Articles

Access the latest knowledge in applied science, electrical engineering, computer science and information technology, education, and health.

Advanced Search
Filter Icon

Filters article

Years

FAQ Arrow
Single Year
Range Year
0
0

Source Title

FAQ Arrow

Authors

FAQ Arrow

30,938 Article Results

Comparative performance analysis of MPPT algorithms for wind power generation: P&O, INC, and TSR methods

10.11591/ijape.v15.i2.pp894-904
Muhammad Aulia Desky , Yulianta Siregar , Maksum Pinem
Wind energy has great potential, especially in areas with high wind speeds such as Southeast Aceh. However, wind speed fluctuations reduce turbine efficiency, necessitating maximum power point tracking (MPPT) for optimization. This study compared three MPPT methods perturb and observe (P&O), incremental conductance (INC), and tip speed ratio (TSR) to identify the most effective technique. Using MATLAB Simulink, simulations were conducted with wind speed data from Southeast Aceh and a DC-DC boost converter. Results showed the P&O method performed best, producing 847.83 W at 10 m/s, compared to 702.40 W for INC and 324.35 W for TSR. P&O also achieved the highest current output, reaching 16.45 A, while INC and TSR produced 13.66 A and 6.34 A, respectively. At lower wind speeds, P&O continued to outperform the other methods. This study concludes that the P&O method is the most effective method to improve the efficiency of wind turbines in Southeast Aceh, while INC shows moderate performance and TSR is the least effective method due to fluctuating wind speeds in a short time, so that TSR cannot maintain its maximum value. Therefore, P&O is recommended as the optimal MPPT technique for wind power plants in this region.
Volume: 15
Issue: 2
Page: 894-904
Publish at: 2026-06-01

The effect of emotion card games on emotional intelligence among elementary school-aged children: a quasi-experimental study in Mataram, Indonesia

10.11591/ijphs.v15i2.27032
Moh. Arip , Sri Susantini , Martha Meti Kodi , Melati Inayati Albayani , Novi Enis Rosuliana
Emotional intelligence is a key skill influencing adaptation, communication, and personal growth in elementary school-aged children. Emotional card games offer a promising interactive approach to enhance children's emotional competencies. To analyze the effect of emotional card games on the emotional intelligence of elementary school-aged children. A quasi-experimental pretest-posttest control group design was conducted among 77 first-grade students at MI Mambaul Khair NW Bertais Mataram in 2025. The intervention group (n = 39) participated in three sessions of an emotional card game, while the control group (n = 38) received no intervention. Emotional intelligence was measured using a validated 24-item questionnaire. The intervention group demonstrated a significant increase in emotional intelligence scores from pre-test to post-test (p = 0.007), whereas the control group showed no significant change. Between-group comparison confirmed significantly higher post-test scores in the intervention group (p = 0.006). After adjusting for confounding variables and baseline scores, the intervention effect remained statistically significant (p < 0.001). Emotional card games effectively improve emotional intelligence among elementary school-aged children. These findings support the integration of game-based social-emotional learning strategies into elementary school curricula. School health practitioners and educators can utilize this low-cost, engaging intervention to promote children's emotional well-being and support holistic child health development.
Volume: 15
Issue: 2
Page: 398-407
Publish at: 2026-06-01

Smart adaptive CC-CV charger with PSO-accelerated load identification and fuzzy duty-cycle regulation

10.11591/ijpeds.v17.i2.pp1045-1057
Indhana Sudiharto , Era Purwanto , Muhamad Milchan , Alifian Nur Rahmadika
This paper presents an adaptive constant-current/constant-voltage (CC-CV) charger architecture, meticulously designed to address a key challenge in smart chargers. This challenge involves recognizing various battery types and applying the appropriate charging profile expeditiously, without requiring user intervention. The system integrates a particle swarm optimization (PSO) algorithm for ultra-fast load identification with a Mamdani-type fuzzy logic controller for precise duty cycle regulation. The PSO mechanism is capable of determining the optimal initial duty cycle in less than 500 milliseconds. Subsequent to this preliminary initiation, the fuzzy logic controller guarantees the effectiveness of current and voltage regulation during the charging phases. The simulation results obtained from this study validate the system's robustness, as evidenced by the consistent maintenance of voltage ripple below ±0.06 V and current ripple below ±0.04 A. These findings demonstrate the efficacy of the proposed approach in achieving fast, stable, and safe multi-load battery charging. The chemistry-agnostic design of the battery pack is extendable to any battery pack following the CC-CV paradigm, making it highly suitable for practical applications that demand flexibility and high reliability.
Volume: 17
Issue: 2
Page: 1045-1057
Publish at: 2026-06-01

Comparison of phase disposition, phase opposition, and phase disposition with variable frequency PWM techniques for harmonic reduction in cascaded multilevel inverters

10.11591/ijpeds.v17.i2.pp858-872
G. Nayana , Savita D. Torvi
Renewable energy penetration in distributed generation systems significantly impacts the power quality of the output. The stochastic nature of the inverters provides variable voltage and variable frequency outputs, which is an advantage when used with photovoltaic (PV) and grid integration to the distribution grid, and also in induction motor drives. A primary source of power quality issues is the harmonics generated by the inverters. Multilevel inverters are commonly employed to mitigate these harmonics and improve power quality. Among the various multilevel inverter topologies, the cascaded multilevel inverter (CMLI) has gained prominence due to its simple structure, ease of control, and reduced component requirements. This paper presents a comprehensive review of multilevel inverter topologies that have influenced the evolution of the CMLI structure, along with an investigation into the application of advanced pulse width modulation (PWM) strategies for performance enhancement. In particular, phase disposition (PD), phase opposition disposition (POD), and phase disposition with variable frequency (PD-VF) PWM techniques are implemented on cascaded h-bridge (CHB) multilevel inverters configured for five-level, seven-level, and nine-level operations. A comparative evaluation of total harmonic distortion (THD) is conducted for each inverter configuration, both with and without the inclusion of an LC output filter, to assess waveform quality and harmonic mitigation capability. Furthermore, the harmonic suppression effectiveness of PD, POD, and PD-VF modulation methods is systematically analyzed across different voltage levels. The study also demonstrates that varying the carrier frequency in PD-VF modulation significantly influences THD performance, offering enhanced flexibility and expanded control possibilities in multilevel inverter applications.
Volume: 17
Issue: 2
Page: 858-872
Publish at: 2026-06-01

Dual random optimized pulse width modulation controller for three-phase voltage source inverter driven brushless DC motor

10.11591/ijpeds.v17.i2.pp966-980
Halidu Abdul Mumin , Solomon Nunoo , Joseph Cudjoe Attachie
Brushless DC (BLDC) motors are widely employed in modern power electronic applications due to their high efficiency and dynamic performance. However, conventional pulse width modulation (PWM) techniques often generate concentrated harmonic components, leading to acoustic noise, torque ripple, and reduced inverter efficiency. This paper proposes an artificial neural network–assisted dual random pulse width modulation (ANN-DRPWM) strategy to enhance the output quality of a three-phase voltage source inverter driving a BLDC motor. In the proposed approach, supervised ANN training enables dual randomization of the carrier and modulation signals, effectively dispersing harmonic energy while maintaining improved DC-link voltage utilization. A passive LC filter is subsequently integrated to further suppress residual harmonics and ensure compliance with harmonic standards. The system is modeled and simulated in MATLAB/Simulink and evaluated against conventional sinusoidal PWM and flying capacitor multilevel inverter (FCMLI) techniques. Results demonstrate that the proposed ANN-DRPWM method achieves a post-filter total harmonic distortion (THD) of 2.17%, along with a 6-9% improvement in inverter efficiency and a noticeable reduction in torque ripple. Overall, the proposed strategy offers an efficient and intelligent modulation solution for high-performance BLDC motor drives, suitable for applications such as electric vehicles, renewable energy systems, and industrial drives.
Volume: 17
Issue: 2
Page: 966-980
Publish at: 2026-06-01

Investigation of the photoluminescence properties of quantum dots using theoretical simulation

10.11591/ijape.v15.i2.pp942-947
Le Doan Duy , Le Xuan Thuy
This study investigates the optical behavior of CdSe quantum dots, a class of semiconductor nanomaterials widely studied for light-emitting, photovoltaic, and bioimaging applications owing to their size-dependent electronic structure. The objective is to clarify the relationship between quantum dot size, size distribution, and emission characteristics through experimental and simulated optical spectra. UV-Vis absorption, photoluminescence, and simulated PL spectra were analyzed for CdSe quantum dots excited at 325 nm. The experimental PL spectrum exhibits a single and narrow emission band assigned to the 1Se → 1Sh transition, which is blue-shifted compared with bulk CdSe, confirming strong quantum confinement in 2-3 nm particles with a very narrow size distribution of less than 1%. A large Stokes shift of 0.93 eV is observed, attributed to confinement effects and surface-related states. Simulated photoluminescence (PL) spectra for 3-6 nm quantum dots show progressive red-shifting and spectral broadening with increasing particle size, while smaller quantum dots display stronger PL intensity due to enhanced confinement and more efficient radiative recombination. Parameter analysis further reveals that size deviation and linewidth broaden emission and reduce intensity without changing the peak wavelength. These findings provide useful guidance for optimizing CdSe quantum dots for QLEDs, bioimaging, and broadband optoelectronic devices.
Volume: 15
Issue: 2
Page: 942-947
Publish at: 2026-06-01

Comparison of differential evolution optimization technique with other techniques in solving multi-objective optimal power flow

10.11591/ijape.v15.i2.pp663-673
Vineeta S. Chauhan , Jaydeep Chakravorty , Siddharthsingh K. Chauhan
Optimal power flow (OPF) is a complex, non-linear optimization problem focused on determining the steady-state operating parameters of power systems for economic and secure operation. The challenge intensifies due to numerous system constraints that must be satisfied simultaneously. Although various evolutionary algorithms (EAs) have been applied to OPF in recent decades, these algorithms often use unconstrained search strategies. A common approach to handle constraint violations is the static penalty function, which penalizes infeasible solutions. However, selecting suitable penalty coefficients typically involves time-consuming trial and error, affecting overall performance. This study explores the integration of advanced constraint handling (CH) techniques within the differential evolution (DE) framework to enhance the performance of optimal power flow (OPF) solutions. In particular, it looks at three approaches: a hybrid ensemble of two CH techniques (ECHT), a self-adaptive penalty method (SP), and superiority of viable solutions (SF). The IEEE 30-bus and IEEE-57 bus benchmark systems are used to evaluate the efficacy of these techniques under a variety of OPF goals, including lowering emissions and generation costs, cutting power losses, and enhancing voltage stability. We took into consideration both weighted-sum multi-objective and single-objective formulations. The simulation outcomes indicate that the proposed CH-DE approaches deliver robust and competitive optimization results, demonstrating improved constraint handling capabilities when compared to contemporary methods in the literature.
Volume: 15
Issue: 2
Page: 663-673
Publish at: 2026-06-01

Regenerative braking with battery management system in E-bike

10.11591/ijape.v15.i2.pp565-572
B. P. Divyashree , G. Lakith , H. N. Sukanya , Nagaling M. Gurav , Neeli Mallikarjuna , Unnam Anil
Energy neither be created nor be destroyed, but it can be transformed into other forms as per the law of conservation of energy. This information is epitomized by the regenerative braking system (RBS), which transforms kinetic energy into mechanical energy, thus recuperating waste energy into mechanical energy and making it beneficial. The regenerative braking have significant impact in electric vehicle technology due to the contemporary energy challenges and dwindling resources. Regenerative braking involves apprehending the lost kinetic energy during braking and converting it into a storable or instantly usable form. The recuperated kinetic energy can be reintegrated into vehicle’s power system or stored for further use, often in a battery, especially lithium-ion batteries which are managed by a battery management system (BMS) to ensure optimal performance and longevity. The utilization of various sensors by BMS to monitor parameters such as temperature, current, and voltage, entitling it to assess the battery’s health and determine its state of charge and discharge. Additionally, the BMS protects the battery against cavernous discharge and over-voltage, which can result from rapid discharging and charging currents, thereby optimizing the utilization of battery energy. In this article, the design of an electrical regenerative braking system with a battery management system in an electric bicycle (E-bike) applications are presented. The results show that the system works well in both battery-operated and regenerative modes. When in regenerative mode, the voltage and current stay within the specified range and are suitable for charging batteries. On the other hand, during regular operation, the increase in energy consumption is matched with the battery mode mileage.
Volume: 15
Issue: 2
Page: 565-572
Publish at: 2026-06-01

Comparative analysis of PM6:L8-BO organic and inverted organic solar cell

10.11591/ijape.v15.i2.pp770-780
Karthika Krishnakumar , Ashish Grover , Pardeep Kumar
Advancements in solar technologies are driven by the pursuit of higher efficiency and reduced environmental impact. This study presents a comprehensive and comparative analysis of organic and inverted organic solar cells (OSC and IOSC), using the OghmaNano software for simulations and analysis. This work is specifically designed to compare conventional and inverted structures and understand how device engineering impacts performance metrics. When OSCs are characterized by a low work-function cathode on top, IOSCs feature a clear conductive oxide cathode at the bottom. The study focusses on extracting key electrical output, including short circuit current density (JSC), open-circuit voltage (VOC), fill factor (FF) and power conversion efficiency (PCE), through the calculated current-voltage characteristic (J-V). Various physical characteristics, such as thickness of different layers and materials deployed as electron transport layer (ETL) and hole transport layer (HTL), are systematically investigated. Diverse top and bottom electrodes, encompassing monothin and multithin layer configurations, are proposed. The study shows that IOSC achieves higher efficiency than OSC, reaching 21.60%, while using a multithin layer ZTZ (ZnO/TiOx/ZnO) as the bottom contact, demonstrating improved charge transport and overall efficiency.
Volume: 15
Issue: 2
Page: 770-780
Publish at: 2026-06-01

Rule-based energy management strategies for a hybrid microgrid using grey wolf optimizer

10.11591/ijape.v15.i2.pp858-879
Sarmid Shakir Abdulsattar , Chee Wei Tan , Shahrin Ayob , Yasir Shakir Abdulsattar , Ahmed Tijjani Dahiru , Chin Kim Gan , Kwan Yiew Lau
This study utilizes grid-connected microgrids using photovoltaics (PVs) and wind turbines (WTs) in a residential system. For improved reliability, the system uses battery storage and diesel generators (Dgen). The proposed system uses supervisory controllers (as a rule-based energy management system) for energy management strategy implementations. The essence of using the grey wolf optimizer (GWO) is to strategize the rule-based energy management system in the proposed microgrid operations. The primary objectives are to achieve a low levelized cost of energy (LCOE) and determine the optimal number of microgrid components. The performance of the GWO is compared with three other optimization algorithms, namely, antlion optimizer (ALO), particle swarm optimizer (PSO), and cuckoo search algorithm (CSA), for benchmarking purposes. The findings indicate that the proposed GWO supersedes ALO, PSO, and CSO in energy cost reduction by 30.3% (0.0448 $/kWh), 65.6% (0.0971 $/kWh), and 120% (0.1774 $/kWh), respectively. The suggested algorithm selects the optimum number of the system’s components, which is 46 PV modules, 30 wind turbines, and 10 units of batteries. An improved GWO-based algorithm based on hybridization with gradient descent algorithms is envisaged to implement a customer-centered energy management that can ensure customer satisfaction and further reduce energy cost.
Volume: 15
Issue: 2
Page: 858-879
Publish at: 2026-06-01

Analysis of CCS implementation in Indonesia’s coal fired power plants, economic optimization, and potential impact on Java-Bali grid for future decarbonization

10.11591/ijape.v15.i2.pp927-941
Anggit Raksajati , Sanggono Adisasmito , Veri Hendrayawan
This study aims to evaluate impact of retrofitting carbon capture and storage (CCS) technology on coal fired power plants (CFPP) in Indonesia. Using a representative 3×330 MW CFPP, the integration of CCS increases the levelized cost of electricity (LCoE) to 124 USD/MWh. Key cost components include CO₂ capture (21.7%), energy penalty from steam extraction (18.5%), and CO₂ transport and injection (16.7%). Sensitivity analysis indicates that CCS becomes financially viable under a high carbon cap (0.9 tCO₂/MWh) and a carbon tax of 76 USD/tCO₂. Meanwhile, International carbon markets offer a potential revenue at 75 USD/tCO₂ can fully offset CCS costs. Additionally, CAPEX grants can reduce LCoE to 12.4%, serving to mitigate upfront investment for CCS deployment. Within the Java-Bali grid, CFPP account for 58.8% of the generation mix with 41% aged 10-20 years using predominantly subcritical technology while 28% are over 20 years old and follow natural retirement being replaced by renewable energy. CCS retrofitting is more economically and technically viable for mid aged plants with newer technologies and lower emission intensities, supporting grid stability with limited renewable base load availability. This strategy also serves as a transitional pathway toward long term renewable integration until the LCoE of PV+BESS falls below 50 USD/MWh.
Volume: 15
Issue: 2
Page: 927-941
Publish at: 2026-06-01

Self tuning of output scaling factor for type-2 interval fuzzy controllers

10.11591/ijape.v15.i2.pp480-491
Mouna Ghanai , Kheireddine Chafaa , Ali Medjghou , Nadia Bounouara
In this study presents a self-tuning type-2 fuzzy logic controller framework, which operates on the principle of continuously adjusting the controller structure by modifying the controller gain (scaling factor) as a function of the error and its rate of change, in order to achieve optimal control performance. The proposed structure is both simple and robust, with real-time gain adaptation facilitated by two type-2 fuzzy systems; the first one containing the rules of control task for speed regulation, and the second one containing the rules for the adaptation of the scaling factor. Both systems have the same inputs error and its variation. This work specifically focuses on tuning the output scaling factor, which is considered equivalent to the controller gain. The effectiveness of the proposed approach is evaluated through its application to the control of an induction machine, a system known for its complexity and strong nonlinearity. Simulation results demonstrate that the fuzzy controller significantly enhances performance, even under challenging operating conditions such as low-speed regimes.
Volume: 15
Issue: 2
Page: 480-491
Publish at: 2026-06-01

Performance degradation analysis of induction motors using Simulink and hybrid method

10.11591/ijape.v15.i2.pp525-534
Kamrai Janprom , Sittadach Morkmechai , Natchanun Prainetr , Supachai Prainetr
Voltage unbalance faults (VUF) have a significant adverse impact on the performance and operational lifespan of induction motors. This paper presents a hybrid method that integrates multi-sensor analysis to evaluate induction motor behavior under different levels of electrical fault conditions. The research methodology comprises the development of a three-phase induction motor model in MATLAB/Simulink, combined with experimental monitoring of current, voltage, rotational speed, acoustic signals, and torque. The collected data are analyzed using linear regression to quantify performance degradation. The results indicate that increasing fault severity correlates with reductions in motor efficiency and operational stability. Furthermore, a hybrid technique incorporating modulation analysis of acoustic signals derived from vibration and resonance is proposed to improve the accuracy of efficiency and loss estimation. This approach outperforms conventional methods and demonstrates strong potential for industrial applications, as it effectively mitigates the negative effects of voltage supply faults.
Volume: 15
Issue: 2
Page: 525-534
Publish at: 2026-06-01

Wind direction based aggregation of wind power plants under exact wind speeds

10.11591/ijape.v15.i2.pp818-830
Ali M. S. Al-Bayati , Huda Hamza Abdulkhudhur
Modeling of a wind power plant (WPP) containing numerous wind turbines in a highly detailed manner requires a substantial computational cost. Further, the response and dynamic behavior of the WPP systems are significantly influenced by the dynamic nature of wind speed. This paper presents a methodology of aggregating WPP systems with consideration for wind speed directions. To attain a realistic aggregated model, an algorithm for calculating actual exact wind speed at each wind turbine within the WPP was proposed considering different wind speed directions. Furthermore, the best wind speed direction for a fixed site area that produces a minimum wind energy losses inside the WPP was also assessed and reported. The results revealed the importance of employing the exact wind speed calculations within the WPP to ensure that the aggregated WPP model accurately represents real-world conditions. The results of this paper highlighted the role of wind direction in determining the response of WPPs and provide guidance on maximizing the WPP throughput during the year under the prevailing wind speed direction at the site.
Volume: 15
Issue: 2
Page: 818-830
Publish at: 2026-06-01

Sliding mode control of a solar powered switched-inductor based quadratic DC-DC converter for sustainable EV battery charging application

10.11591/ijape.v15.i2.pp712-723
Jawahar Marimuthu , Edward Rajan Samuel Nadar
The growing demand for sustainable transportation and fast charging solutions requires efficient power conversion technologies for solar electric vehicles or electric vehicles (SEVs/EVs). A non-isolated solar-powered switched-inductor quadratic DC-DC converter is proposed here to achieve high voltage gain in a practical way under reduced stress on power devices. A switched-inductor network blended with CCM operation avoids the extremely high duty cycles and high electromagnetic interference in conventional boost converters. A sliding mode control (SMC) strategy is applied here to improve robustness against parameter variations, ensure stable operation against dynamic load variations, and extract maximum power during solar-powered charging operation. This makes the topological platform proposed in this study especially suitable for a wide variety of applications, such as for SEVs and fast-charging applications of EVs. Detailed MATLAB/Simulink analyses along with a laboratory-scale prototype verify the performance of the converter under practical operation conditions and confirm the high efficiency of 91-96% at varied irradiance, low voltage ripple of 0.5-1.5% of output voltage and input current ripple of 5-12% of input current, reduced switching losses of 1-4%, and suitability of the presented converter for renewable-energy-based transportation systems.
Volume: 15
Issue: 2
Page: 712-723
Publish at: 2026-06-01
1 2 3
...
2062 2063
Show 33 of 2063

Discover Our Library

Embark on a journey through our expansive collection of articles and let curiosity lead your path to innovation.

Explore Now
Library 3D Ilustration