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
2,781 Documents
<![CDATA[TCM-Former: a transformer with temporal convolution for photovoltaic power forecasting ]]>
<![CDATA[Sarab Al-Chlaihawi]]>;
<![CDATA[Mohammed A. T. Alrubei]]>;
<![CDATA[Faris A. Alhaddad]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 3: September 2026 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v17.i3.pp2127-2148
<![CDATA[To tackle the problem of modeling long-term trends and short-term and high-frequency variations in PV time series, a strong and efficient forecasting model of photovoltaic (PV) power generation is advanced. This paper presents STL-TCM-Former, a hybrid model that breaks down the raw PV signal with seasonal-trend decomposition with LOESS (STL) into trend and seasonal components. These elements are after that processed via a dual path encoder decoder transformer architecture that is improved with a temporal convolutional module (TCM). The period (transformer-based) path is used for capturing the global, long-range dependencies in seasonal component and temporal (TCM) path is used to extract the localized, short-term dynamics. Trend component is processed with a dedicated TCM branch, minimizing component interferences and providing a multiscale temporal representation, specific to PV generation patterns. The proposed model was evaluated on the Yulara (Uluru) solar dataset under short-term (60-hour) and long-term (300-hour) forecasting horizons. Compared with benchmark models including LSTM, WOA-LSTM, VMD-LSTM, WOA-VMD-LSTM, and hybrid WOA/VMD/LSTM configurations, STL-TCM-former achieved superior performance with R² = 99.76%, MAPE ≈ 2.24%, RMSE = 16.63, and MAE = 10.36. In addition, the PJM interconnection dataset was also employed to evaluate the generalization capability of the proposed method. The results demonstrate high accuracy, stability, and strong generalization capability under varying environmental conditions.]]>
<![CDATA[A self-lift quadratic boost converter topology for efficient marine propulsion drive systems ]]>
<![CDATA[Subbulakshmy Ramamurthi]]>;
<![CDATA[Dhandapani Meena]]>;
<![CDATA[Velmurugan Palani]]>;
<![CDATA[Shobana Devendiran]]>;
<![CDATA[S. Ganesh Kumaran]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 3: September 2026 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v17.i3.pp1852-1858
<![CDATA[This paper proposes a high-gain self-lift quadratic boost converter (SL-QBC) topology tailored for efficient marine propulsion drive systems. The presented converter architecture incorporates a self-lift circuit embedded within a quadratic boost stage to achieve significant voltage gain while maintaining low component stress and high conversion efficiency. Specifically, the converter is capable of boosting a low input voltage of 45 V to a high output voltage of 473 V. The high-voltage output is then fed to the marine propulsion system through a three-phase, three-level neutral point clamped (NPC) inverter, which drives a three-phase induction motor. Designed to interface low-voltage DC sources such as batteries, photovoltaic panels, or fuel cells with high-power marine propulsion motors, the proposed topology offers a compact and cost-effective solution for electric and hybrid marine applications. The self-lift mechanism enhances voltage boosting capability by leveraging additional inductive and capacitive energy transfer paths. The topology ensures continuous current operation, reduced voltage ripple, and improved dynamic response, all of which are critical for smooth and reliable marine drive performance. Simulation results validate the converter’s effectiveness, confirming its potential as a robust and efficient power conditioning stage in next-generation marine energy systems.]]>
<![CDATA[Combination whale optimization algorithm and fuzzy logic for optimal design battery charging LiFePO₄ ]]>
<![CDATA[Indhana Sudiharto]]>;
<![CDATA[Mochammad Machmud Rifadil]]>;
<![CDATA[Ajeng Amelia Veganesa]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 3: September 2026 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v17.i3.pp1994-2003
<![CDATA[This research proposes an optimized charging strategy for lithium iron phosphate (LiFePO₄) batteries by integrating the whale optimization algorithm (WOA) with a fuzzy logic controller (FLC) for adaptive constant current-constant voltage charging. The method addresses the limitations of conventional CC-CV charging, which uses fixed parameters and has limited adaptability to changing operating conditions. WOA automatically optimizes the FLC scaling factors to improve control performance and system responsiveness. The WOA-fuzzy and WOA-PI models were trained using 226 samples of initial current and voltage data. The system was evaluated in PSIM by comparing fuzzy, PI, WOA-PI, and WOA-fuzzy controllers. Open-loop simulation produced an average voltage error of 1.29%, confirming the need for closed-loop control. Under SOC conditions ranging from 30% to 97%, all controllers maintained the charging voltage near 73 V and the charging current around 10 A. The average voltage errors were 0.6635% for PI, 0.6684% for fuzzy, 0.6618% for WOA-PI, and 0.6601% for WOA-fuzzy. Hardware testing confirmed these results, with average errors of 0.14% for WOA-fuzzy and 0.31% for WOA-PI. Overall, WOA-fuzzy provides stable charging, faster convergence, and improved charging performance.]]>
<![CDATA[Novel improvised satin bowerbird algorithm for speed control and torque ripple minimization for switched reluctance motor ]]>
<![CDATA[M. Upanya]]>;
<![CDATA[S. Rashmi]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 3: September 2026 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v17.i3.pp1659-1674
<![CDATA[Switched reluctance motors (SRMs) have gained a lot of popularity for adjustable speed drive systems, cost-effectiveness, and simplicity. Currently, SRMs are widely used in electric vehicles, compressors, and machine tools. In the proposed work, the satin bowerbird (SBB) algorithm is improvised and implemented to determine the optimal turn-off angle (θoff), along with gain parameters for the proportional integral (PI) controller, to regulate the speed and to enhance the torque profile of the SRM. The performance of the SRM drive is tested for 4 different control schemes with different load torque and reference speed. The control schemes are a PI controller with hysteresis current control (HCC), implemented with conventional SBB and improvised SBB (ISBB). The other control scheme is a PI controller with an improved torque sharing function (TSF) and HCC, implemented with conventional SBB and improvised SBB. The TSF used in the control scheme has been improvised with adaptive smoothing and adaptive boosting functions. For the different control schemes tested, ISBB with a PI controller and improvised TSF with HCC has resulted in better speed regulation and a 50% reduction in total harmonic distortion (THD) when compared to the control scheme constituting the conventional SBB algorithm with a PI controller and HCC. The proposed work is extended with the computation of torque rising time (Tr) and torque settling time (TS).]]>
<![CDATA[Cost-effective and emission-aware dispatch strategy for a smart EV charging parking lot ]]>
<![CDATA[O. K. Rajesh]]>;
<![CDATA[N. Shanmugasundaram]]>;
<![CDATA[V. Rajendran]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 3: September 2026 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v17.i3.pp1591-1600
<![CDATA[The growing adoption of electric vehicles (EVs) necessitates intelligent charging strategies to alleviate grid congestion and control rising operational costs. This study introduces an IoT-enabled centralized energy management framework for a PV-BESS-EV integrated smart parking system, leveraging real-time data on carbon emissions, grid pricing, and solar irradiance. A key innovation is its bi-objective optimization model, which simultaneously minimizes both cost and carbon footprint, setting it apart from traditional single-objective approaches. The study evaluates teaching-learning-based optimization (TLBO) and particle swarm optimization (PSO) for addressing the system’s nonlinear challenges. Results indicate that TLBO offers faster convergence and greater robustness, leading to improved load flattening, enhanced PV utilization, and stable battery energy storage system (BESS) state of charge (SoC). Overall, the framework provides a scalable solution that effectively balances economic and environmental objectives for modern grid-integrated EV charging systems.]]>
<![CDATA[Real time fuzzy energy management of hybrid storage systems in DC microgrids with dynamic voltage restorer assisted power quality enhancement ]]>
<![CDATA[Yacine Benatallah]]>;
<![CDATA[Abdelkrim Benali]]>;
<![CDATA[Mabrouk Dahane]]>;
<![CDATA[Somia Benali]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 3: September 2026 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v17.i3.pp2197-2209
<![CDATA[This paper presents a real-time fuzzy logic-based energy management system (EMS) for a hybrid DC microgrid supplying a constant DC load and an AC sensitive load protected by a dynamic voltage restorer (DVR). The system integrates a 25-kW photovoltaic (PV) array, a 10-kW fuel cell (FC), a 15-kW battery energy storage system, and a 396 V supercapacitor bank. The EMS calculates the net power balance (ΔP = PPV - Pload), compares it with the states-of-charge (SoC) of the battery and supercapacitor, and dynamically allocates power references to each source. Fuzzy rules prioritize renewable generation, exploit the supercapacitor for fast transient compensation, and schedule the battery and fuel cell for medium- and long-term power balancing. The DVR acts as a series active power filter, injecting real power during sags and absorbing excess energy during swells, while the EMS maintains DC bus stability under fault conditions. Simulation results demonstrate enhanced DC bus voltage regulation, reduced battery cycling, efficient hydrogen utilization, and rapid recovery from voltage disturbances. The proposed strategy improves power quality and ensures continuous operation of sensitive loads, making it suitable for smart grid and renewable-based microgrid applications.]]>
<![CDATA[Design of PI and fuzzy-based sliding mode controller for speed control of BLDC motor using Landsman converter in electric vehicles ]]>
<![CDATA[S. Sahana]]>;
<![CDATA[K. Sasikala]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 3: September 2026 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v17.i3.pp1873-1884
<![CDATA[This research paper compares a conventional proportional-integral (PI) controller with a fuzzy-based sliding mode controller (FSMC) for speed control of a brushless DC (BLDC) motor powered by a Landsman DC-DC converter for electric vehicle (EV) applications. MATLAB/Simulink is used to model and simulate the proposed system's cascaded control architecture, which consists of a voltage source inverter and a Landsman converter. The performance is assessed in steady-state, load-disturbance, and transient scenarios. According to simulation data, the FSMC outperforms the PI controller in terms of rise time (0.064 s), overshoot (0.17%), and settling time (0.212 s). The FSMC exhibits better resilience, limiting the speed reduction to 45 RPM with a recovery time of 0.04 s with a sudden load disturbance of 1 Nm. The findings verify that the FSMC is appropriate for high-performance BLDC motor drive systems in electric vehicle applications because it provides improved dynamic response and disturbance rejection.]]>
<![CDATA[Adaptive internal model control-proportional integral for robust control of three-phase active front-end rectifiers ]]>
<![CDATA[Azizah Abdul Razak]]>;
<![CDATA[Norjulia Mohamad Nordin]]>;
<![CDATA[Razman Ayop]]>;
<![CDATA[Hazlina Selamat]]>;
<![CDATA[Abobaker Kikki Abobaker]]>;
<![CDATA[Nik Rumzi Nik Idris]]>;
<![CDATA[Tole Sutikno]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 3: September 2026 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v17.i3.pp1794-1807
<![CDATA[Three-phase active front-end (AFE) rectifiers are widely deployed in motor drives, electric vehicle chargers, and grid-connected renewable energy systems, where precise DC-link voltage regulation is essential for stable converter operation. In practice, DC-link capacitance degrades over time, and load profiles vary dynamically, both degrading the DC-link voltage regulation performance. Conventional proportional-integral (PI) outer voltage controllers are designed based on nominal operating conditions, with limited stability margins resulting in sluggish or oscillatory DC-link voltage responses under significant load and parameter variations. This paper proposes an adaptive internal model control-proportional integral (AIMC-PI) outer voltage loop controller for a three-phase AFE rectifier. It extends the conventional IMC-PI structure by incorporating an active damping term, an internal feedforward gain, a reference filter, and a Lyapunov-based adaptation law that updates the embedded plant model and IMC filter time constant online ensuring closed-loop stability and bounded tracking error. Simulation results show that AIMC-PI achieves a faster dynamic response than PI and performance comparable to IMC-PI and linear active disturbance rejection control (LADRC) under nominal conditions. As DC-link capacitance degrades to 0.5C, AIMC-PI maintains a well-damped DC-link voltage, whereas LADRC exhibits noticeable oscillations. Experimentally, AIMC-PI successfully eliminates the AC-supply current and DC-link voltage ripples present in fixed-λ IMC-PI.]]>
<![CDATA[Short-circuit analysis and protection coordination of a 33 kV phosphate plant distribution network ]]>
<![CDATA[Cheikhani Abdel Kader]]>;
<![CDATA[Bamba El Heiba]]>;
<![CDATA[Mohamed El Mamy Mohamed Mahmoud]]>;
<![CDATA[Beibah Gleigume]]>;
<![CDATA[Abdel Kader Mahmoud]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 3: September 2026 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v17.i3.pp1768-1779
<![CDATA[This study presents a short-circuit and protection coordination analysis of a 33 kV/0.4 kV industrial distribution network supplying a phosphate processing plant in Mauritania. Using ETAP software, the system was modeled to evaluate fault behaviors based on IEC 60909 and IEC 60255-151 standards. The study assesses the existing protection architecture and proposes an optimized digital protection framework. Simulation results indicate that the initial symmetrical short-circuit current at the 0.4 kV busbar reaches 96.5 kA, exceeding the 25-36 kA breaking capacity of the legacy equipment by nearly 300%. The analysis also investigates single-line-to-ground faults, revealing a fault current inversion phenomenon driven by the solid grounding configuration. To address these vulnerabilities, the study proposes upgrading to 150 kA-rated high-breaking-capacity switchgear and implementing advanced negative-sequence protection (ANSI 46) and transformer differential protection (ANSI 87T). This work provides a practical diagnostic framework for mitigating asymmetrical faults and optimizing protection coordination in heavy-duty industrial clusters.]]>
<![CDATA[Performance index for optimization method based on PMSM drives using ABC and PSO ]]>
<![CDATA[Leong Hui Ee]]>;
<![CDATA[Jurifa Mat Lazi]]>;
<![CDATA[Mohd Ruzaini Hashim]]>;
<![CDATA[Md Hairul Nizam Talib]]>;
<![CDATA[Azrita Alias]]>;
<![CDATA[Anggun Anugrah]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 3: September 2026 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v17.i3.pp1688-1701
<![CDATA[The permanent magnet synchronous motor (PMSM) is commonly used in industrial and home appliances for its high efficiency and dynamic performance. In this research, a PMSM drive based on field-oriented control (FOC) is designed and simulated using MATLAB/Simulink. The speed controller of the drive is tuned using the trial-and-error method. However, the method requires more time for testing and adjustment of the speed controller to generate an optimal output response. Thus, particle swarm optimization (PSO) and artificial bee colony (ABC) algorithms, which require less computational effort and effectively produce good responses, are used to optimize the speed controller of the drive. PSO and ABC also offer an attractive optimization framework because of their independent, agnostic model structures, global searching capability, and low-load real-time calculation. In this study, the results obtained from different tuning methods are compared to determine the best optimization method of the speed controller in the PMSM drive under different operations. Other than that, performance measures such as integral square error (ISE), integral absolute error (IAE), and integral time absolute error (ITAE), which are commonly used to measure the effectiveness of a controller, are also discussed. The results show that the PMSM drive based on the ITAE criterion using the ABC algorithm gives better performance under different conditions.]]>
