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29,758 Article Results

Analytical formulation of relationship between ionization current and extracted ion beam current in a Penning ion source

10.11591/ijpeds.v17.i1.pp629-639
Silakhuddin Silakhuddin , Idrus Abdul Kudus , Bambang Murdaka Eka Jati , Dwi Satya Palupi , Taufik Taufik , Emy Mulyani , Heranudin Heranudin
A study on the performance of the Penning-type internal ion source of the DECY-13 cyclotron has been conducted to evaluate the relationship between cathode current and extracted ion beam current, as well as the stability of the extracted beam. The DECY-13 cyclotron, developed at the Research Center of Accelerator Technology, BRIN, is designed to produce 13 MeV protons for radioisotope production. In the experiment, the cathode current was varied between 200-400 mA, while the magnetic field and extraction voltage at 1.25 T and 3 kV, respectively. The results indicate a clear power-law dependence between cathode current (Ic) and extracted beam current (Iext), expressed as Iext=343.8 Ic^1.42 . This relationship suggests that ionization efficiency increases sharply with cathode current. Stability tests at 400 mA cathode current showed that the extracted beam current remained stable at ~70 μA over 45 minutes, with only minor fluctuations. These findings demonstrate that cathode current is an effective parameter for controlling extracted beam current. The results contribute to a better understanding of ion source behavior in cyclotron systems and provide a foundation for further optimization of Penning ion sources for radioisotope production.
Volume: 17
Issue: 1
Page: 629-639
Publish at: 2026-03-01

Enhancing SAPF performance with VOC and SVM for electrical networks depollution

10.11591/ijpeds.v17.i1.pp593-601
Kamal Bayoude , Mohamed Moutchou , Yassine Zahraoui
This paper presents a significant enhancement in the filtering performance of shunt active power filters (SAPF) by leveraging the voltage oriented control(VOC) in combination with a three-level NPC inverter using space vector modulation (SVM). The VOC technique enables precise control of the SAPF by utilizing the orientation of the voltages, thereby optimizing harmonic compensation and reference tracking. Incorporating a three-level inverter allows for more refined voltage modulation, resulting in a substantial reduction in injected harmonic content. Simulation results from MATLAB/Simulink demonstrate the effectiveness of this approach. Before compensation, the measured total harmonic distortion (THD) reaches 27.98%, exceeding the IEEE 519-1992 standard threshold of 5%. However, after applying the SAPF, the THD drops to 0.85%, aligning with international standards for power quality. The figures included in the study illustrate the stability of the phase-locked loop(PLL)voltages and the noticeable improvement in the source current waveforms, which exhibit a near-sinusoidal profile after filtering. These findings validate the superiority of the VOC strategy coupled with an NPC inverter and SVM in effectively mitigating harmonic distortions and enhancing power quality in modern electrical networks.
Volume: 17
Issue: 1
Page: 593-601
Publish at: 2026-03-01

Linearity analysis of a brushed DC machine thermal system in response to speed input using transfer function

10.11591/ijpeds.v17.i1.pp95-106
M. S. Mat Jahak , M. A. H. Rasid
This study represents a preliminary step toward developing a real-time condition monitoring system for brushed DC machines by analyzing the linearity of their thermal behavior. The temperature response of an MY1016 DC motor was collected under no-load conditions at five different speed levels, ranging from 20% to 100% of the rated speed, until the motor reached steady-state conditions to emphasize the temperature increase due to speed variability. A transfer function model was identified using MATLAB’s System Identification Toolbox, and the system’s linearity was evaluated by analyzing the spread of pole values across different speeds. Results showed significant variability in the coefficient of variation (CV) for key components, with values ranging from 0.18 for the casing to 0.84 for the brush. These findings reveal significant deviations from linear thermal behavior, indicating that a single linear transfer function may be insufficient to model the system. This research highlights the need to validate linearity assumptions in thermal modeling and introduces a framework for assessing thermal variability under varying speed conditions.
Volume: 17
Issue: 1
Page: 95-106
Publish at: 2026-03-01

DCNNVA: a deep convolutional neural network for volcanic activity classification using satellite imagery

10.11591/ijaas.v15.i1.pp281-292
Yasir Hussein Shakir , Reem Ali Mutlag , Eshaq Aziz Awadh AL Mandhari , Mohamed Shabbir Abdulnabi
Monitoring and classifying volcanic activity are a critical task for disaster risk reduction and hazard management. Recent discoveries in machine learning and deep learning have proved excellent satellite image classification and volcanic anomaly identification capabilities, yet the majority of existing methods suffer from small datasets, particularly on solitary data modalities or particular cases, merely as examples. In this research work, we put forward develop deep convolutional neural network for volcanic activity (DCNNVA) classification specifically designed for satellite imagery on volcanic activity. We rigorously benchmarked DCNNVA model's strength against a total of eight state-of-the-art transfer learning models: ResNet50, NASNetLarge, DenseNet121, MobileNet, InceptionV3, Xception, VGG19, and VGG16. Comparative experimental results show that proposed DCNNVA framework's overall performance significantly surpasses its competitors with an accuracy of 99.33%, precision of 100%, recall of 98.67%, and F1-score of 99.33%, significantly beating existing state-of-the-art methods. Also, we create a deployable graphical user interface (GUI) system that is capable of real-time monitoring on volcanic activity and generates multi-modal alert processing that can make this research directly applicable for practical use on disaster management as well as in early warning systems. This research contributes a scalable, strong, as well as practical solution towards volcanic hazard identification as well as a baseline system toward developing future multi-modal as well as real-time geohazard tracking system frameworks.
Volume: 15
Issue: 1
Page: 281-292
Publish at: 2026-03-01

Development of a mathematical model for electric drive dynamics in belt conveyors: A Simulink-based analysis of transient behavior

10.11591/ijpeds.v17.i1.pp69-81
Khalaf Y. Alzyoud , Jawdat S. Alkasassbeh , Ayman Y. Al-Rawashdeh , Vlademer Е. Pavlov
This paper presents a detailed study of developing a mathematical model and experimental analysis of electric drive processes in belt conveyors. The proposed model simplifies the complex real mechanical system by substituting distributed parameters, such as the transported load's mass and the traction element's elasticity, with concentrated equivalents. A comprehensive investigation of key transient processes including stator currents speed, torque and resistance forces was performed using MATLAB's Simulink environment. The findings reveal significant differences in performance between the initial startup phase and operation under loaded conditions. To validate the model's accuracy, the authors employed numerical analyses utilizing regression metrics such as root mean square error (RMSE) and correlation coefficients. The results show that the proposed model significantly outperforms similar models in the literature with a notable RMSE of 12.5 A for stator current, reflecting an 18% improvement and 8.7 Nm for torque prediction, indicating a 15% enhancement. Furthermore, the model achieved a correlation coefficient of 0.98, confirming its high accuracy in experimental data fitting. By effectively capturing oscillatory phenomena during both unloaded and loaded startup conditions, this work establishes the model as a reliable representation of belt conveyor dynamics, setting a new benchmark in the field.
Volume: 17
Issue: 1
Page: 69-81
Publish at: 2026-03-01

Temperature and pH effects on bioethanol production from wild cassava (Manihot glaziovii Muell. Arg) using simultaneous co-fermentation

10.11591/ijaas.v15.i1.pp227-235
Ida Ayu Pridari Tantri , Ida Bagus Wayan Gunam , Anak Agung Made Dewi Anggreni , I Gede Arya Sujana
Bioethanol is a clean alternative energy source, with wild cassava (Manihot glaziovii Muell. Arg) as a potential feedstock. Fermentation converts glucose from hydrolysis into ethanol. This study examines the effects of pH and fermentation temperature on bioethanol characteristics using a simultaneous saccharification and co-fermentation (SSCF) technique. A factorial randomized block design (RBD) was used with two factors: pH (4.5, 5.0, and 5.5) and fermentation temperature (30, 32.5, and 35 °C). Data were analyzed using variance and Duncan’s test. Results showed that pH and temperature significantly affected pH value, total soluble solids, reducing sugar, and ethanol content. The optimal conditions for bioethanol production were pH 4.5 and temperature 32.5 °C, yielding a pH of 3.55±0.07, total soluble solids of 9.3±0.57 °Brix, reducing sugar of 3.038±0.10 mg/mL, and ethanol content of 3.48±0.37 (%w/v). Based on the results of this study, wild cassava can be utilized as bioethanol by considering the effect of fermentation conditions.
Volume: 15
Issue: 1
Page: 227-235
Publish at: 2026-03-01

Modulation and performance analysis of two-wheeler electric vehicle

10.11591/ijape.v15.i1.pp186-194
Debani Prasad Mishra , Rudranarayan Senapati , Pavan Kumar , Lakshay Bhardwaj , Surender Reddy Salkuti
When compared to traditional cars, electric vehicles (EVs) have less pollution, better fuel efficiency, and are better for the environment. This essay explores the evolution of EVs in great detail, emphasizing their vital role in lowering CO2 emissions and promoting sustainability. It builds a dynamic model for EVs using MATLAB/Simulink, which explains the state of charge (SOC) and range prediction. The study emphasizes the importance of EVs in promoting a sustainable future by thoroughly covering design details, modeling, and a scientific methodology. Through the use of modeling to clarify technical aspects and highlight the significance of EV adoption, this study highlights the vital role that EVs play in reducing environmental impact and advancing environmentally friendly transportation. It highlights EVs' potential to revolutionize the automobile sector while promoting cleaner modes of transportation. It offers a thorough overview of EV production and usage and fervently promotes their wider acceptance as a means of laying the groundwork for a more sustainable and clean future.
Volume: 15
Issue: 1
Page: 186-194
Publish at: 2026-03-01

Hydrothermal synthesis and defect-driven optical characterization of CdS nanoparticles for semiconductor and solar applications

10.11591/ijape.v15.i1.pp440-448
Deepti Bhargava , R. K. N. R. Manepalli , M. C. Rao , P. Venkata Ramana Rao , N. S. Subba Rao , A. Narendra Babu , P. Sree Brahmanandam
Nanoparticles (NPs) play a crucial role in advancing technology, particularly by enhancing the performance of energy storage in semiconductor applications. The synthesis of NPs with reduced particle size and increased surface area, along with a higher number of active sites, facilitates improved ion diffusion, making them highly suitable for such applications. Various methods have been employed to reduce the size of NPs, depending on factors such as purity and controlled composition. The present study focuses on controlling both the size and composition of cadmium sulfide (CdS) NPs, aiming to achieve a high surface-to-volume ratio. These NPs were synthesized using a hydrothermal method in a high-pressure autoclave. The evaluation of the synthesized inorganic CdS-NPs for technological applications requires experimental validation of their characteristics, including particle size, energy band gap, thermal stability, temperature response, as well as optical and electronic properties. The results obtained using the proposed methods reveal a bandgap of 2.28 eV, a hexagonal wurtzite structure with an average crystallite size of 10.26 nm, reduced effective mass, and an intense absorption peak at a higher wavelength. These characteristics indicate that the synthesized CdS nanoparticles are suitable for various applications, including high-power semiconductors, solar energy harvesting, optoelectronic devices, and materials for energy and electrical engineering.
Volume: 15
Issue: 1
Page: 440-448
Publish at: 2026-03-01

Robust SOC estimation for lithium-ion batteries under faulty charging scenarios using sliding mode observer techniques

10.11591/ijape.v15.i1.pp46-58
Soulef Mahiddine , Abdelghani Djeddi , Dib Djalel
With the growing demand for electric vehicles, embedded electronics, and renewable energy applications, lithium-ion batteries have become an essential component in modern energy storage systems. Accurate state of charge (SOC) estimation is crucial for ensuring battery reliability, longevity, and safety, particularly under faulty charging conditions—a challenge where many conventional estimation techniques fall short due to model limitations or lack of robustness. In this study, we propose an advanced SOC estimation approach based on a sliding mode observer (SMO) integrated with a third-order equivalent circuit model (ECM). Unlike conventional methods, which either focus on SOC estimation without considering battery voltage or apply SMO techniques only to second-order models, our approach enhances estimation accuracy by incorporating a higher-order model that better captures the complex battery dynamics. The proposed methodology is tested under both normal and faulty charging conditions, demonstrating superior performance in estimating both SOC and terminal voltage over extended periods. The simulation results confirm the robustness of the method, with accurate SOC tracking even in the presence of charging current faults, making it a viable solution for real-world applications in battery management systems (BMS). This work contributes to improving fault-tolerant SOC estimation strategies, advancing the development of safer and more efficient energy storage technologies.
Volume: 15
Issue: 1
Page: 46-58
Publish at: 2026-03-01

Trapezoidal PWM scheme for voltage gain inverter

10.11591/ijape.v15.i1.pp90-97
Harikrishna Naraboyana , I. Kumaraswamy
The trapezoidal modulating wave-based high voltage gain 9-level inverter (HVG9LI) addresses significant difficulties related to the growing usage of capacitors, DC sources, and semiconductor switches. The proposed HVG9LI generates a nine-level resultant voltage with few components, exhibiting the capacity to double the output voltage gain. Furthermore, the HVG9LI utilizes a trapezoidal modulating wave and variable frequency carrier (TM-VFC) pulse width modulation method to increase the resulting voltage and enhance the voltage output quality. The performance and practicability of the HVG9LI with TM-VFC are evaluated across several modulation techniques and indices implemented by using MATLAB/SIMULINK and tested experimentally.
Volume: 15
Issue: 1
Page: 90-97
Publish at: 2026-03-01

The current status of the hydrogen value chain in India: a critical review

10.11591/ijape.v15.i1.pp110-119
Shyamsing Thakur , Lalitrao Amrutsagar , Dipankar Kakati , Vijaykumar Kisan Javanjal , Kuldeep A. Mahajan , Dipali B. Tawar
The Bharat is the largest economy with a humongous population that has increasing energy demands day by day. Clean energy sources like green hydrogen are necessary to balance climate change and meet energy demand, which also reduce carbon footprints in related energy sectors. This paper critically reviews the need of green hydrogen, production, storage and transportation strategies, the role of government schemes, and prominent private corporations working in the Indian green hydrogen sector. Efforts are made to analyze available data and current advisory regulations pertaining to the green hydrogen ecosystem in India. Based on this, suggestions are made for a research and development roadmap for establishing a green hydrogen value chain. This research paper suggests salt caverns as potential geological structures for hydrogen storage chains and also sheds light on potential collaborative initiatives and pilot projects for improving the efficiency and sustainability of the green hydrogen value chain across developing countries like India.
Volume: 15
Issue: 1
Page: 110-119
Publish at: 2026-03-01

Feature transformation with ensemble learning for power grid stability in sustainable energy and industry systems

10.11591/ijape.v15.i1.pp298-307
Sirish Kumar Pagoti , Kavitha Kapala , Thikka Rama Kanaka Durga Vara Prasad , Chukka Rajasekhar , Krishna Rao Pedada , Sai Kiran Oruganti
Power grids today operate under unpredictable and rapidly changing conditions, making reliable stability prediction increasingly important. This study evaluates two hybrid learning frameworks that integrate deep feature transformation with ensemble classification. In the first framework, an autoencoder (AE) is used for feature encoding before classification with extreme gradient boosting (XGBoost), while the second applies a TabTransformer (TT) followed by the same classifier. For comparison, conventional ensemble models, including random forest and standalone LightGBM, are also assessed. The models are tested on a large public dataset using stratified cross-validation and standard performance metrics. Results show that the AE-XGBoost hybrid achieves the highest performance, with a test accuracy of 97.73% and an F1-score of 0.98 for both stable and unstable states. LightGBM also performs strongly, offering consistent accuracy (95.8%) and good interpretability. In contrast, TT-XGBoost, despite its architectural novelty, achieves lower accuracy (89.4%) and struggles with unstable states. These findings highlight that model effectiveness depends not only on architectural complexity but also on the synergy between feature transformation and classification. The results provide practical insights for building dependable, confidence-aware predictive systems to support smart grid decision-making.
Volume: 15
Issue: 1
Page: 298-307
Publish at: 2026-03-01

Blade number and angle effect the archimedes spiral wind turbine performance

10.11591/ijape.v15.i1.pp393-402
Rosadila Febritasari , Muhammad Ibnul Abidin
The efficiency and performance of Archimedes spiral wind turbine (ASWT) are affected by the design and number of turbine blades which can convert the kinetic energy of the wind into mechanical energy to turn a generator that can produce electricity as much as possible in low wind speed. This study aims to obtain the optimal ASWT design in low wind speed in terms of aerodynamic performance. The method is conducted by numerically computational fluid dynamics (CFD) simulation on the fixed-opening angle and the blades number variations. The results show that the smallest C_D value is -2.18 at the 65° of opening angle, the largest C_L value at the 45° of opening angle is 0.37, and the largest C_M value is 0.61 at the 65° of opening angle and 4 blades. Therefore, it can be concluded that the Archimedes wind turbine with 4 blades and 65° pitch is the optimal.
Volume: 15
Issue: 1
Page: 393-402
Publish at: 2026-03-01

Artificial neural network-optimized bridgeless Landsman converter for enhanced power factor correction in electric vehicle applications

10.11591/ijape.v15.i1.pp238-247
Podila Purna Chandra Rao , Radhakrishnan Anandhakumar , T. Vijay Muni , L. Shanmukha Rao
Electric vehicles (EVs) are gaining popularity globally due to their energy-efficient battery storage systems, low carbon emissions, and eco-friendly operation. By transforming both the transportation and electrical sectors, EVs could create a synergistic relationship that reduces fossil fuel use and improves renewable energy integration. However, this convergence emphasizes the necessity for appropriate power factor correction (PFC) methods, especially in EV battery charging systems, to alleviate supply-end PQ concerns. Use of a bridgeless Landsman converter (BLC), noted for its efficiency and link voltage monitoring, is innovative in this research. A proportional-integral (PI) controller tuned by an artificial neural network (ANN) improves prediction and classification, especially response time. The ANN-based PI controller optimises system performance in real time using adaptive control. Using a hysteresis controller attached to a pulse width modulation (PWM) generator regulates the converter's steady-state switching frequency for accurate and consistent output. The proposed approach reduces harmonic distortions and improves operating efficiency. This comprehensive architecture improves power factor and addresses significant PQ concerns in EV charging infrastructure. Integrating improved control tactics and converter design shows that this approach may support electric car technology developments. MATLAB simulations show that power factor correction (PFC) charges EV batteries quickly and effectively. Findings suggest the technique could increase power quality, system efficiency, and EV uptake.
Volume: 15
Issue: 1
Page: 238-247
Publish at: 2026-03-01

A novel 9-level fourfold-boost switched capacitor inverter (N9L-FBSCI) configuration utilizing fewer components and optimized active switches

10.11591/ijape.v15.i1.pp132-140
N. Subhashchandrabose , I. Kumaraswamy
Multilevel inverter (MLI) topologies are more important in high-voltage applications where the most common design tends to have significant disadvantages, including being very component when it comes to the switch voltage stress, control scheme, and also not self-voltage balanced. These problems lead to higher cost, lower efficiency, and lower reliability. This paper will therefore develop a new nine-level fourfold-boost switched capacitor inverter (N9L-FBSCI) without increasing the number of components but ensures greater voltage gains and ease of use. It uses only one DC source, eight active switches, and two capacitors with a self-balancing mechanism of the voltage, avoiding extra balancing of the voltage. A four fold voltage gain is achieved using fewer switching devices per stage and less blocking voltage to control across switches. An efficient control is achieved by a level-shifted phase disposition PWM (LS-PDPWM) technique. Analytical and comparative testing against recent MLI design proves that the topology proposed has better voltage boosting and efficiency using the least number of components. Simulation and experimental verification prove the practical efficiency of the N9L-FBSCI, which can achieve a 400 V peak output with low total harmonic distortion. The topology has a high potential in renewable and industrial fields with cost effective high performance. Experimental and simulation data support an output voltage of 400 V at an output load current of 2 A with RL loading (100 Ω, 100 mH) delivering 400 W power output. The efficiency in the case of the inverter reaches its peak at 97.84% and voltage and current total harmonic distortion (THD) of 16% and 6%, correspondingly. The present proposed N9L-FBSCI has a better voltage gain and fewer components than available nine-level topologies without altering the delight of the wave position.
Volume: 15
Issue: 1
Page: 132-140
Publish at: 2026-03-01
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