%, and F1-measure of 78.2%; and ROUGE-L with a precision of 88.0%, recall of 82.6%, and F1-measure of 83.4%. These findings indicate the potential use of chatbots as an effective tool to support the mental health of adolescents.
Volume: 14
Issue: 3
Page: 849-858
Publish at: 2025-09-01

Study of the development of tandem solar cells to achieve higher efficiencies

10.11591/ijape.v14.i3.pp647-655
Debani Prasad Mishra , Jayanta Kumar Sahu , Umamani Subudhi , Arun Kumar Sahoo , Surender Reddy Salkuti
Tandem solar cells are the brand-new age revolution within the photovoltaic (PV) enterprise thanks to their higher power conversion efficiency (PCE) capability as compared to single-junction solar cells, which are presently dominating, however intrinsically restrained. With the appearance of steel halide perovskite absorber substances, manufacturing extremely efficient tandem solar cells at an inexpensive price can profoundly regulate the future PV landscape. It has been formerly seen that tandem solar cells primarily based on perovskite have confirmed that they can convert mild more efficiently than stand-alone sub-cells. To reap PCEs of greater than 30%, numerous hurdles have to be addressed, and our understanding of this interesting era has to be accelerated. On this, a technique of aggregate of substances was followed and via a modified numerical technique, it was decided what preference of substances for the pinnacle and bottom sub-cell consequences in a better fee of electricity conversion efficiency (PCE). Through this study, it was discovered that the use of germanium telluride (GeTe) backside subcellular together with perovskite (MAPbI3-xClx) as pinnacle subcell can offer an excessive performance of 46.64% compared to a tandem mobile with perovskite (MAPbI3)/CIGS and perovskite (MAPbI3)/GeTe which produce decrease efficiencies. SCAPS-1D was used to evaluate and simulate the overall performance of the developed tandem cells.
Volume: 14
Issue: 3
Page: 647-655
Publish at: 2025-09-01

Optimum control and design of a small hydro power plant for agriculture investment in Iraqi desert

10.11591/ijape.v14.i3.pp560-568
Jamal Ahmed Hameed , Thamir Hassan Atyia , Saba Fadhil Ahmed Jaf , Zubaidah Ghaze Abdulkareem , Ghanim Thiab Hasan
The aim of this paper is to conduct a mathematical and physical analysis to get a systematic treatment of design parameters and thus optimize water wheels. By today's standards, one finds empirical formulas instead, which take into account the practical experience of previous constructions, estimates of particular wheelbase shapes and sizes. So, based on the basic design and optimization standards for water wheels implementation, this paper attempts to design a water wheel power source in desert areas. Since the water wheels mainly use the gravitational force of water, there is only a slight hydrodynamic power losses. In addition to the high torque due to the large inertia of the water wheel. The obtained results indicate that the optimum operating range of the trailing water wheels is at a diameter of (2-7 m) and the Q water flow of about (0.1 m3/s). So, it can conclude that the implementing design has good efficiency and offer an economic benefit when use for the agriculture investment in desert areas.
Volume: 14
Issue: 3
Page: 560-568
Publish at: 2025-09-01

Battery cycle life and throughput optimization in wireless communication system with energy harvesting capability

10.11591/ijape.v14.i3.pp600-612
Omar Enassiri , Youssef Rochdi , Ouadoudi Zytoune
This research paper proposes a novel approach to address the energy challenges faced by internet of things (IoT) devices. The wireless communication system involves a transmitter equipped with energy harvesting module that charges both a rechargeable battery and a capacitor through an energy storage management system (ESMS). This ESMS is based on a reinforcement learning algorithm to dynamically switch between the battery and the capacitor, ensuring efficient power utilization. This reinforcement learning algorithm enables the device to learn and adapt its energy consumption patterns based on environmental conditions and usage, optimizing energy usage over time. Additionally, the system employs a rainflow counting method to estimate the state-of-health (SoH) of the battery, ensuring its longevity and overall system performance. By combining these approaches, the proposed system aims to significantly improve the energy efficiency and lifespan of IoT devices, as well as the amount of data sent for different temperature ranges, ultimately enhancing their cost-effectiveness and performance.
Volume: 14
Issue: 3
Page: 600-612
Publish at: 2025-09-01

Enhanced multi-mode control of Z-source virtual synchronous generator for photovoltaic systems using fuzzy logic controller

10.11591/ijape.v14.i3.pp701-711
Vempalle Rafi , Pradyumna Kumar Dhal , Shaik Hussain Vali , Sadhu Radha Krishna , Uppuluri Suryavalli , S. Vinoth John Prakash
An enhanced multi-mode control solution for a Z-source virtual synchronous generator (ZVSG) that makes use of a fuzzy logic controller (FLC) is proposed by this study for use in photovoltaic (PV) systems. As a potential grid integration option for PV systems, the ZVSG has great potential due to its steady and adjustable power production. A stable voltage and frequency output can be maintained by the ZVSG when it is running in a variety of modes, such as grid-connected, standalone, and islanding, according to the control approach that has been provided. The FLC is used for the purpose of controlling the switching frequency of the ZVSG as well as the DC-link voltage. The performance of the ZVSG is improved by the FLC-based control approach that has been proposed. This technique reduces the steady state error and offers a rapid dynamic response. The results of the simulation show that the recommendation for a control approach improves the performance of the ZVSG across a wide variety of operating modes and load conditions.
Volume: 14
Issue: 3
Page: 701-711
Publish at: 2025-09-01
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