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28,296 Article Results

Optimization of two-stage DTMOS operational transconductance amplifier with Firefly algorithm

10.11591/ijpeds.v16.i3.pp1417-1428
Udari Gnaneshwara Chary , Swathi Mummadi , Kakarla Hari Kishore
This paper presents a methodology for optimizing dynamic threshold MOSFET (DTMOS) two-stage operational transconductance amplifiers (OTAs) tailored for biomedical applications through the utilization of the Firefly algorithm. The optimization process focuses on enhancing key performance metrics such as gain, bandwidth, and power efficiency, which are critical for biomedical signal processing, neural interfaces, and wearable healthcare devices. The methodology encompasses circuit architecture definition, Firefly algorithm implementation, fitness evaluation, and result analysis. The optimization results reveal a significant enhancement in performance metrics. Specifically, the number of transistors in the design is 25. The initial overall gain was 76.65 V/V, with a power efficiency (µ) of 1.6. After optimization, the overall gain was significantly improved to 84.029 dB using the Firefly algorithm, demonstrating superior performance compared to existing algorithms. The power efficiency (µ) was also enhanced to 1.702, underscoring the efficiency improvements achieved through optimization. Simulation results and statistical analysis confirm that the Firefly algorithm effectively achieves optimal configurations, improving the robustness of OTA designs against parameter variations. These enhancements validate the algorithm's efficacy in addressing power-performance trade-offs and its suitability for diverse biomedical applications. Physical prototyping of the optimized design further demonstrates real-world functionality, underscoring its practical applicability.
Volume: 16
Issue: 3
Page: 1417-1428
Publish at: 2025-09-01

Machine learning techniques for solar energy generation prediction in photovoltaic systems

10.11591/ijpeds.v16.i3.pp2055-2062
J. Sumithra , J. C. Vinitha , M. J. Suganya , M. Anuradha , P. Sivakumar , R. Balaji
For photovoltaic (PV) systems to be as effective and dependable as they possibly can be, it is vital to make an accurate prediction of the amount of power that will be generated by the sun. Using machine learning, it is now much simpler to forecast the amount of solar energy that will be generated. These approaches are more accurate and are able to adapt to the ever changing conditions of the nature of the environment. We take a look at the most recent machine learning algorithms for predicting solar energy and examine their methodology, as well as their strengths and drawbacks, in this paper. Using performance metrics like root mean squared error (RMSE), mean absolute error (MAE), and mean squared error (MSE) makes it possible to evaluate important algorithms like support vector machines, decision trees, and linear regression. The results show that machine learning could help make predictions more accurate, lower the amount of uncertainty in operations, and help people make decisions in real time for PV systems. The study also points out important areas where research is lacking and suggests ways to move forward with the use of machine learning in systems that produce renewable energy.
Volume: 16
Issue: 3
Page: 2055-2062
Publish at: 2025-09-01

DC bus control strategy and implications for voltage source converter system

10.11591/ijpeds.v16.i3.pp1505-1515
Haider Fadel , Ahmed Abdulredha Ali , Mustafa Jameel Hameed
Significantly, the use of power electronic devices in residential and industrial settings has grown significantly in the last several years. Recent advancements in power semiconductors and microelectronics may be the main reason of their growing use in power systems for filtering, conditioning, and compensating. Additionally, the proliferation of semiconductor switches appropriate for high-power applications, and the enhancement of microelectronics enable mixed signal processing and control mechanisms. Furthermore, the concentration on renewable energy sources within the electric utility industry has emphasized the incorporation of power electronic converters into power systems. The operation and control of the regulated DC-voltage power port are examined in this work, a key part in different applications, such as STATCOM, dual mode HVDC converter systems, and aerodynamic wind energy converters with adaptive-speed optimization, emphasizing its significance in upholding a stable voltage level throughout the DC bus. The research also highlights the importance of power electronic converters within contemporary power systems, emphasizing their crucial role in facilitating effective and reliable power distribution. The obtained simulation results confirmed the efficacy of feed forward compensation in stabilizing the voltage responses of the DC bus.
Volume: 16
Issue: 3
Page: 1505-1515
Publish at: 2025-09-01

A model predictive control strategy for enhance performance of totem-pole PFC rectifier

10.11591/ijpeds.v16.i3.pp1687-1700
Le Chau Duy , Nguyen Dinh Tuyen
This paper proposed a simple but effective finite control set-based model predictive control (FCS-MPC) method to control a totem-pole bridgeless boost PFC rectifier (TBBR). The control algorithm selects from the possible switching states an appropriate one that fulfills a predefined cost function. This method also successfully eliminates the zero-crossing current distortion so that the grid current can synchronize well with the grid voltage. The theoretical analysis was presented and verified by simulation. Finally, a 3.3 kW/400 Vdc prototype was fabricated and investigated through various working conditions to realize the effectiveness of the proposed control strategy. Both simulation and experimental results show that the proposed control method can ensure accurate control of DC link output voltage and sinusoidal input current with unity power factor.
Volume: 16
Issue: 3
Page: 1687-1700
Publish at: 2025-09-01

Photovoltaic energy harvesting for the power supply of medical devices

10.11591/ijpeds.v16.i3.pp1962-1969
Hamza Abu Owida , Basem Abu Izneid , Nidal Turab
The increasing demand for sustainable and reliable power sources in portable and implantable medical devices has led to growing interest in photovoltaic (PV) energy harvesting. Traditional power sources, such as batteries, are limited by finite energy capacity and frequent replacement or recharging needs, particularly in implantable devices where surgical intervention is required for battery replacement. Photovoltaic energy harvesting, which converts light into electrical energy, offers a promising alternative, especially in environments with consistent light exposure. This review provides an in-depth analysis of the advancements in PV technologies for powering medical devices. It covers various types of PV materials, design innovations, and the integration of energy storage systems. Additionally, the review highlights the application of PV systems in both external and implantable medical devices, while addressing critical challenges such as ensuring biocompatibility, optimizing performance in low-light conditions, and miniaturizing PV systems for implantation. The potential of PV energy harvesting to improve device longevity and reduce the need for invasive procedures is emphasized. This review concludes by outlining the current challenges and future directions needed to achieve widespread clinical adoption, aiming to contribute to the development of sustainable power solutions in healthcare.
Volume: 16
Issue: 3
Page: 1962-1969
Publish at: 2025-09-01

Comparative reliability and performance analysis of PV inverters with bifacial and monofacial panels

10.11591/ijpeds.v16.i3.pp1970-1982
Muneeshwar Ramavath , Rama Krishna Puvvula Venkata
In the realm of solar energy systems, the reliability and performance of photovoltaic (PV) inverters play a critical role in ensuring efficient energy conversion and long-term operation. This study delves into a comprehensive reliability-oriented performance assessment of PV inverters, with a particular focus on the comparative analysis between bifacial and monofacial panels. Reliability evaluation is carried out by considering a yearly mission profile with a one-minute sample at Hyderabad, India. A test case of a 3-kW PV system for grid-connected applications is considered. By integrating reliability metrics with performance indicators, we aim to provide a holistic evaluation of PV inverters operating under varying conditions inherent to both panel types. The research methodology involves detailed simulations and field data analysis to capture the nuances of inverter performance influenced by the unique characteristics of bifacial panels, such as their ability to capture light from both sides, compared to the traditional monofacial panels. In this paper, performance parameters such as junction temperature, MCS, and B10 lifetime (system level (SL) and component level (CL)) are evaluated. Key findings highlight the impact of these differences on inverter reliability. The Bi-PV panel exhibits a decreasing trend. In India, CL reliability (B10) is decreased from 34 years to 1.5 years, and SL reliability (B10) is decreased from 24 years to 1 year. In comparison with monofacial panels, the thermal stress on the PV inverter due to the bifacial panel is increased, and reliability is decreased.
Volume: 16
Issue: 3
Page: 1970-1982
Publish at: 2025-09-01

Intelligent control solutions for enhancing dual-fold Luo converter efficiency in EVs

10.11591/ijpeds.v16.i3.pp1789-1800
P. Siva Subramanian , B. Marisekar , P. Mohana Karthiga , R. Ramya
This research proposes the design and application of a smart controller for a dual-fold Luo converter tailored specifically for E-vehicle applications. The dual-fold Luo converter, known for its ability to efficiently step up and step down voltage levels with reduced components, is augmented with a smart control strategy to enhance its performance in the context of electric vehicles. The smart controller utilizes advanced techniques, such as artificial neural networks or fuzzy logic, to adaptively regulate the converter's operation, thereby improving efficiency, transient response, and overall reliability. By leveraging real-time data from the E-vehicle system, the controller dynamically adjusts key parameters to optimize performance under varying load and operating conditions. Key design considerations include the selection and training of the smart controller to achieve desired voltage regulation, efficiency, and robustness in the face of uncertainties inherent in E-vehicle operation. The proposed design methodology is validated through simulation studies, demonstrating superior performance compared to conventional control techniques. The results illustrate the efficacy of the smart controller in enhancing the dynamic response of the dual-fold Luo converter, making it a promising solution for E-vehicle power management systems. This research contributes to the advancement of power electronics in electric transportation, facilitating the development of more efficient and reliable E-vehicle systems in the pursuit of sustainable mobility.
Volume: 16
Issue: 3
Page: 1789-1800
Publish at: 2025-09-01

An analytical technique for failure analysis and reliability assessment of grid daily outage performance in distributed power system

10.11591/ijpeds.v16.i3.pp1852-1864
Jacob Kehinde Ogunjuyigbe , Evans Chinemezu Ashigwuike , Kafayat Adeyemi , Ngang Bassey Ngang , Timothy Oluwaseun Araoye , Isaac Ojochogwu Onuh , Benson Stephen Adole , Solomon Bala Okoh , Iboi Endurance
This paper modeled and analyzed the reliability performance of the 132/33 kV substation in Abuja, Nigeria through the historical data collected from the APO substation using MATLAB 2021b. The probability distribution model was applied to determine the daily feeder’s outage using Reliability, availability, mean time to repair (MTR), Failure rate, distribution indices, and mean time between failures (MTBF). Due to the application of smart energy meters, the use of prepaid energy meters has helped to regulate energy demand, reduce network overloading especially during peak hours, and minimize the cost of energy consumed. There are more forced failures in the distribution system due to the switchgear and Transformer failures. There are more forced failures in the distribution system since 2013, which caused a reduction in the number of interruptions even with an increase in several customers linked to the transmission network. The result shows that the system was most available in the year 2015 with an average service availability index (ASAI) value of 98.9971%. The system was least available in year 2011 with an ASAI value of 98.6558%. The paper recommended that there should be interconnections between different feeders through proper configuration of switches or reclosers, to reduce failure occurrence in the network.
Volume: 16
Issue: 3
Page: 1852-1864
Publish at: 2025-09-01

Enhancing cancer patient care via nursing apps: a systematic review

10.11591/ijphs.v14i3.26000
Dwi Retnaningsih , Niken Sukesi , Rozaq Isnaini Nugraha , Reanita Anggis Deraya , Maulida Izzatin Ni’mah , Iva Anissya Putri , Sinta Selviana
Digital health interventions have been shown to be effective in improving the quality of life for cancer patients through education, symptom management, and psychosocial support. This research aims to identify application content that can enhance the quality of life for cancer patients. The method used is a systematic review based on the population, intervention, comparison, outcome, study design (PICOS) criteria. From the search, 941 articles were found in the JSTOR database (n = 11), Science Direct (n = 54), ProQuest (n = 609), and Springer Link (n = 267), with a publication period from 2019 to 2024. The keywords used include: nursing applications, cancer, application content, quality of life, and randomized clinical trials (RCT). The inclusion criteria encompass RCT published in peer-reviewed journals, written in English, and utilizing digital applications as interventions to improve the quality of life for cancer patients. This research includes patients aged 16-80 from various countries, including China, Turkey, Ireland, Taiwan, and Australia. The results show that digital interventions such as digital storytelling, education through applications, nurse support programs, and virtual reality significantly improve patients' quality of life. The intervention content includes six main themes: medical education, symptom management, psychosocial support, multidisciplinary interventions, physical activity, and relaxation, as well as interactive digital platforms.
Volume: 14
Issue: 3
Page: 1232-1242
Publish at: 2025-09-01

Resonant converter for fast-charging applications

10.11591/ijpeds.v16.i3.pp1832-1839
Remala Geshma Kumari , Narahari Krishna Kumari , Kankipati Shravya
Resonant converters (RCs) are gaining attention from the research community due to their significant contributions to the architecture of electric vehicle (EV) charging infrastructure. The primary part of RC is responsible for enabling constant-current (CC) charging, which helps lower inrush current, decrease losses, and improve efficiency. While the load current stays constant during charging using the CC approach, the source current grows linearly with charging time. However, pulling a high source current increases the rating of the inverter switches, which stresses them, raises their temperature, increases heat sink demand, and causes conduction loss—all of which are undesirable. Consequently, the rated CC is provided by the P2 topology of RC, which has a lower peak current source than other topologies and will improve charger performance. However, this assertion must be verified by mathematical modeling, design with theoretical calculations, specifications, and MATLAB simulation before execution. By providing a constant load current of 5 A at a DC source voltage of 200 V, the P2 RC and the conventional LCL RC are designed to compare source current values.
Volume: 16
Issue: 3
Page: 1832-1839
Publish at: 2025-09-01

Digital twin-based performance evaluation of a photovoltaic system: A real-time monitoring and optimization framework

10.11591/ijpeds.v16.i3.pp2072-2081
Mustafa Fadel , Fajer M. Alelaj
The digital twin (DT) technology implementation in photovoltaic (PV) systems provides an innovative approach to real-time performance monitoring and predictive maintenance. In this paper, an end-to-end DT framework for real-time performance analysis, fault detection, and optimization of a 250 W PV system is proposed. A physics-based equation and AI-based prediction hybrid DT model is developed through MATLAB/Simulink, trained from real data acquired by means of a testbed. The DT simulates the dynamic physical PV system behavior and adjusts itself using self-correcting algorithms to enhance precision in prediction and forecast power output at high fidelity. Results indicate that the DT gives the true response of the PV system with very small differences attributable to model approximations and sensor faults, 95% error minimization after compensation, and a root mean square error (RMSE) of 2.8 W, indicating its applicability for real-time monitoring and predictive main-maintenance. The work here focuses on the feasibility of applying DTs towards the autonomous optimization of distributed renewable energy systems.
Volume: 16
Issue: 3
Page: 2072-2081
Publish at: 2025-09-01

Investigation of optimal tilt, orientation, and tracking of a solar PV system in Iraq

10.11591/ijpeds.v16.i3.pp1914-1925
Ahmed Zurfi , Ali Abdul Razzaq Altahir , Ali Ibrahim
This paper examines the effect of tilt angle and tracking modes on energy performance of a PV system under Iraqi weather conditions. A 5-kWdc rooftop residential PV system is modeled and simulated using system advisor model (SAM) to investigate its optimal configuration of tilt angle and tracking axes for maximum energy extraction. The system is simulated with meteorological datasets for all 18 Iraqi provinces. The effect of soiling losses due to dust accumulation on incident irradiance and energy generation is considered as most Iraqi territories suffer from frequent dust storms yearly. The system annual AC energy and optimal tilt angles are evaluated and compared in five different scenarios including fixed-axis with tilt at latitude, fixed-axis with tilt at annual optimal angle, fixed-axis with tilt at monthly annual angle, one-axis tracking and dual-axis tracking. The results showed that considerable amount of energy is left unharnessed in fixed-axis scenarios when tilt angles are adjusted at latitude and optimal annual values. Using optimal monthly tilt with fixed-axis improved energy extraction by 5-6% for all locations. Energy performance is further improved with one axis tracking. Dual-axis tracking achieved highest energy yield compared to other scenarios. Overall, mid-south provinces provided highest energy opportunities among others.
Volume: 16
Issue: 3
Page: 1914-1925
Publish at: 2025-09-01

Enhancement of power quality of grid integrated photo voltaic system using active power filter

10.11591/ijpeds.v16.i3.pp2017-2029
Praveen Kamat , Anant Naik
The world's population's energy needs are growing daily, while at the same time, fossil fuels are being reduced at an alarming rate. Fossil fuel burning also increases pollution and causes global warming. Renewable energies are now being extensively used to generate electricity, so the dependence on fossil fuels is considerably reduced. Among the primary sources of alternative energy used to create power is photovoltaic (PV) technology. A grid connected PV system is the most widely recommended. When PV is linked to the grid, two main issues are the maximum power that can be taken out of it and the quality of the electricity placed into it. With the help of neural networks, the maximum power point tracking (MPPT) technology has been developed to increase the PV array's power harvesting. An active power filter (APF) had been created and analyzed using Instantaneous Reactive Power Theory, including the Chebyshev II low-pass filter. As required by IEEE 519, the total harmonic distortion (THD) with injected source current has been confirmed well within 5%. These results demonstrate that this method is a simple and efficient way to inject harmonic-free currents into the grid.
Volume: 16
Issue: 3
Page: 2017-2029
Publish at: 2025-09-01

Factors impacting high-level mobility in traumatic brain injury: a scoping review

10.11591/ijphs.v14i3.25261
Syazlin Azmi , Nor Azlin Mohd Nordin , Alia Alghwiri , Haidzir Manaf
High-level mobility is crucial for improving quality of life and ensuring active participation in daily routines and community engagement. Therefore, this scoping review explored the available evidence on factors impacting high-level mobility among traumatic brain injury (TBI) individuals and the outcome measures used to evaluate high-level mobility. Following the preferred reporting items for Systematic Reviews and Meta-analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines, five databases were searched: Scopus, Web of Science, Cochrane Library, Science Direct, and PubMed, yielding 109 articles, with eight meeting eligibility criteria. The keywords used in the search strategies were: traumatic brain injury, TBI, brain trauma, traumatic encephalopathy, and high-level mobility. This review revealed that the High-Level Mobility Assessment Tool (HiMAT) was identified as the most commonly used outcome measure for assessing high-level mobility. The key factors that may influence the outcome of high level mobility in people with TBI are age, sex, mechanism of injury, duration of post-traumatic amnesia, and individual endurance. The associations between individuals’ factors and outcomes in TBI studies exhibit significant variation. This can be attributed to several factors, including the diverse characteristics of TBI samples, different neurological recovery rates, methodological differences, timing of assessments, interactions between factors, and potential moderators.
Volume: 14
Issue: 3
Page: 1189-1200
Publish at: 2025-09-01

Oxygen/sulphur self-doped tunnel-like porous carbon from yellow bamboo for advanced supercapacitor applications

10.11591/ijpeds.v16.i3.pp2030-2042
Erman Taer , Novi Yanti , Rahma Lia Putri , Apriwandi Apriwandi , Awaludin Martin , Julnaidi Julnaidi , Nidya Chitraningrum , Ahmad Fudholi , Rika Taslim
The 3D hierarchical pore structure with tunnel-like pores is essential to the performance of porous activated carbon (AC) materials used in symmetric supercapacitors. This study aimed to effect of adding (0.3, 0.5, and 0.7) M KOH reagent and heat treatment on the formation of 3D porous, tunnel-like AC derived from yellow bamboo (YB) through N2-CO2 pyrolysis at 850 °C. The AC produced had a high concentration of nanopores, becoming a valuable storage medium with favorable physical-electrochemical properties. The results showed that 0.5-YBAC had the best physical and electrochemical properties, with a carbon purity, 89.16%, micro crystallinity of 7.374 Å, and excellent amorphous porosity. Furthermore, 3D hierarchical pore structure, enriched naturally occurring heteroatoms, dopant of oxygen (10.14%) and sulfur (0.10%). A maximum surface area of 421.99 m² g⁻¹, along with a dominant combination of micro-mesopores. The electrochemical performance test of the 0.5-YBAC electrode showed a Csp of 214 F g⁻¹, with Esp 24.7 Wh kg⁻¹ and Psp 19.2 W kg⁻¹. In conclusion, this study showed the potential of YB stems to enhance the development of supercapacitors, offering superior porosity characteristics for efficient energy storage applications.
Volume: 16
Issue: 3
Page: 2030-2042
Publish at: 2025-09-01
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