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International Journal of Power Electronics and Drive Systems (IJPEDS)
Published by Institute of Advanced Engineering and Science
ISSN : -     EISSN : 20888694     DOI : -
Core Subject : Engineering,
Control & Systems Engineering Electrical & Electronics Engineering
International Journal of Power Electronics and Drive Systems (IJPEDS, ISSN: 2088-8694, a SCOPUS indexed Journal) is the official publication of the Institute of Advanced Engineering and Science (IAES). The scope of the journal includes all issues in the field of Power Electronics and drive systems. Included are techniques for advanced power semiconductor devices, control in power electronics, low and high power converters (inverters, converters, controlled and uncontrolled rectifiers), Control algorithms and techniques applied to power electronics, electromagnetic and thermal performance of electronic power converters and inverters, power quality and utility applications, renewable energy, electric machines, modelling, simulation, analysis, design and implementations of the application of power circuit components (power semiconductors, inductors, high frequency transformers, capacitors), EMI/EMC considerations, power devices and components, sensors, integration and packaging, induction motor drives, synchronous motor drives, permanent magnet motor drives, switched reluctance motor and synchronous reluctance motor drives, ASDs (adjustable speed drives), multi-phase machines and converters, applications in motor drives, electric vehicles, wind energy systems, solar, battery chargers, UPS and hybrid systems and other applications.
Arjuna Subject : -
Articles 2,781 Documents
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Performance analysis of a battery-operated electric vehicle using metaheuristic optimization Swati Sabnam Gan; Puvvula Venkata Rama Krishna
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 3: September 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v17.i3.pp1610-1619

Abstract

Battery-powered electric vehicles (BEVs) are gaining significant attention due to high energy efficiency, zero emissions, and advanced control systems. This article illustrates the performance analysis of BEV, which consists of a high-voltage battery pack, a BEV controller, a motor driver, a gearbox, and a longitudinal driver. A conventional PID controller is used as a BEV controller. Several optimal algorithms are employed for tuning the PID controller, including the Ziegler-Nichols method (ZN method), particle swarm optimization (PSO), genetic algorithm (GA), grey wolf optimization (GWO), artificial bee colony algorithm (ABC), and artificial hummingbird algorithm (AHA). The proposed research framework was assessed in terms of vehicle efficiency, battery power consumption, vehicle mileage, motor speed, and battery state of charge (SOC). Metaheuristic algorithms with PID controllers outperform conventional PID and classical ZN-PID controllers. Among all algorithms, the PID-GWO controller achieves maximum vehicle mileage, low battery power consumption, improved battery SOC, and the highest vehicle efficiency.
Stator interturn short circuit fault identification in DFIG and its analysis using an artificial neural network Vivek Kushwaha; Sanjay Kumar Maurya; Arvind Kumar Yadav
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 3: September 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v17.i3.pp1643-1658

Abstract

Inter-turn short circuit (ITSC) issues are a common electrical failure mainly caused by the deterioration of winding insulation in the machine over time. Failing to detect such issues early can lead to catastrophic consequences. This article investigates the interturn fault in the stator winding of a doubly-fed induction generator (DFIG) used in wind turbines. A flux linkage difference vector (FLDV) model is introduced in this study for fault detection. Additionally, an artificial neural network (ANN) model is proposed to classify these faults. Specifically, a short-circuit fault is induced in each phase of the stator winding, and the faults are classified by assigning different magnitudes to the respective phases. The ANN is trained to identify which phase contains an interturn fault, with output waveform amplitudes of 1, 2, or 3 corresponding to faults in phases "a," "b," and "c." If no fault is present, the waveform magnitude is designated as "0." This approach enables early fault diagnosis by analyzing waveform patterns, thereby preventing overheating caused by short circuits and avoiding severe, irreversible damage to the windings.
Enhancing scattering strength improvement and color uniformity in white light-emitting diodes using high concentration of cobalt(II) oxide Tung Vo Thanh; Phan Xuan Le; Nguyen Doan Quoc Anh
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 3: September 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v17.i3.pp1974-1981

Abstract

The study herein investigates the structural development of cobalt(II) oxide (CoO) thin films grown on Ag (0 0 1) substrates and evaluates their impact on optical performance in white light-emitting diodes (WLEDs). The structural and chemical properties of CoO films were characterized using grazing-incidence X-ray diffraction (GIXD), Xray photoelectronic spectroscopic (XPS), as well as low-power electronic diffracting (LEED). The outcomes reveal that CoO films initially grow pseudomorphically up to 3-4 monolayers, followed by gradual relaxation toward the bulk lattice parameter. A periodic mismatch dislocation network forms at approximately 8 monolayers, leading to lattice tilting and the formation of ordered nanoscale domains. In addition, the incorporation of CoO as a scattering material in WLEDs significantly improves light scattering and color uniformity, while maintaining stable luminous performance. Compared with conventional scattering materials, CoO demonstrates lower scattering loss and reduced chromatic deviation, making it a promising candidate for high-precision optoelectronic applications.
Voltage stability and PQ analysis of a PV solar grid-connected system under varying weather conditions in Oman Ahmed Said Al Busaidi; Shaik Abdul Saleem; Sakhr M. Sultan; Tilal Elrayah; Rashid Abri
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 3: September 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v17.i3.pp2149-2161

Abstract

This paper studies the voltage stability and power quality (PQ) of a 128 kW grid-connected photovoltaic (PV) system installed at a school in Al-Hamra, Oman, by using a MATLAB/Simulink model. An incremental conductance maximum power point tracking (MPPT) algorithm is used to control the duty cycle of a DC/DC boost converter and to keep the DC-link voltage almost constant at about 498 V for different solar irradiance levels. A rotating d-q control strategy is applied to the voltage source converter (VSC) to generate balanced three-phase currents with a high power factor while the PV system partly supplies an average 400 kW school load and the remaining power is taken from the local distribution network. Steady-state and transient simulations with real irradiance and temperature data are carried out to examine the system performance during sudden changes in irradiance, load, and grid conditions such as voltage sags. The results show that the proposed control scheme keeps the DC-link voltage stable, reduces overshoot during disturbances, and achieves good power quality at the point of common coupling, with THDi of about 1.45%. Although this work is based only on simulations, it confirms that the controller can operate robustly under different weather and operating conditions and can help the integration of solar PV into the Omani distribution network.
Energy analysis of bifacial photovoltaic systems on different soils and orientations in a coastal low-latitude area Ayong Hiendro; Syaifurrahman Syaifurrahman; Fitriah Fitriah; Kho Hie Khwee
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 3: September 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v17.i3.pp2058-2069

Abstract

Coastal low-latitude regions exhibit consistent annual solar irradiance, offering stable solar resource availability that enhances their suitability for year-round photovoltaic energy generation. This study analyzes the annual energy production of bifacial photovoltaic (PV) systems under varying ground albedo conditions and installation orientations, accounting for the effects of tilt angle, ground clearance height, ground coverage ratio (GCR), and row spacing. Meteorological parameters were derived from Japan's Himawari-8/9 satellite data, which were integrated into the System Advisor Model and the National Renewable Energy Laboratory database to compute front‑ and rear‑side solar irradiance. Electrical measurements from bifacial PV systems were used to evaluate annual energy output and bifacial gain. Results demonstrate that landscape-oriented bifacial PV systems consistently outperformed portrait-oriented configurations in both energy production and bifacial gain. For systems with optimized parameters, landscape orientations achieved annual energy outputs 0.70%, 0.51%, and 0.42% higher than portrait orientations for white dry sands, white sands with granite rocks, and white wet sand substrates, respectively. Similarly, bifacial gain values for landscape-oriented systems reached 18.64%, 15.47%, and 12.43% across these substrates, surpassing portrait-oriented systems. The findings highlight the crucial influence of ground albedo and panel orientation on optimizing the performance of bifacial photovoltaic systems in coastal low‑latitude regions.
Multi-output deep learning framework for joint forecasting of solar irradiance and wind speed with cross-regional transferability analysis S. Selvi; Annamalai Muthu; Murali Narayanamurthy; B. Ardly Melba Reena; Gobimohan Sivasubramanian; T. Logeswaran
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 3: September 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v17.i3.pp2101-2111

Abstract

Accurate forecasting of solar irradiance and wind speed is essential for improving hybrid renewable energy systems and ensuring grid stability. This study develops and evaluates a multi-output deep learning framework for the simultaneous prediction of global horizontal irradiance (GHI) and wind speed across multiple Indian regions. Hourly data from the National Solar Radiation Database (NSRDB) for the period 2015–2020 were used to train light gradient boosting machine (LightGBM), long short-term memory (LSTM), bidirectional long short-term memory (BiLSTM), and convolutional long short-term memory (ConvLSTM) models, with cross-regional transfer learning applied across Tamil Nadu, Kerala, Karnataka, and Andhra Pradesh. Among the models, ConvLSTM achieved the best performance with a mean absolute error (MAE) of 0.061 and an R² value of approximately 0.91, while BiLSTM demonstrated comparable accuracy with lower computational cost. The proposed framework emphasizes cross-regional transferability, demonstrating robust generalization across heterogeneous climatic conditions. Error distribution analysis further indicates improved prediction stability, with ConvLSTM exhibiting lower variability compared to other models. These results support scalable and reliable renewable energy forecasting, with practical implications for grid operation, power electronic control, and hybrid energy system management.
Modeling and four-loop master-slave control of a six-phase interleaved buck converter for ultrafast EV charging Alya H. Al-Rifaie; Mohammed Obaid Mustafa
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 3: September 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v17.i3.pp1926-1940

Abstract

In this paper, modeling and control of a six-phase interleaved buck converter (IBC) are presented for fast charging of ultra-fast electric vehicle (EV) batteries. The primary difficulty faced is the need to operate at high power charging rates with stable and efficient performance, while minimizing output ripple and current sharing errors. To solve these problems, the cascaded multi-loop control method is proposed using a proportional-integral (PI) controller. By implementing a reduced number of control loops (four coordinated loops) from conventional configurations, the control structure is simplified, while stable operation and effective current sharing are maintained. The proposed system is implemented in a constant current/constant voltage (CC-CV) charging method, which guarantees safe and efficient battery charging. The proposed system is validated by using MATLAB/Simulink simulation under steady-state and transient conditions. The results show that with a very small amount of ripple, a battery voltage of about 820 V and a charging current of 330 A are obtained. The dynamic response has a settling time of about 100 ms and an overshoot less than 5%, which is suitable for disturbances. Furthermore, in the SIMO configuration, it is noted that a disturbance or fault on the output of one of the cascaded control loops has minimal effect on the output of the other control loop, which illustrates good decoupling between cascaded control loops. This is a sign of better robustness and reliability for multi-output EV charging applications. Moreover, the stability margins of the proposed control method are verified by frequency-domain analysis.
A privacy-preserving IoT-machine learning framework for optimized and secure demand-side management in smart grids S. Pushpa; Jonnadula Narasimharao; K. L. Kishore; T. Sathish Kumar; M. Bhoopathi; R. Kalaivani
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 3: September 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v17.i3.pp2004-2012

Abstract

This paper presents an integrated internet of things (IoT) and machine learning-based framework for secure and efficient demand-side management (DSM) in modern smart grids. The proposed approach combines long short-term memory (LSTM) networks for accurate load forecasting, federated learning (FL) for decentralized privacy-preserving model training, and blockchain technology for secure and tamper-proof communication. In addition, a digital twin (DT)-assisted architecture is incorporated to enable predictive decision-making and system-level optimization. The framework explicitly considers renewable energy integration, electric vehicle (EV) charging loads, distributed energy storage, and power electronic converter constraints. Simulation results demonstrate a reduction in forecasting error by 15-25%, a 25% decrease in daily energy cost, and a 23.7% reduction in peak demand. The proposed system achieves improved voltage stability with reduced deviation and enhances overall efficiency up to 88%. Furthermore, cybersecurity performance is validated with an anomaly detection AUC of 0.95 and reduced data transmission through FL by 87%. The results confirm that the proposed framework provides a scalable, secure, and intelligent solution for next-generation smart grid applications.
DPC backstepping control applied to an active rectifier: analysis and comparison with a PIL implementation Slimane Chiboub; Mohamed Khafallah; Jawad Lamterkati
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 3: September 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v17.i3.pp1808-1821

Abstract

This paper presents a simulation and comparison of direct power control (DPC) and the new backstepping (BS) control for a three-phase PWM rectifier. The objective is to evaluate these techniques in achieving high-performance grid integration, targeting the absorption of sinusoidal current, maintaining a unity power factor, and minimizing grid current harmonics. While DPC is recognized for its fast dynamic response, it often suffers from high power ripples and variable switching frequency due to the switching table. Conversely, the proposed BS control provides superior tracking performance and improved stability margin, even under parameter uncertainties. Through detailed modeling and simulation in MATLAB/ Simulink environment, this paper analyzes key performance indicators, including current total harmonic distortion (THD), response time, and robustness, under multiple grid conditions, and validates the proposed control law using a processor-in-the-loop (PIL) implementation. The comparative study demonstrates the trade-offs between the two control methods, highlighting the advantage of backstepping control.
Analytical design, modelling and simulation of an LLC resonant converter for an electric vehicle auxiliary power module Mohamad Affan Mohd Noh; Jacques Juicy Patureau Ravina; Sivakumar Sivanesan; Hafizul Azizi Ismail; Ali Akbar Firoozi
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 3: September 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v17.i3.pp1885-1901

Abstract

This paper presents an analytical design, modelling, and simulation of an LLC resonant converter for an electric vehicle auxiliary power module (APM). The work contributes a complete LLC‑focused workflow that starts from design specifications and proceeds through: i) Resonant‑tank selection using normalized gain–frequency maps to choose the inductance ratio Ln and a quality factor Qe with soft‑switching in mind; ii) Transformer sizing from core data and loss limits; and iii) Small‑signal‑based PI controller tuning those accounts for the plant’s inherent inversion. The workflow is implemented and validated in MATLAB Simulink and PLECS for input voltages of 235-265 V and load levels from 10% to 100%. The converter achieves a peak efficiency of 98.1% within an 80.6-128.3 kHz switching range, full‑load efficiency of 93.5%, and about ±1% output voltage regulation. The controller maintains stable output settling times of 0.42-0.44 ms during 100% to 80% load steps and the reverse transition. At the highest input voltage, the switching frequency drifts beyond the intended range, which indicates a clear target for controller refinement in future work. The results show that the proposed analytical workflow is practical for designing LLC converters that meet APM efficiency and regulation goals, with cross‑platform simulation providing consistent evidence of performance.

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