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31,207 Article Results

Sliding-mode assisted direct torque control for reliable wind turbine operation

10.11591/ijape.v15.i3.pp1180-1189
Nehal Ouassila , Dib Djalel , Billel Meghni , Dib Nour Elhouda
This paper investigates and compares the performance of two advanced control strategies, direct torque control (DTC) and sliding mode control (SMC), applied to a permanent magnet synchronous generator (PMSG) used in wind energy conversion systems. The control schemes aim to ensure efficient energy conversion and stable operation under variable wind conditions. The comparison is carried out through detailed simulations considering electromagnetic torque response, stator flux behavior, speed regulation, and robustness to disturbances and parameter variations. The results show that DTC provides a fast dynamic response with a relatively simple control structure, but suffers from torque and flux ripples and sensitivity to parameter variations. In contrast, SMC demonstrates higher robustness against uncertainties and disturbances, with smoother torque characteristics and improved speed regulation. Overall, the study indicates that SMC is a promising approach for enhancing the stability and performance of PMSG-based wind energy systems. Future work may explore hybrid strategies combining the fast response of DTC with the robustness of SMC, as well as intelligent control techniques to further optimize energy extraction.
Volume: 15
Issue: 3
Page: 1180-1189
Publish at: 2026-09-01

Environmental footprint assessment of lithium-ion (Li-ion) batteries in electric scooters: a case study of PT Motor Listrik Indonesia

10.11591/ijape.v15.i3.pp955-964
Rafi Juniar Saputra , Aufar Fikri Dimyati , Silvi Istiqomah , Dwi Heru Siswantoro
Indonesia ranks as the world's sixth-largest contributor to CO2 emissions, with motorcycles alone responsible for 56,788 tons of CO2 in 2020. While electric motorbikes are considered a cleaner alternative due to their lack of exhaust emissions, their overall environmental impact must be evaluated throughout the entire battery life cycle. This study conducts a gate-to-grave life cycle assessment (LCA) on the lithium-ion (Li-ion) batteries used in MOLINDO electric motorbikes, covering the supplier, production, usage, and disposal stages. The total environmental impact was found to be 920 points (pt), with the usage phase being the largest contributor at 550 pt, followed by production at 185.5 pt, supplier at 179 pt, and disposal at 5.54 pt. Two improvement strategies were explored: reusing external battery cases, which slightly reduced the impact to 918.86 pt, and repurposing second-life batteries, which extended battery use but increased the impact to 998.04 pt due to additional energy requirements. Compared to conventional motorbikes, electric motorbikes still offer a major environmental advantage in the usage phase (550 pt vs. 3,397 pt). These findings suggest that, alongside the shift to electric mobility, targeted actions such as better battery reuse, more efficient recycling, and cleaner electricity sources are essential to fully unlock the environmental benefits of electric motorbikes.
Volume: 15
Issue: 3
Page: 955-964
Publish at: 2026-09-01

Impact of power cable modelling on switching transient overvoltage analysis in medium voltage motors

10.11591/ijape.v15.i3.pp1233-1242
A. Nisar Basha , N. Mahiban Lindsay
Precise electrical cable representation is crucial for examining surge transient overvoltages in medium voltage (MV) motor systems. These brief overvoltages, initiated by swift switching actions, may induce substantial insulation strain, equipment degradation, and potential system failures. This study explores the influence of different power cable modeling techniques on transient overvoltage characteristics in MV motors during switching operations. Various modeling techniques, such as aggregated parameter, spread parameter, and frequency-dependent models, are evaluated for their effectiveness in inward capturing transient phenomena. Simulation studies using industry-standard electromagnetic temporary (EMT) assessment instruments evaluate the effect of these simulation methods on voltage spikes, shape distortions, and rise times. The discoveries indicate that exact electrical wire depiction is pivotal in molding, fleeting reactions, emphasizing the significance of choosing suitable simulation methods for efficient insulation coordination and system protection. This research provides valuable guidance for power system engineers, helping them mitigate transient overvoltage risks and improve the reliability of MV motor applications. Also, this study demonstrates electrical cable simulation that can impact the advice and verdicts obtained from moderate voltage motor.
Volume: 15
Issue: 3
Page: 1233-1242
Publish at: 2026-09-01

Predictive maintenance for induction motors: a novel synergy of deep learning and machine learning techniques

10.11591/ijape.v15.i3.pp1157-1167
V. Rajini , Karunya Harikrishnan , Krismadinata Krismadinata
Condition monitoring of induction motors is vital for preventing unexpected downtimes and minimizing the maintenance costs in industrial settings. A predictive maintenance model for early detection of faults is proposed. The motor current, flux, vibration, thermal and acoustic emission signatures are commonly used for fault detection as these signals reveal fault specific frequency components. Signal processing techniques like wavelet transform and Hilbert transform are used to identify faults at incipient stages. Machine learning and deep learning models are used nowadays to extract features and classify the faults accurately. The current and flux signals from healthy and faulty motors for inter turn faults were analyzed in this work and features were extracted through various signal processing methods. These features were then used to train models, including deep learning architectures, to classify motor faults. While the classical machine learning models provided a reasonably accurate fault classification, the convolutional neural network provided a very good classification accuracy. The findings show that deep learning models excel in detecting faults, especially under noisy and varying operational conditions, outperforming the traditional methods. These models offer a scalable, real-time solution for improving the reliability and efficiency of induction motor and facilitate more reliable assessments and contribute towards energy efficiency and extended lifetime of equipment.
Volume: 15
Issue: 3
Page: 1157-1167
Publish at: 2026-09-01

Near-zero NDZ islanding detection for multi-source DGs via hybrid ANFIS and adaptive fuzzy classification

10.11591/ijape.v15.i3.pp1117-1131
Madamaneri Ramya , Thangellamudi Devaraju
Increased penetration of distributed generation (DG) increases the likelihood of inadvertent islanding, in which traditional active/passive approaches are plagued with large non-detection zones (NDZ) and power-quality trade-offs. This article introduces a hybrid islanding detector that combines an adaptive neuro-fuzzy inference system (ANFIS) and an adaptive fuzzy classifier, concurrently benefiting from active frequency drift and rate-of-change-of-frequency (RoCoF) while consuming multi-signal features-RMS/THD of voltage and current, frequency, and active/reactive power sensed at the PCC. This architecture eliminates fixed-threshold brittleness and reduces the NDZ to zero without compromising power quality. Innovative aspects are i) a stacked, real-time sampling approach (Ts = 5 ms) that supplies per-signal ANFIS modules and a main decision ANFIS, ii) subtractive clustering for generating fuzzy rules data-driven, and iii) low iq perturbation to maintain unity power factor when querying doubtful NDZ examples. MATLAB/Simulink experimentation on a seven-case, seven-stage multi-source PV-interfaced microgrid (including power-matched NDZ) demonstrates fast, robust trips at disconnection with retention of IEEE-1547 voltage/frequency envelopes; the structure achieves minimum/ideal detection times of 0.04 s and reliably indicates islanding at ~0.4 s in matched and mismatched conditions, achieving normal breaker trip expectations (
Volume: 15
Issue: 3
Page: 1117-1131
Publish at: 2026-09-01

A deep learning approach for electric vehicle battery charging duration estimation using IoT

10.11591/ijape.v15.i3.pp1375-1385
Tumuluri Kanthimathi , Adhimoolam Sairam , Durairaj Chandrakala , Moorthy Radhika , Bichagal Shadaksharappa , Pitchai John Britto , Minakshi Sanadhya , Balasubramanian Suganya , Chelliah Srinivasan
The rapid development of electric vehicles (EVs) has increased the desire for precise charging duration estimate to enhance charging station administration and elevate customer experience. This research presents a deep learning (DL) architecture that uses internet of things (IoT)-enabled data to categorise charging duration into short, medium, and long classifications. The assessment dataset comprises many numerical and categorical variables affecting battery performance and charging behaviour, providing a thorough foundation for prediction. The system utilises a deep neural network (DNN) architecture with nonlinear transformations and regularisation techniques, trained with adaptive optimisation to provide durable convergence. Extensive experiments indicate that the proposed model achieves an overall accuracy of 99.26%, markedly improving traditional machine learning (ML) techniques. These results highlight the potential of DL to adeptly discern complex linkages in charging dynamics, providing dependable predictions for duration classification. The framework provides an advanced basis for implementation in smart charging infrastructures, facilitating effective scheduling, minimizing waiting times, and endorsing predictive maintenance measures. It enhances the reliability and efficiency of EV charging ecosystems with data-driven, IoT-enabled DL technologies.
Volume: 15
Issue: 3
Page: 1375-1385
Publish at: 2026-09-01

Modeling and implementation of a dual-mode emulator for line distance protection based on minimum line reactance

10.11591/ijape.v15.i3.pp1327-1339
Yassine El Asri , Abdellah Lassioui , Hassan El Fadil , Anwar Hasni , Marouane El Ancary , Hafsa Abbade
Advances in power system protection and the increasing complexity of electrical networks have created a growing need for flexible and cost-effective platforms for testing and validating protection algorithms. However, academic laboratories still face a lack of accessible experimental platforms allowing researchers to implement and evaluate new protection strategies under realistic conditions. This gap is becoming increasingly significant with the emergence of artificial intelligence and data-driven techniques, which require flexible environments for development, testing, and experimental validation. To address this limitation, this work presents the modeling and implementation of a dual-mode emulator for minimum reactance distance protection of overhead transmission lines, operating in both real-time and offline modes. The proposed system acquires and processes voltage and current signals to determine the minimum line reactance used for fault detection and distance estimation. The developed algorithm is evaluated through simulated fault scenarios under different operating conditions. Results demonstrate reliable fault detection and consistent fault-distance estimation. The dual-mode architecture enables both offline analysis of recorded signals and real-time algorithm evaluation. The proposed emulator therefore provides a practical, low-cost academic platform for research, training, and experimental validation of conventional and emerging protection strategies.
Volume: 15
Issue: 3
Page: 1327-1339
Publish at: 2026-09-01

Condition assessment of medium voltage cable insulation using leakage current and phase-resolved partial discharge

10.11591/ijape.v15.i3.pp1340-1350
Kamrai Janprom , Sittadach Morkmechai , Natchanun Prainetr , Supachai Prainetr
Reliable operation of medium-voltage distribution networks critically depends on the integrity of cross-linked polyethylene (XLPE) insulated cables. This paper proposes a diagnostic methodology that integrates leakage current (LC) measurement with phase-resolved partial discharge (PRPD) analysis to assess cable insulation condition. A MATLAB R2025 simulation model is first developed to emulate partial discharge (PD) signals superimposed on leakage current, providing preliminary validation of the proposed approach. The method is then experimentally verified using a 70 mm² XLPE cable rated at 16/20 (24) kV and tested in accordance with IEC 60502. Under applied high-voltage stress, leakage current and PD activity are measured, and insulation degradation is characterized using PRPD patterns. Both simulation and experimental results confirm that the proposed method reliably detects insulation defects and provides accurate condition assessment of XLPE cables. These findings demonstrate the potential of the method as a practical tool for supporting condition-based maintenance in medium-voltage power distribution systems.
Volume: 15
Issue: 3
Page: 1340-1350
Publish at: 2026-09-01

Structural and behavioral determinants of HIV among Indonesian MSM

10.11591/ijphs.v15i3.26988
Neila Sulung , Adi Cahya Murfi , Efriza Efriza , Nurdin Nurdin , Cici Apriza Yanti
HIV prevalence among men who have sex with men (MSM) remains disproportionately high in Indonesia. While behavioral risk factors have been widely studied, evidence integrating structural determinants remains limited. This study examined the role of structural and behavioral factors associated with HIV status among MSM in Jambi City, Indonesia. A cross-sectional study was conducted among 60 MSM recruited using non-probability sampling due to the hidden nature of the population. Data were collected using validated structured questionnaires and analyzed using multivariable logistic regression. Fifty percent of respondents were HIV-positive. Low educational attainment emerged as an independent structural determinant of HIV status (AOR = 5.51; 95% CI: 1.14-26.49), whereas behavioral factors showed significant crude associations but lost significance after adjustment. HIV vulnerability among MSM is shaped by structural inequalities beyond individual behaviors. Structural-focused interventions are essential to strengthen HIV prevention strategies in Indonesia.
Volume: 15
Issue: 3
Page: 640-647
Publish at: 2026-09-01

Biophysiological responses of premature infants in neonatal nursing care: a descriptive study of infant and maternal characteristics

10.11591/ijphs.v15i3.27051
Dwi Hastuti , Anggorowati Anggorowati , Zubaidah Zubaidah , Tri Nur Kristina , Siti Yuyun Rahayu Fitri
Preterm infants are physiologically vulnerable and require continuous cardiorespiratory and thermal monitoring during neonatal nursing care. Evidence describing physiological indicators in relation to infant maturity and maternal sociodemographic characteristics remains limited. This study aimed to describe physiological indicators (heart rate, respiratory rate, oxygen saturation, and temperature) among preterm infants and examine their associations with infant and maternal characteristics. An observational descriptive study was conducted from August to December 2025 among preterm infants (
Volume: 15
Issue: 3
Page: 726-736
Publish at: 2026-09-01

Physical-maturation with health education on the incidence of anemia among adolescents who married at a young age

10.11591/ijphs.v15i3.26734
Desta Ayu Cahya Rosyida , Nyna Puspita Ningrum , Nina Hidayatunnikmah , Solichatin Solichatin
Physical maturity and the incidence of anemia in adolescents who marry at a young age have an impact on the biological and physiological unpreparedness of the adolescent body that is not yet fully mature against the increased risk of anemia, especially in early pregnancy. The solution in this paper provides health education and increased awareness of the dangers of early marriage to physical health, especially the risk of anemia. Nutrition intervention programs and iron supplements for adolescent girls. The purpose of this study was to evaluate the effect of physical maturity on the incidence of anemia in adolescents who marry at a young age. Quantitative research method with quasi-experimental pre-post test design with control group. The population of the study was 54 young women who were married at a young age. The sample size of 44 respondents. Sampling was done using the accidental technique. Data were analyzed using the Chi-square test. The difference in mean hemoglobin levels in adolescents before and after the intervention was analyzed using the paired t-test. Based on the results of statistical test, a p-value of 0.000 was obtained (p-value ≤ 0.05), which indicated that the difference was statistically significant.
Volume: 15
Issue: 3
Page: 777-786
Publish at: 2026-09-01

Association between exclusive breastfeeding and stunting among toddlers in a high-burden rural community of South Central Timor: a cross-sectional study

10.11591/ijphs.v15i3.26943
Roslin E. M. Sormin , Emanuel Gerald Alan Rahmat
This cross-sectional study assessed the relationship between exclusive breastfeeding and stunting among toddlers in Batuputih, South-Central Timor, East Nusa Tenggara, Indonesia. Conducted in July 2025, it involved 52 children aged 6-59 months using total sampling. Exclusive breastfeeding history was obtained through caregiver interviews and verified with health records to reduce recall bias. Height-for-age z-scores were measured using WHO standards, and data were analyzed with Fisher’s exact test and penalized logistic regression with Firth correction to address the small sample size. Stunting prevalence was 59.6%, while exclusive breastfeeding coverage reached 82.7%. All toddlers who were not exclusively breastfed were stunted. Regression analysis confirmed a strong protective effect of exclusive breastfeeding against stunting (OR 0.05; 95% CI 0.003-0.92; p = 0.012), which remained significant after adjusting for birth weight, sex, recent illness, and maternal education. These findings highlight exclusive breastfeeding as a critical protective factor in high-burden rural settings. Yet, the persistence of stunting despite high coverage underscores the need for integrated strategies at the primary health-care and district levels. Strengthening breastfeeding counseling must be complemented by maternal nutrition, infection prevention, and sanitation improvements within broader stunting prevention frameworks tailored to rural Timorese communities.
Volume: 15
Issue: 3
Page: 745-752
Publish at: 2026-09-01

Analysis of charge transport kinetics in photovoltaic based on FTO@TiO2@CdS:Cu²⁺@ZnS photoanode

10.11591/ijape.v15.i3.pp1064-1071
Thai Van Thanh , Nguyen Van Minh , Ho Minh Trung
This study examines charge-transport kinetics in TiO₂@CdS:Cu²⁺@ZnS quantum dot-sensitized solar cells, addressing a key research gap regarding how controlled Cu²⁺ incorporation simultaneously affects recombination dynamics and interfacial charge-transfer resistances. While previous works mainly emphasized optical improvements from Cu doping, the coupled effects on impedance characteristics and device performance remain insufficiently clarified. Cu-doped CdS quantum dots with concentrations ranging from 0 to 0.5 mol were synthesized via the SILAR method and protected with a ZnS passivation layer. Electrochemical impedance spectroscopy and I-V characterization were employed to quantify changes in Rct1, Rct2, Jsc, Voc, fill factor, and power conversion efficiency. The optimal Cu(0.2) device achieved 4.69% efficiency with a Jsc of 27.4 mA/cm², reflecting enhanced charge transport, reduced recombination, and improved light absorption. The findings reveal the previously underexplored dual role of Cu doping in tuning both optical and electronic properties. Furthermore, they identify the threshold at which excessive Cu leads to recombination-dominated losses and structural degradation. This work establishes a clearer mechanistic basis for engineering high-performance quantum absorber architectures in next-generation solar cell technologies.
Volume: 15
Issue: 3
Page: 1064-1071
Publish at: 2026-09-01

Microplastic exposure in anchovies: baseline evidence from small-island waters of Indonesia

10.11591/ijphs.v15i3.27108
Veronika Amelia Simbolon , Erpina Santi Meliana Nadeak , Demsa Simbolon , Ristina Rosauli Harianja
Microplastics are emerging contaminants in aquatic environments and may enter human exposure pathways through seafood consumption. However, baseline exposure data for small pelagic fish in small-island settings remain limited, particularly in Indonesia. Anchovy (Stolephorus spp.), which is commonly consumed whole, may represent a direct dietary exposure pathway. This study aimed to quantify and characterize microplastic contamination in anchovy collected from Dendun Island waters. A descriptive cross-sectional study was conducted in 2025 using 100 anchovy samples obtained from local catches. Microplastics were extracted using oxidative digestion followed by density separation, filtration, and stereomicroscopic observation. Data were analyzed descriptively. A total of 109 microplastic particles were identified, with a mean abundance of 1.09 particles per individual. Fibres dominated (67.0%), followed by films (20.2%) and fragments (12.8%). Various colours were observed, indicating heterogeneous particle characteristics. This study provides baseline evidence of microplastic contamination in anchovy from a small-island coastal setting, highlighting its potential as a dietary exposure pathway. These findings support the need for routine monitoring and strengthened plastic pollution control strategies to protect seafood safety and public health.
Volume: 15
Issue: 3
Page: 860-867
Publish at: 2026-09-01

Predictors of blood pressure among adults: the role of lifestyle and body composition

10.11591/ijphs.v15i3.27128
Evelin Malinti , Yunus Elon , Mori Agustina br Perangin-angin
Hypertension is influenced by multiple biological and behavioral factors; however, the relative contributions of body age and body composition remain unclear. This study examined the associations of lifestyle behaviors, body age, and body composition with blood pressure among 167 adults in Indonesia using a cross-sectional design. Lifestyle score, body age, body mass index (BMI), skeletal muscle mass, total body fat percentage, and blood pressure were assessed using standardized procedures. Spearman correlation and multiple linear regression analyses were performed. Body age was the only significant predictor of systolic blood pressure (β = .311, p = .002). In contrast, skeletal muscle mass (β = .172, p = .030) and total body fat percentage (β = .248, p = .017) were significant positive predictors of diastolic blood pressure. Lifestyle score and BMI were not significant predictors in the regression models. These findings suggest that physiological aging and body composition are more strongly associated with blood pressure than lifestyle behaviors. Incorporating body age and body composition assessments into cardiovascular risk screening may improve hypertension prevention and early intervention strategies.
Volume: 15
Issue: 3
Page: 669-677
Publish at: 2026-09-01
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