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
2,721 Documents
<![CDATA[High risk industries for advanced lightning protection system ]]>
<![CDATA[Kalagotla Chenchireddy]]>;
<![CDATA[P. Nagabushanam]]>;
<![CDATA[Radhika Dora]]>;
<![CDATA[Vadthya Jagan]]>;
<![CDATA[Shabbier Ahmed Sydu]]>;
<![CDATA[Nunavath Praveen]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 2: June 2026 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v17.i2.pp958-965
<![CDATA[Lightning strikes are a serious risk for high-risk facilities like oil and gas plants, mines, explosive storage, and data centers. These places hold the sensitive equipment and dangerous materials, and a lightning strike can cause major damage, leading to expensive downtime or even disastrous events such as fires or explosions. That’s why having a strong lightning protection system is not just a matter of following rules, but it is crucial for protecting both people and property. The complete lightning protection solutions designed to meet the specific needs of these critical industries. The services include lightning simulations and both isolated and attached lightning protection systems. This study investigates the real-time installation and testing of advanced lightning protection systems across high-risk industries like oil and gas plants, mines, explosive storage, and data centers. This ensures that the facility stays safe and continues to operate, even during severe weather. By investing in an effective lightning protection system, you can help secure your assets and keep everyone safe, focusing on what really matters in your industry.]]>
<![CDATA[FPGA-based sustainable EV charging controller with dynamic pricing for smart cities ]]>
<![CDATA[G. Sreeramulu Mahesh]]>;
<![CDATA[K. Hemachandra Reddy]]>;
<![CDATA[H. Pushparaj]]>;
<![CDATA[G. Balagopal Reddy]]>;
<![CDATA[N. Bharathesh Patel]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 2: June 2026 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v17.i2.pp981-990
<![CDATA[The growing adoption of electric vehicles (EVs) poses significant challenges to the stability and efficiency of the power grid, particularly under dynamic electricity pricing and variable grid availability in smart cities. This paper presents a novel, low-latency, hardware-driven approach to smart EV charging control using a field-programmable gate array (FPGA) Arty A7-100T. A customized finite state machine (FSM) evaluates the state of charge (SoC) and real-time pricing across multiple time slots. Based on this evaluation, it generates charge eligibility for each EV and transmits these decisions-along with the SoC and pricing data-via UART to an external Python interface. The received data is processed in Python and used to dynamically plot the SoC, pricing, and charging permission for each EV across time slots-providing a clear, intuitive visualization of decision-making based on energy economics. The distributed hardware-enabled paradigm minimizes delay as well as external dependency, thus offering improved responsiveness for the grid. The implementation is shown to represent a scalable solution for solving vital issue of demand side management for the evolving EV ecosystem for smart cities.]]>
<![CDATA[Torque ripple reduction in PMSM for FCEVs using ANFIS controller ]]>
<![CDATA[Shilpa Rao Hosabettu]]>;
<![CDATA[Pushpa Rajesh Viswanathan]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 2: June 2026 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v17.i2.pp885-893
<![CDATA[Globally, there is a growing emphasis on switching to green energy, particularly in the transportation sector, due to the effects of global warming, as seen by rising carbon footprints. Fuel cell electric vehicles (FCEVs) are one such technology that has attracted a lot of interest because of their availability, ease of use, high efficiency, and silent operation. Fuel cells are employed along with batteries to drive the vehicle much farther. Motors like permanent magnet synchronous motor (PMSM) provide the driving force for the vehicle, owing to their high torque at variable speeds and compactness. In such systems, it is necessary to have intelligent controllers that can align with the load requirement by means of a consistent and optimized power distribution. The torque ripple phenomenon, which has an impact on dynamic performance and operational stability, is one of the main limitations in the operation of PMSMs. In this work, smart control techniques, which are a combination of adaptive neuro fuzzy inference systems (ANFIS) and proportional-integral (PI) control, are employed to demonstrate the application of PMSM in conjunction with field-oriented control (FOC). Simulation results indicate that the proposed ANFIS-based FOC reduces torque ripple as compared to conventional PI control under varying load conditions.]]>
<![CDATA[Implementation of sliding control with washout filter in boost and buck converters ]]>
<![CDATA[Esteban Flórez Urrego]]>;
<![CDATA[Fredy E. Hoyos]]>;
<![CDATA[John E. Candelo-Becerra]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 2: June 2026 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v17.i2.pp1188-1198
<![CDATA[This paper presents the analysis, design, and implementation of a two-stage power conversion system consisting of a boost converter and a buck converter. Both converters were controlled using a sliding-mode control based on a washout filter. The system was supplied with an alternating current (AC) voltage source that was rectified using a diode bridge. The main objectives are to improve the power factor (PF) in the boost stage and regulate the output voltage in the buck stage. In the first stage, sliding-mode control is applied to shape the input current according to the rectified voltage, increasing the PF and reducing harmonic distortion. In the second stage, the same control approach is used to maintain a constant output voltage under load variations and disturbances. This study includes the mathematical modeling of both converters, control design, and simulation results in PSIM. The results show that the proposed sliding-mode control strategy effectively enhances energy efficiency, stabilizes the output voltage, and significantly improves the PF, making it suitable for robust and efficient power conversion systems.]]>
<![CDATA[Design simulation and analysis of an MPPT technique using ANNs integral backstepping and SMC for PV systems ]]>
<![CDATA[Naoufal Zhani]]>;
<![CDATA[Hassane Mahmoudi]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 2: June 2026 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v17.i2.pp1288-1303
<![CDATA[This paper introduces the design of an innovative hybrid MPPT method called artificial neural networks-integral backstepping sliding mode control (ANN-IBSMC). This approach combines artificial neural networks (ANNs), which output the maximum power point voltage using inputs such as irradiance and temperature, with a robust control strategy. The designed controller aims to track the reference voltage with high accuracy and responsiveness by modifying the pulse width modulation of the DC-DC converter in the photovoltaic system. The IBSMC integrates the advantages of two control methods: the stability and accuracy of integral backstepping, and the robustness and fast response of sliding mode control (SMC). This combination enables improved precision, high convergence speed, enhanced robustness, and strong stability, the latter being ensured by the Lyapunov function. To evaluate the performance of the proposed controller, a comparative study is performed against other hybrid control techniques, such as the ANN-backstepping controller, the ANN-integral sliding mode controller, and the ANN-backstepping sliding mode controller, using MATLAB/ Simulink. A sensitivity and robustness analysis was carried out.]]>
<![CDATA[Grid-connected battery energy storage system using interleaved bidirectional buck/boost converter and 3-level SVPWM inverter ]]>
<![CDATA[Oumaymah Elamri]]>;
<![CDATA[Jacob Wekalao]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 2: June 2026 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v17.i2.pp1199-1210
<![CDATA[This study presents a high-performance grid-connected battery energy storage system architecture designed to overcome the trade-off between DC-side current ripple and AC-side power quality. The proposed system synergistically integrates an interleaved bidirectional buck/boost converter, a three-level neutral-point clamped inverter, and an optimized LCL filter under a unified control strategy based on space vector pulse width modulation. Unlike conventional topologies that prioritize either subsystem individually, this integrated approach simultaneously minimizes battery current stress and ensures strict grid compliance. Extensive simulations in MATLAB/Simulink demonstrate that the proposed control strategy achieves a total harmonic distortion (THD) of just 2.93%, significantly outperforming the 40.25% THD of conventional two-level inverters and surpassing recent state-of-the-art benchmarks. The system exhibits robust dynamic response during rapid charging/discharging transitions and maintains stability under grid disturbances, such as 20% voltage dips. These results validate the architecture as a viable, high-efficiency solution for integrating modern renewable energy.]]>
<![CDATA[Design and development of a portable electromagnetic coil accelerator for advanced defense applications ]]>
<![CDATA[M. Priyadharsini]]>;
<![CDATA[Sunil Kumar Gupta]]>;
<![CDATA[Manoj Gupta]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 2: June 2026 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v17.i2.pp823-834
<![CDATA[In this work, a prototype of a six-stage coil gun was designed and developed to accelerate and propel a ferromagnetic projectile as an alternative technology to traditional firearms, which rely on explosive power for defense applications. The electromagnetic coils were arranged along the length of the barrel and were energized one at a time, sequentially, from one end of the barrel to the other to accelerate and propel the projectile forward. This paper presents the design, simulation, and optimization of the barrel and projectile, including details of the electromagnetic coils, triggering and switching circuits, and pulsed current sources. Simulations were conducted using COMSOL Multiphysics software with both single-coil and multiple-coil configurations. The prototype model incorporates a non-ferromagnetic barrel to minimize the retarding magnetic field and hysteresis, which could otherwise reduce the projectile’s velocity. The barrel is equipped with IR sensors to detect the projectile’s movement and activate or deactivate the corresponding electromagnetic coils, ensuring efficient forward propulsion. Utilizing a capacitor bank and rapid charging circuits, the developed prototype unit is capable of propelling the projectile at a velocity of 419 m/s measured at a 10-meter distance and could fire every 2 milliseconds successfully. The prototype unit developed is a handheld rifle using a polyvinyl chloride (PVC) barrel and uses a projectile with dimensions meeting the defense application.]]>
<![CDATA[Design of 7-level cascade asymmetric multilevel inverter for renewable energy applications using FPGA ]]>
<![CDATA[Afarulrazi Abu Bakar]]>;
<![CDATA[Hazwaj Mhd Poad]]>;
<![CDATA[Benjamin Ho Hao Xian]]>;
<![CDATA[Tharnisha Sithananthan]]>;
<![CDATA[Wahyu Mulyo Utomo]]>;
<![CDATA[Triyanto Pangaribowo]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 2: June 2026 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v17.i2.pp1231-1242
<![CDATA[The increasing focus on renewable energy has driven the need for efficient and reliable power converters. Multilevel inverters offer low harmonic distortion and high-quality output but often suffer from design complexity and excessive component count. This study presents the design and implementation of a 7-level cascaded asymmetric multilevel inverter optimized for renewable energy applications. The proposed topology utilizes a cascade structure with asymmetric DC voltage sources to generate seven voltage levels, providing a practical balance between performance and simplicity. The design was first validated through MATLAB/Simulink software to analyze circuit operation and evaluate the total harmonic distortion (THD) performance. Experimental evaluation was then conducted using a hardware prototype to verify simulation results. Without a filter, the THD from the simulation was 21.31%, while the experimental setup recorded a slightly higher value of 21.61%, indicating a marginal difference of 0.21%. With a filter, the simulation achieved a THD of 3.81%, whereas the experimental setup outperformed with a THD of 1.5%, showing a notable reduction of 2.31%. These findings confirm the proposed inverter’s capability to deliver superior power quality and operational efficiency. The combination of simulation and experimental validation demonstrates the practicality and reliability of the 7-level cascade asymmetric multilevel inverter for renewable energy applications.]]>
<![CDATA[Neuro-fuzzy control on a permanent magnet synchronous generator integrated in a wind system ]]>
<![CDATA[Mohammed Aoumri]]>;
<![CDATA[Ibrahim Yaichi]]>;
<![CDATA[Harrouz Abdelkader]]>;
<![CDATA[Patrice Wira]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 2: June 2026 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v17.i2.pp1304-1312
<![CDATA[This paper introduces a control strategy for a synchronous generator in a wind energy system using an adaptive neuro-fuzzy approach. The suggested controller, based on neuro-fuzzy logic (NFLC), is meant to govern a permanent magnet synchronous generator (PMSG) often utilized in wind power applications. The generator's output voltage phase, phase current, reactive power, active power, angular velocity, and DC voltage are all under control. The adaptive neuro-fuzzy controller efficiently stabilizes all variables in a brief amount of time, according to simulation results. The effectiveness and robust performance of the suggested control system are verified by a number of simulated scenarios. The resilience of fuzzy logic control (FLC) and NFLC systems was compared. The study carefully tested the performance of both control techniques under varied operating settings and disturbance situations to determine their relative stability, flexibility, and efficacy in sustaining desired system behavior.]]>
<![CDATA[Adaptive control of the virtual synchronous generator by deep neural networks for a wind high power conversion chain ]]>
<![CDATA[Wijdane El Maataoui]]>;
<![CDATA[Abdelouahed Abounada]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 2: June 2026 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v17.i2.pp1440-1450
<![CDATA[The virtual synchronous generator (VSG) is commonly used to reproduce the inertial response of conventional synchronous machines. However, the VSG control architecture relies on controller chains, benchmark transformations, and parameter settings, including virtual inertia and damping, which limit its flexibility in highly dynamic environments. This paper proposes an innovative end-to-end control approach based on a neural network to fully replace the classical VSG control structure. The neural network developed is trained to directly generate inverter control signals from real-time electrical measurements, including voltages and currents, as well as active and reactive power. A dataset is generated from a detailed VSG model under different operating conditions, and then a multilayer neural network is trained using supervised learning with MATLAB. The resulting model is then integrated into a complete wind energy conversion chain simulated in Simulink. The simulation results demonstrate that control based on artificial neural networks ensures better frequency and voltage stability, more accurate tracking of the active power injected, and a significant improvement in power quality, with total harmonic distortion (THD) reduced to 0.04%, compared to 0.51% for conventional VSG control. These results confirm the potential of artificial intelligence-based approaches for the intelligent control of renewable energy systems.]]>
