International Journal of Power Electronics and Drive Systems (IJPEDS)
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.
Articles
2,594 Documents
<![CDATA[Dynamic model and control strategies of battery-supercapacitor hybrid power sources for electric vehicles: a review ]]>
<![CDATA[Al Tahtawi, Adnan Rafi]]>;
<![CDATA[Rohman, Arief Syaichu]]>;
<![CDATA[Rusmin, Pranoto Hidaya]]>;
<![CDATA[Rizqiawan, Arwindra]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 2: June 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.11591/ijpeds.v16.i2.pp695-709
<![CDATA[The addition of a supercapacitor to electric vehicles is considered beneficial for extending battery lifetime. Due to its higher power density compared to the battery, a supercapacitor can efficiently handle sudden high-current demands. However, to achieve energy efficiency, a specific control strategy is required for this battery-supercapacitor (Batt-SC) hybrid power source (HPS). This paper reviews the dynamic model of the Batt-SC as HPS for electric vehicles and explores its various control strategies in order to achieve energy efficiency. A high-fidelity model, a control-oriented model, and an integrated dynamic model are presented. Various control strategies are then discussed, including high-level control, low-level control, and DC bus voltage regulation. This paper also identifies several key research opportunities, such as developing an integrated dynamic model of a hybrid Batt-SC electric vehicle, combining high-level and low-level control into a unified control strategy, and designing an optimal-adaptive controller that can minimize a certain performance index by considering nonlinearity factors.]]>
<![CDATA[Advanced multi-source converters for DC microgrids: integrating photovoltaic, wind, and hybrid storage systems ]]>
<![CDATA[Neelagiri, Suganthi]]>;
<![CDATA[Usha, Pasumarthi]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 2: June 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.11591/ijpeds.v16.i2.pp1261-1273
<![CDATA[This paper presents a new configuration for integrating multi-source and hybrid energy storage (HES) systems tailored for a direct current (DC) microgrid. Unlike conventional multi-input converters, the proposed design features a hybrid energy storage system combining ultracapacitors and batteries. The proposed system is intended to effectively manage power variations from wind, photovoltaic (PV) sources, and abrupt load changes. The inclusion of ultracapacitors addresses high-frequency fluctuations, thereby extending battery life and reducing the overall size of the storage unit. The control framework is designed to maintain power balance within the system, ensuring that renewable energy sources operate at their maximum power points and that energy storage is efficiently charged and discharged based on power availability. The main advantages of this configuration include: i) a reduced number of switches, ii) built-in voltage boosting and regulation for the ultracapacitor, and power-sharing between the battery and ultracapacitor, and iii) a streamlined control system with fewer components. The paper details the investigation, modeling, and design of the planned system, supported by MATLAB simulation results.]]>
<![CDATA[A novel temperature parametric method for rapid maximum power point detection in photovoltaic modules ]]>
<![CDATA[El Ouahab, Soufyane Ait]]>;
<![CDATA[Bakkali, Firdaous]]>;
<![CDATA[Amghar, Abdellah]]>;
<![CDATA[Zriouile, Rachid]]>;
<![CDATA[Sahsah, Hassan]]>;
<![CDATA[Boudouane, Meriem]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 2: June 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.11591/ijpeds.v16.i2.pp1284-1297
<![CDATA[Photovoltaic systems (PVS) exhibit variability in their maximum power point (MPP) output due to variations in irradiance and cell temperature. This can lead to reduced efficiency, as maximum power point tracking (MPPT) algorithms often have slow response times and limited ability to adapt to rapidly changing environmental conditions. New algorithms are therefore needed to capture more energy and improve the efficiency of these systems. In this context, this article presents a new method for temperature parametric (TP) and its implementation using a digital PI controller, a buck converter, and MATLAB-Simulink. This innovative approach relies on detecting the MPP by continuously measuring the cell temperature of the PV panel (????????????????????) and solar irradiance (S). A 3D linear regression model connects these two parameters with the maximum current (????????????????), enabling real-time monitoring of the MPP. We have applied this new method on two different types of PV (POLY-40W and BPSX330J) under a range of environmental conditions, including stable and dynamic scenarios. The results of the simulation demonstrate the superiority of our approach compared to the hill climbing (HC) for perturbation steps of HC (1%) and HC (2%). Our method achieves faster convergence time 0.009 s and high MPPT efficiency at 98.18%, fewer steady-state oscillations, and better detection.]]>
<![CDATA[PSO-based adaptive sliding mode control of a bidirectional DC-DC converter with an improved reaching law ]]>
<![CDATA[Cham, Julius Derghe]]>;
<![CDATA[Koffi, Francis Lénine Djanna]]>;
<![CDATA[Gabriel, Ekemb]]>;
<![CDATA[Boum, Alexandre Teplaira]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 2: June 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.11591/ijpeds.v16.i2.pp998-1011
<![CDATA[This paper explores the development of an adaptive sliding mode control (ASMC) that incorporates an improved optimal reaching law. We intend to use the proposed ASMC in DC microgrids or electric vehicle applications to regulate a bidirectional (two-way) buck-mode DC-DC converter. To initiate the design process, we develop a mathematical model of the converter operating in the charging mode. A particle swarm optimization is employed to help get the controller’s gains to better performance. By capitalizing on the benefits of an ASMC algorithm, the developed controller achieves improved reaching conditions, increased robustness, and strengthened stability. The efficacy of the suggested controller in comparison to conventional sliding mode control (CSMC) and ASMC is demonstrated through MATLAB/Simulink simulations conducted on the converter. The comparison demonstrates that the proposed controller achieves the intended transient response in steady-state conditions with minimal error and better reference tracking. The performance of the suggested controller is robust with regard to the rejection of variations in source voltage and load resistance. For applications involving DC microgrids or electric vehicles, the suggested controller will guarantee a consistent DC transit voltage.]]>
<![CDATA[Wind turbine defect detection using deep learning ]]>
<![CDATA[Somasundaram, Deepa]]>;
<![CDATA[Vanitha, M.]]>;
<![CDATA[Kumar, T. Sathish]]>;
<![CDATA[Adaikalam, I. Arul Doss]]>;
<![CDATA[Kavitha, P.]]>;
<![CDATA[Kalaivani, R.]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 2: June 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.11591/ijpeds.v16.i2.pp1348-1355
<![CDATA[Wind turbines play a critical role in the generation of renewable energy, but their maintenance and inspection, especially in large-scale wind farms, present significant challenges. Traditionally, wind turbines have been inspected manually, a process that is not only time-consuming but also costly and risky. Unmanned aerial vehicles (UAVs) have emerged as an efficient alternative, offering a safer and more economical means of gathering inspection data. However, the challenge lies in the manual analysis of the collected data, which demands expertise and considerable time. This paper proposes using object detection algorithms, specifically YOLOv8, to automate the detection of wind turbines and their defects, streamlining the inspection process. The model is trained on wind turbine images to identify potential faults such as cracks and corrosion. This approach aims to increase the accuracy and efficiency of wind turbine maintenance, ensuring prompt defect detection and reducing both operational costs and downtime.]]>
<![CDATA[A novel adaptive control scheme for dynamic voltage restorer ]]>
<![CDATA[Kiran, Tummala Kranti]]>;
<![CDATA[Rajagopal, Balakrishnan]]>;
<![CDATA[Raju, Yerramilli Butchi]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 2: June 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.11591/ijpeds.v16.i2.pp1083-1093
<![CDATA[This study introduces a novel approach to improve the performance of the dynamic voltage restorer (DVR) using a control structure based on the inverse hyperbolic sine function-based least mean square (IHSF-LMS). The proposed control structure efficiently extracts the fundamental source voltage component with rapid convergence. The primary objective of this control scheme is to enhance compensation capability and maintain load voltage stability. Key features include superior steady-state performance and heightened robustness with reduced computational complexity. This approach achieves a reduction in peak overshoot and settling time compared to the traditional LMS method. The validation of system performance is conducted through MATLAB/Simulink simulations, demonstrating compliance with the IEEE-519-2014 standards for harmonic spectra.]]>
<![CDATA[Retraction Notice: A modified circulating current suppression control based on MMC grid connected using NLM ]]>
<![CDATA[Hasan, H. A.]]>;
<![CDATA[Chillab, Riyadh Kamil]]>;
<![CDATA[Hannan, Ahmed K.]]>;
<![CDATA[Farghly, Abdelrahman]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 2: June 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.11591/ijpeds.v16.i2.pp1051-1060
<![CDATA[-----------------------------------------------------------------------------------------------Notice of RetractionAfter careful and considered review by a duly constituted expert committee, this paper has been found to be in violation of IAES Publication Principles. 1. PlagiarismThe article was found to have copied portions of content from the following Chinese paper without appropriate citation:DOI: 10.13873/J.1000-9787(2024)11-0028-05https://d.wanfangdata.com.cn/periodical/Ch9QZXJpb2RpY2FsQ0hJTmV3UzIwMjUwMTE2MTYzNjE0Eg5jZ3FqczIwMjQxMTAwOBoIM3B4b2xsZ3M%3D 2. Authorship MisconductThe Editorial Office received a formal request from Dr. Riyadh Kamil Chillab (University of Baghdad), who stated: “as I was mistakenly included as an author without my consent.” This confirms that his name was added to the article without his knowledge or approval, constituting a serious violation of authorship ethics. 3. Corresponding Author’s StatementThe submitter of the paper, Mr. Ahmed Kamil Hannan, sent multiple emails to the Editorial Office regarding manuscript ID: 23942 (“A modified circulating current suppression control based on MMC grid connected using NLM”, Vol. 16, No. 2, June 2025, DOI: 10.11591/ijpeds.v16.i2.pp1051-1060).In his communications, Mr. Hannan did not acknowledge plagiarism. Instead, he stated that the authors had “noticed scientific errors in the manuscript” and requested withdrawal of the paper. He further offered to bear all costs and assured that the manuscript would not be submitted to any other journal. Retraction DecisionIn accordance with IAES’s commitment to uphold the highest standards of academic integrity, and considering both plagiarism and authorship misconduct, the content of this article has been formally retracted from the OJS platform.----------------------------------------------------------------------------------------------- High total harmonic distortion (THD) occurs when conventional circulating current suppression and modulation strategies fail to control arm circulating current in a modular multilevel converter (MMC) controlled by a virtual synchronous generator. This paper proposed a joint circulating current suppression technique that improves the proportional resonant controller's control mode and introduces the nearest level approach modulation (NLM) strategy for arm circulating current rectification. The MATLAB/Simulink program is used to conduct the simulations. The results show that: when the grid frequency does not fluctuate, the joint suppression strategy's arm current THD is 2.79%, 0.92% lower than the quasi-proportional resonant controller's (QPRC) THD; under primary frequency modulation, the suggested strategy's THD of the a-phase current is 1.75%, 1.03% lower than the QPRC's THD. Under typical operating conditions and with primary frequency management of the grid-type MMC, the results show that the proposed combined circulating current suppression technique may successfully lower total harmonic distortion (THD), eliminate bridge arm circulating current, and improve power quality.]]>
<![CDATA[Micro short circuit fault diagnosis in Li-ion cell ]]>
<![CDATA[Gomathy, S.]]>;
<![CDATA[Dhanasekaran, Boopathi]]>;
<![CDATA[Ramasamy, Sivabalakrishnan]]>;
<![CDATA[Jayaram, Radha]]>;
<![CDATA[Muthusamy, Sabarimuthu]]>;
<![CDATA[Subramanian, A. T. Sankara]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.11591/ijpeds.v16.i3.pp2103-2111
<![CDATA[Micro short circuits (MSCs) in lithium-ion battery cells are a critical safety concern, potentially leading to thermal runaway, internal short circuits, overheating, and battery degradation. Compared to normal cells, MSC fault cells exhibit reduced capacity with each charge-discharge cycle and an increasing state of charge (SOC) deviation over time. To differentiate normal cells from MSC fault cells, a fault diagnosis method based on remaining charge capacity (RCC) estimation is proposed. After each charge discharge cycle, the cell’s RCC is compared to a safe threshold value. The method uses the charge cell voltage curve (CCVC) of a fully charged reference cell to estimate RCC via standard CCVC hypothetical conversion. This approach’s accuracy is validated in constant power and constant current charging scenarios. MSC leakage current is calculated by incrementing RCC after each charge, and then converted to MSC resistance. A MATLAB/Simulink model of a battery pack with an MSC fault was developed to test the method across various charge cut-off voltages. The diagnostic procedure’s applicability to ageing cells, constant power, and multi-step charging is further confirmed through experiments with external resistance, enhancing MSC detection before thermal runaway becomes unmanageable.]]>
<![CDATA[Improvement direct torque control of induction motor using robust intelligence artificial ANFIS speed controller ]]>
<![CDATA[Abdelhaq, Laoufi]]>;
<![CDATA[Moulay-Idriss, Chergui]]>;
<![CDATA[Chekroun, Soufiane]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.11591/ijpeds.v16.i3.pp1552-1565
<![CDATA[This paper proposes a study aimed at improving the conventional direct torque control (DTC) technique applied to induction motors (IM). The primary aim is to reduce the harmonic distortions and fluctuations associated with the electrical current, flux variations, and generated torque, while ensuring accurate speed reference tracking and ensuring optimal dynamic performance of the drive, especially under variable speed conditions. To achieve this, we introduce an intelligent control system that utilizes a hybrid neuro-fuzzy inference model (ANFIS), through the application of the back propagation method. The DTC-ANFIS technique is compared with the traditional DTC-PI method and simulated using MATLAB/Simulink in different scenarios. The obtained results reveal a significant improvement in performance over DTC-PI, with superior results over a wide speed range.]]>
<![CDATA[Predicting transmission losses using EEMD – SVR algorithm ]]>
<![CDATA[Lestari, Hesti Tri]]>;
<![CDATA[Sereati, Catherine Olivia]]>;
<![CDATA[Siregar, Marsul]]>;
<![CDATA[Bachri, Karel Octavianus]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.11591/ijpeds.v16.i3.pp2122-2129
<![CDATA[This work introduces a predictive model for evaluating transmission losses in the Java-Bali electrical system using ensemble empirical mode decomposition (EEMD) and support vector regression (SVR) techniques. Transmission losses, a critical aspect of energy efficiency, are affected by several operational aspects, such as load flow, energy composition, peak load, and meteorological factors such as transmission line temperature. Transmission losses data were decomposed into many intrinsic mode functions (IMFs) by EEMD, effectively capturing both high-frequency (short-term) and low-frequency (long-term) trends. The SVR algorithm, utilizing a radial basis function (RBF) kernel, was subsequently employed to predict the deconstructed IMFs, facilitating accurate predictions of transmission losses. The proposed EEMD-SVR model achieved a mean absolute error (MAE) of 5.43%, with the highest error observed during the period of abrupt load shifts. These results confirm the model’s strength in identifying long-term transmission loss patterns, making it suitable for system planning and operational forecasting. While the model exhibited high prediction accuracy, especially in recognizing long-term trends, it faced limitations in accurately predicting abrupt changes in transmission losses. Therefore, future improvements should aim to enhance responsiveness to sudden changes in the system dynamics. The result suggests that the EEMD SVR model can proficiently assist power system operators in monitoring and mitigating transmission losses.]]>
