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[Variable frequency drive based on full-bridge class D for single-phase induction motor ]]>
<![CDATA[Jati, Budi Pramono]]>;
<![CDATA[Hapsari, Jenny Putri]]>;
<![CDATA[Haddin, Muhamad]]>;
<![CDATA[Prasetyowati, Sri Arttini Dwi]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i3.pp1701-1710
<![CDATA[The issue with induction motors lies in speed regulation, which can be addressed by adjusting the motor voltage; however, this affects torque. In contrast, a variable frequency drive (VFD) changes the motor frequency while maintaining a constant voltage. A VFD controller with constant sinusoidal voltage and adjustable frequency can be implemented using an Arduino and a class D full-bridge MOSFET amplifier inverter. This paper discusses the electronic speed control (ESC) of induction motors using VFD regulation, demonstrating how changes in frequency affect motor speed. The system involves an induction motor controlled by a VFD comprising three main components: an AC-to-DC converter, a class-D full-bridge MOSFET inverter, and a variable-frequency sinusoidal signal source. VFDs operate with constant voltage and variable frequency. This method includes the design and testing of VFD hardware and software. The VFD components include: a class-D full-bridge switching inverter, a sinusoidal signal frequency generator (30–70 Hz), an Arduino with custom software, an SMPS power supply, and a step-up transformer. The results indicate that the class-D full-bridge inverter can effectively regulate motor speed through VFD control. The motor speed is almost directly proportional to the frequency: at 30 Hz, the speed is 860 RPM; at 50 Hz, 1472 RPM; and at 70 Hz, 2035 RPM.]]>
<![CDATA[A model predictive control strategy for enhance performance of totem-pole PFC rectifier ]]>
<![CDATA[Duy, Le Chau]]>;
<![CDATA[Tuyen, Nguyen Dinh]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i3.pp1687-1700
<![CDATA[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.]]>
<![CDATA[Investigation of optimal tilt, orientation, and tracking of a solar PV system in Iraq ]]>
<![CDATA[Zurfi, Ahmed]]>;
<![CDATA[Altahir, Ali Abdul Razzaq]]>;
<![CDATA[Ibrahim, Ali]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i3.pp1914-1925
<![CDATA[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.]]>
<![CDATA[Torque sharing function optimization for switched reluctance motor control using ant colony optimization algorithm ]]>
<![CDATA[Ismael, Dhiyaa Mohammed]]>;
<![CDATA[Atyia, Thamir Hassan]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i3.pp1537-1551
<![CDATA[Switched reluctance motors (SRMs) are gaining popularity in industrial and automotive applications due to their robust design, fault tolerance, and high torque density, particularly in wide-speed-range operations. However, SRM performance is often limited by torque ripple, speed oscillations, and inefficiencies, which can lead to mechanical stress, vibration, and acoustic noise. Addressing these challenges requires the effective optimization of control strategies. This study aims to enhance the performance of SRM drives by employing an ant colony optimization (ACO) algorithm to optimize the torque sharing function (TSF). The proposed method iteratively tunes TSF parameters to minimize torque ripple and improve speed stability under varying operating conditions. Simulation results demonstrate significant improvements: torque ripple is reduced from a range of –20 Nm to 10 Nm without optimization to below 10 Nm with ACO-based optimization. Similarly, current peaks decrease from 60 A to 5.5 A, ensuring smoother motor operation and enhanced efficiency. Comparative analysis confirms that the ACO-based TSF provides superior tracking of speed set points, reduced mechanical stress, and improved reliability, making it well-suited for high performance applications in both industrial and automotive sectors.]]>
<![CDATA[Optimizing slow-charging EV loads with a two-layer strategy to enhance split-phase voltage quality and mitigate issues in PDNs ]]>
<![CDATA[Prasad, Attada Durga]]>;
<![CDATA[Siva, Manickam]]>;
<![CDATA[Reddy, Alla Srinivasa]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i3.pp1472-1483
<![CDATA[Power distribution networks (PDN) were mostly affected by the voltage imbalances created by the slow charging of electric vehicles (EV), were there random load into the PDN system, causing split-phase voltage quality (SPVQ) issues. Hence, to mitigate the problems associated with EVs’ slow charge in distributed phases of the power system, a multi-layer charging strategy is proposed considering the following constraints in the system: voltage deviation (VD) and voltage harmonics (VH) in split phase (SP). Further multi-layer control is associated with an inner layer equipped with hybrid non-dominated sorting genetic algorithm (NSGA-II) to select the optimal phase for charging the EV and send it to the output layer where a SP current algorithm is utilized so that voltage quality can be fed in loop to inner layer so that iterations were performed to satisfy the convergence condition. Simulation results in MATLAB demonstrate a voltage unbalance (VU) reduction of up to 32.81%, a maximum VD reduction of 9.11%, and a VH reduction of 6.25% at key grid nodes. The proposed method significantly enhances PDN efficiency and maintains voltage quality within national standards across 1,000 to 5,000 EV connections. The generated results reflected the optimal improvement in SPVQ, and the harmonics content reduced further; PDN operational efficiency also improved to a greater extent.]]>
<![CDATA[Accurate state of health estimation using hybrid algorithm for electric vehicle battery pack performance and efficiency enhancement ]]>
<![CDATA[Prakhya, Rajesh Kumar]]>;
<![CDATA[Krishna, Puvvula Venkata Rama]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i3.pp1438-1445
<![CDATA[Temperature fluctuations, overcharging, and over-discharging are all issues that can cause fast deterioration, capacity loss, and thermal runaway in lithium-ion batteries (LIBs). To overcome these challenges, a hybrid model combining a stacked recurrent neural network (SRNN) and bidirectional long short-term memory (biLSTM) is presented for a reliable state of health (SoH) estimate. This model finds subtle patterns in battery data using SRNN layers to capture sequential dependencies and biLSTM modules to solve long-term temporal correlations while avoiding vanishing gradient concerns. The effectiveness of model is assessed by performance measures such as root mean square error (RMSE), mean absolute error (MAE), and maximum error (MAX), which demonstrate its superiority for precise SoH estimation. The stacked RNN-based SoH estimation achieves superior accuracy, with RMSE, MAE, and MAX error levels of 1.5%, 0.8%, and 4.84%, respectively, compared to GRU’s higher errors (3.8%, 3%, and 5.5%). Stacked RNN hierarchically processes sequential battery data, effectively capturing complex temporal relationships, and ensuring accurate and reliable SoH estimation for LIBs.]]>
<![CDATA[Synchronous generator system identification via dynamic simulation using PSS/E: Malaysian case ]]>
<![CDATA[Baswaimi, Saleh]]>;
<![CDATA[Verayiah, Renuga]]>;
<![CDATA[Xu, Tan Yi]]>;
<![CDATA[Panneerchelvan, Nagaraja Rupan]]>;
<![CDATA[Abidin, Aidil Azwin Zainul]]>;
<![CDATA[Marsadek, Marayati]]>;
<![CDATA[Ramasamy, Agileswari K.]]>;
<![CDATA[Abidin, Izham Zainal]]>;
<![CDATA[Jaafar, W. Mohd Suhaimi Wan]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i3.pp1658-1672
<![CDATA[The synchronous generator (SG) plays a crucial role in power systems by serving as a stable and reliable source of electrical energy. The performance of an SG hinges on its standard parameters, which can be derived through dynamic tests. This study introduces a method for determining the standard parameters of an SG from dynamic tests conducted via power system simulation for engineering (PSS/E). The proposed method entails conducting several key tests on the generator, including a direct-load rejection test, excitation removal test, quadrature-axis load rejection test, arbitrary axis load rejection test, and open-circuit saturation test. The results obtained from these tests are then utilized to calculate the standard parameters of the SG accurately. To validate the effectiveness of the method, simulation data from the SG, as well as the designed initial data, are utilized. Statistical analysis reveals that the maximum relative error is equal to or less than 2.7% of the design values for all standard parameters, emphasizing the robustness and accuracy of the proposed method. The methodology presented in this study can complement field or site measurements, as it enables the verification of system parameters through dynamic simulations.]]>
<![CDATA[Intelligent MPPT system improved with sliding mode control ]]>
<![CDATA[Dani, Said]]>;
<![CDATA[Drighil, Asmaa]]>;
<![CDATA[Abdouni, Khadija]]>;
<![CDATA[Sabhi, Khalid]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i3.pp1926-1938
<![CDATA[The sharp rise in global energy demand over recent decades has necessitated the exploration of alternative energy sources. Solar energy, known for being both pollution- and fuel-free, stands out as a preferred choice. However, its efficiency is sensitive to factors like temperature fluctuations and solar irradiation. To optimize energy extraction, a maximum power point tracking algorithm is crucial for photovoltaic systems. This paper proposes a robust sliding mode control enhanced with an artificial neural network to achieve the Maximum Power Point in a stand-alone PV system. The artificial neural network determines the reference voltage, which is then regulated by the sliding mode control to match the photovoltaic array voltage. The performance of the suggested controller is compared to that of a proportional integral-based neural network controller and the perturb and observe method using MATLAB/Simulink. The results show that the suggested method provides excellent tracking performance and rapid convergence even under quickly changing weather conditions, highlighting its efficiency and robustness.]]>
<![CDATA[Optimization of ANN-based DC voltage control using hybrid rain optimization algorithm for a transformerless high-gain boost converter ]]>
<![CDATA[Byar, Mohcine]]>;
<![CDATA[Abounada, Abdelouahed]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i3.pp1711-1720
<![CDATA[This paper introduces an adaptive voltage regulation technique for a transformerless high-gain boost converter (HGBC) integrated within standalone photovoltaic systems. A neural network controller is trained and fine-tuned using the rain optimization algorithm (ROA) to achieve improved dynamic behavior under variable solar conditions. The proposed ROA-ANN framework continuously updates the duty cycle to ensure output voltage stability in real time. Validation was carried out using MATLAB–OrCAD co-simulation under multiple scenarios. Comparative results highlight superior performance of the ROA-ANN controller in terms of convergence speed, overshoot minimization, and steady-state response, outperforming conventional PID and ANN-based methods.]]>
<![CDATA[Low voltage fault ride-through operation of a photo-voltaic system connected utility grid by using dynamic voltage support scheme ]]>
<![CDATA[Burada, Satyanarayana]]>;
<![CDATA[Padma, Kottala]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i3.pp1608-1619
<![CDATA[This research suggests a control technique that makes use of a microgrid's energy storage and to enable low voltage ride through (LVRT) process with a flexible dynamic voltage support (DVS) system. First, the requirements for the microgrid's maximum DVS are stated, together with an explanation of how these requirements depend on the characteristics of the analogous network that the microgrid sees. In order to create a flexible DVS regardless of the changing system circumstances, reference signals for currents that are derived from maximum voltage tracking technique are suggested in this research. These signals take into account the challenges involved with real time parameter assessment in the context of transient voltage disruptions. Second, a control scheme is suggested to allow a microgrid's energy storage-based LVRT operation. Thirdly, a novel approach to energy storage sizing for LVRT operation is offered, taking into account the corresponding network characteristics, grid code requirements, and the rated current value of the power electronic converter. Real-time MATLAB simulations for low-voltage symmetrical faults are used to validate the suggested control technique.]]>
