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[Experimental validation of virtual flux concept in direct power control with dynamic performance ]]>
<![CDATA[Hariri, Muhammad Hafeez Mohamed]]>;
<![CDATA[Yusoff, Nor Azizah Mohd]]>;
<![CDATA[Aihsan, Muhammad Zaid]]>;
<![CDATA[Sutikno, Tole]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 4: December 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i4.pp2509-2520
<![CDATA[The virtual-flux direct power control (VFDPC) technique is a sensorless control approach aimed at improving the performance of grid-connected power converters. The approach involves simulating the grid voltage and AC-side inductors similar to an AC motor drive system, a principle deriving from direct torque control (DTC). The basic idea of VFDPC is to indirectly estimate the voltage at the converter's input through the concept of virtual flux, enabling the real-time calculation of instantaneous active and reactive power without necessitating direct voltage measurements. An essential element of the VFDPC approach is the implementation of a lookup table, used as a decision-making tool that identifies the most suitable voltage vector (a particular output state of the converter) in accordance with real-time power conditions. This provides instantaneous and smooth control of power flow, leading to enhanced operational stability. This approach allows for continual optimization of the converter's output, enabling VFDPC to significantly decrease total harmonic distortion (THD) while preserving reliable steady-state and dynamic performance. Experimental validation demonstrates that incorporating real-time feedback into virtual flux estimates improves the precision of voltage prediction and the responsiveness of the power control system. Consequently, VFDPC exhibits enhanced adaptability for various grid and load situations, presenting an appropriate choice for current power systems that demand efficient, reliable, and sensorless operation.]]>
<![CDATA[Design and implementation of IoT-based soft starter for induction motor ]]>
<![CDATA[Khudhur, Laith Najem Abood]]>;
<![CDATA[Chlaihawi, Amer Abdulmahdi Jabbar]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 4: December 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i4.pp2170-2177
<![CDATA[The practical application of the induction motor is an essential part of electrical engineering. A direct connection of the motors to the mains voltage negatively affects both the motor itself and the mains system as a whole due to high starting current values, as a result, more accidents and shortening the drive system service life. This article discusses the development of designing and implementing of soft starter single-phase IM to reduce the inrush current using the firing angle reduction technique with remote monitoring and control using the ESP32 (node MCU) and Arduino Due microcontrollers. The integration of IoT-based tools software such as VS Code, enables the remote monitoring and control of motor features. Testing shows that the system effectively facilitates remote motor control, providing a flexible and accessible learning environment with minimum starting current, solving the inrush current problem facing IMs. The proposed soft starter gives three cases of firing angle reduction that show a percentage reduction in starting current for these cases (case I, case II, and case III) are 51%, 54% and 64%, respectively. Case III has a maximum starting current is 2.2 A compared to 6.2 A for direct connecting of IM to the power supply (DOL).]]>
<![CDATA[Design and analysis of brushless permanent magnet motor for light electrically powered two-wheeler vehicle ]]>
<![CDATA[Yu, How Xuan]]>;
<![CDATA[Jamil, Mohd Luqman Mohd]]>;
<![CDATA[Said, Nurul Ain Mohd]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 4: December 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i4.pp2296-2306
<![CDATA[This study provides a comprehensive process of designing an electric motor that will be used for a small two-wheeled electric vehicle. Due to high performance capability in term of power and torque, brushless permanent magnet topology is chosen so that a compromise between size constraint and performance can be met. For an accurate motor design sizing, the design process is initially carried out by determination of power rating that derived from vehicle dynamic calculation. Based on winding factor calculation, fractional-slot 12-slot/10-pole and 9-slot/10-pole motors equipped with non-overlapping winding are chosen and analyzed using finite element analysis (FEA) software. For an optimum electromagnetic performance, parametric optimization is included, mainly on the stator dimension. Despite the performance of both designs improved, only 9-slot motor results a convincing performance as the rated torque is 18% higher than the 12-slot design. For verification purpose, 1-D analytical solution is also included and compared with results deduced by the FEA. According to the analysis, the proposed motor designs are adequately reliable for a light electrically powered electric vehicle application.]]>
<![CDATA[Bidirectional power converter for electrical vehicle with battery charging and smart battery management system ]]>
<![CDATA[Rajanna, Bodapati Venkata]]>;
<![CDATA[Krishnaiah, Kondragunta Rama]]>;
<![CDATA[Reddy, Ganta Raghotham]]>;
<![CDATA[Ahammad, Shaik Hasane]]>;
<![CDATA[Najumunnisa, Mohammad]]>;
<![CDATA[Inthiyaz, Syed]]>;
<![CDATA[Eragamreddy, Gouthami]]>;
<![CDATA[Sudhakar, Ambarapu]]>;
<![CDATA[Kolukula, Nitalaksheswara Rao]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 4: December 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i4.pp2592-2604
<![CDATA[In electric vehicles (EVs), efficient energy management is critical for reliable power transfer between the battery and motor. This paper presents the design and implementation of a bidirectional DC-DC converter equipped with a smart battery management system (BMS). The system supports bidirectional power flow, operating in boost mode during acceleration and buck mode during regenerative braking, thereby enhancing overall energy efficiency and vehicle performance. A PIC microcontroller governs the system, performing real-time monitoring of key battery parameters such as state of charge (SOC), state of health (SOH), voltage, and temperature. Safety features include automatic cooling fan activation when the temperature exceeds 45 °C and generator startup when battery voltage falls below 23 V. Real-time data is displayed via an LCD interface to improve user interaction and system transparency. The proposed system achieved a conversion efficiency of 90-93% during experimental testing, with stable switching, reliable automation, and effective thermal protection. The embedded energy management system optimizes charging and discharging cycles while preventing overcharging, deep discharge, and thermal stress. This intelligent, automated power converter enhances battery life, improves EV reliability, and contributes to sustainable transportation by enabling features like vehicle-to-grid (V2G) energy transfer. The proposed architecture is well-suited for integration into modern EV infrastructure. Although the system architecture supports future V2G integration, V2G functionality was not implemented or tested in the present experimental setup.]]>
<![CDATA[Processor-in-the-loop performance validation of a three-phase NPC three-level inverter using a novel sinusoidal PWM technique for scalar control of an induction motor ]]>
<![CDATA[N’hili, Badr]]>;
<![CDATA[Barakat, Souhail]]>;
<![CDATA[Mesbahi, Abdelouahed]]>;
<![CDATA[Khafallah, Mohamed]]>;
<![CDATA[Nouaiti, Ayoub]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 4: December 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i4.pp2257-2270
<![CDATA[This paper presents the performance of a three-phase, three-level neutral point clamped inverter driving an induction motor for variable-speed applications, compared to a two-level inverter. The studied inverter operates using a novel sinusoidal pulse width modulation technique that improves the quality of voltage and current output signals while increasing efficiency. Motor speed control is achieved using the scalar control (V/Hz) method. Experimental validation of the simulation results is performed by executing the generated C code on the F28379D DSP LaunchPad within the MATLAB/Simulink and Code Composer Studio environment, applying the processor-in-the-loop (PIL) technique.]]>
<![CDATA[Small signal modeling of restructured boost converter in continuous conduction mode ]]>
<![CDATA[Muqorobin, Anwar]]>;
<![CDATA[Wijanarko, Sulistyo]]>;
<![CDATA[Kasim, Muhammad]]>;
<![CDATA[Irasari, Pudji]]>;
<![CDATA[Wirtayasa, Ketut]]>;
<![CDATA[Widiyanto, Puji]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 4: December 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i4.pp2500-2508
<![CDATA[This paper introduces small signal modeling of the restructured boost converter (RBC) in continuous conduction mode (CCM) by using the circuit averaging technique. The averaging technique produces linear transfer functions of the converter. The transfer functions relating the duty cycle to output voltage, duty cycle to inductor current, input voltage to output voltage, and input voltage to inductor current are obtained. To validate the converter model, power simulation (PSIM) simulations are developed, and experiments are conducted. The function of RBC is similar to a conventional boost converter, i.e., to level up the input voltage. A comparative analysis between the RBC and conventional boost converter is performed. The results highlight the advantages of RBC over a conventional boost converter.]]>
<![CDATA[Advanced control architectures for enhanced simulation and operational analysis of solar PV-driven vehicle systems ]]>
<![CDATA[Mani, Raghupathi]]>;
<![CDATA[Dhanraj, Susitra]]>;
<![CDATA[Nagarajan, Karthikeyan]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 4: December 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i4.pp2615-2622
<![CDATA[Interplanetary interest in solar PV systems in automobiles has grown as renewable energy, especially in transportation subsystems, is used more widely. Emphasizing innovative control strategies to increase power conversion efficiency, reliability, and flexibility, this paper identifies and assesses solar photovoltaic integrated vehicle drive systems. In Simulink, several researchers replicate power systems, solar PV systems, vehicle propulsion systems, and power conversion technologies. To imitate real-world settings, researchers evaluate the efficiency of the device at many solar light and load values. High-level control techniques suitable in such unpredictable conditions are MPPT and dynamic load control. These controls are definitely required to ensure the correct functioning of the plant system, independent of natural variables, like irradiation and temperature. After that, the performance of the suggested control strategies is investigated under the main success criteria: energy analysis, system efficiency, and operational stability. This implies that solar PV integrated systems for automobiles could gain from ideal performance and durability, hence improving the off-grid operation of cars. These findings offered latent promise for use in the developing transportation sector and advancement of solar PV technology.]]>
<![CDATA[Robust sliding mode control of a DFIG based on the SVM strategy ]]>
<![CDATA[Yaichi, Ibrahim]]>;
<![CDATA[Elhachemi, Kouddad]]>;
<![CDATA[Mohamed, Aoumri]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 4: December 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i4.pp2711-2720
<![CDATA[This paper presents a direct power control (DPC) method for a doubly-fed induction generator (DFIG) used in variable-speed wind power systems, combining sliding mode control (SMC) with space vector modulation (SVM). The proposed SMC-based DPC with SVM (SMC-DPC_SVM) achieves decoupled power control through flux orientation, enhancing performance through the robustness of SMC and the precision of SVM. Simulation results demonstrate the effectiveness of this control strategy. The conventional direct power control (C-DPC) approach delivers fast and robust power response, and a comparative analysis between C-DPC and the proposed SMC-DPC_SVM strategy highlights the advantages of the latter. Robustness was evaluated under varying machine parameters, confirming system stability. The proposed control method was implemented and validated using MATLAB/Simulink, achieving a total harmonic distortion (THD) of less than 5%, indicating high-quality power delivery to the electrical grid.]]>
<![CDATA[Predictions of solar power using ensemble machine learning techniques ]]>
<![CDATA[Vinayagam, Arangarajan]]>;
<![CDATA[Mohandas, R.]]>;
<![CDATA[Jeyabharath, R.]]>;
<![CDATA[Mohan, B. S.]]>;
<![CDATA[Lakshmanan, Srinivasan]]>;
<![CDATA[Bharatiraja, C.]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 4: December 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i4.pp2868-2878
<![CDATA[Predicting solar power production accurately is becoming more and more crucial for efficient power management and the grid's integration of renewable energy sources. Using data from an Australian photovoltaic (PV) power station, this study employs a variety of machine learning (ML) ensemble techniques, such as gradient boosting (GB), random forest (RF), and extreme gradient boosting (XGBoost), to forecast solar power production. ML models are developed utilizing pertinent information from electricity and meteorological data in order to forecast solar power. The predictive performance of trained ML models is verified in terms of metrics like mean absolute error (MAE), root mean square error (RMSE), and correlation coefficient (R2). With higher R2 values and lower error results (MAE and RMSE), XGBoost performs better than GB and RF. Optimizing the hyperparameters of the XGBoost model significantly improves its performance. The tweaked XGBoost model shows a significant improvement in R2 (more than 5% to 10%) and error results (reduced MAE and RMSE by 0.01 to 0.06), when compared to other ensemble approaches. Compared to other ensemble approaches, the tuned XGBoost methodology is more robust and generates more accurate forecasts in solar power.]]>
<![CDATA[Adaptive intelligent PSO-Based MPPT technique for PV systems under dynamic irradiance and partial shading conditions ]]>
<![CDATA[Islam, Muhammad Gul E.]]>;
<![CDATA[Tajuddin, Mohammad Faridun Naim]]>;
<![CDATA[Azmi, Azralmukmin]]>;
<![CDATA[Hasanah, Rini Nur]]>;
<![CDATA[Ayob, Shahrin Md.]]>;
<![CDATA[Sutikno, Tole]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 4: December 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i4.pp2841-2859
<![CDATA[This research introduces an adaptive improved particle swarm optimization (AIPSO) approach for maximum power point tracking (MPPT) approach designed to enhance energy harvesting from photovoltaic (PV) systems under dynamic irradiance conditions. The proposed AIPSO algorithm addresses the challenges associated with traditional MPPT methods, particularly in scenarios characterized by fluctuating solar irradiance, such as step changes and partial shading. By incorporating a robust reinitialization strategy along with updated velocity and position equations, the algorithm demonstrates superior performance in terms of convergence accuracy, tracking speed, and tracking efficiency. This modification enables the algorithm to effectively escape local maxima and explore a wider search space, leading to improved convergence and optimal power point tracking. Furthermore, the adaptive nature of the PSO enhances the algorithm’s ability to respond to real-time changes in environmental conditions, making it particularly suitable for large- scale PV systems subjected to varying atmospheric factors. Here, “adaptive” denotes coefficient scheduling (C3) and a re-initialization trigger that responds to irradiance regime changes; “intelligent” denotes robust regime shift detection and safe duty ratio clamping. Across uniform, step change, and partial shading conditions, the proposed AIPSO achieves fast reconvergence and high tracking efficiency with negligible steady state oscillations, as summarized in the results. Building on this contribution, future research will focus on evaluating its scalability across different PV architectures and large-scale grid integration with real hardware setup.]]>
