Djeddi, Abdelghani
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Journal : International Journal of Applied Power Engineering (IJAPE)

Optimal control of the UPFC for the stability of electrical networks Ababsia, Houria; Dib, Djalel; Djeddi, Abdelghani
International Journal of Applied Power Engineering (IJAPE) Vol 14, No 1: March 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v14.i1.pp180-187

Abstract

The unified power flow controller (UPFC) is a crucial element in contemporary power systems, specifically engineered to augment the manageability and adaptability of power transmission in electrical networks. UPFC provides instantaneous modifications to voltage magnitude, phase angle, and line impedance by using sophisticated power electronics and control algorithms. This research examines the function of the unified power flow controller (UPFC) in enhancing the power quality of electrical networks. The UPFC's capacity to dynamically regulate and optimize power flow assists in minimizing voltage fluctuations, decreasing transmission line losses, and improving system stability. In addition, UPFC effectively addresses problems such as voltage sags, swells, and flickers, hence enhancing the resilience and dependability of the power supply. This research highlights the importance of unified power flow control (UPFC) technology in improving system performance and power quality of electrical networks via a thorough examination of its applications. This article presents research on the performance of the unified power flow controller (UPFC) device in a network, specifically focusing on the use of PID and FO-PID controllers for regulating active and passive power.
Robust SOC estimation for lithium-ion batteries under faulty charging scenarios using sliding mode observer techniques Mahiddine, Soulef; Djeddi, Abdelghani; Djalel, Dib
International Journal of Applied Power Engineering (IJAPE) Vol 15, No 1: March 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v15.i1.pp46-58

Abstract

With the growing demand for electric vehicles, embedded electronics, and renewable energy applications, lithium-ion batteries have become an essential component in modern energy storage systems. Accurate state of charge (SOC) estimation is crucial for ensuring battery reliability, longevity, and safety, particularly under faulty charging conditions—a challenge where many conventional estimation techniques fall short due to model limitations or lack of robustness. In this study, we propose an advanced SOC estimation approach based on a sliding mode observer (SMO) integrated with a third-order equivalent circuit model (ECM). Unlike conventional methods, which either focus on SOC estimation without considering battery voltage or apply SMO techniques only to second-order models, our approach enhances estimation accuracy by incorporating a higher-order model that better captures the complex battery dynamics. The proposed methodology is tested under both normal and faulty charging conditions, demonstrating superior performance in estimating both SOC and terminal voltage over extended periods. The simulation results confirm the robustness of the method, with accurate SOC tracking even in the presence of charging current faults, making it a viable solution for real-world applications in battery management systems (BMS). This work contributes to improving fault-tolerant SOC estimation strategies, advancing the development of safer and more efficient energy storage technologies.
Induction motor simultaneous fault diagnosis based on Takagi-Sugeno models Souri, Samira; Louazene, Mohamed Lakhdar; Djeddi, Abdelghani; Soufi, Youcef
International Journal of Applied Power Engineering (IJAPE) Vol 15, No 1: March 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v15.i1.pp195-210

Abstract

This article proposes a model-based approach to the concurrent diagnosis of stator and rotor faults in induction motors (IMs) using Takagi-Sugeno (TS) fuzzy models. Fault-free detection is essential to prevent unexpected downtime and economic loss in industrial applications. The study first develops a dynamic model of the IM in the synchronized reference frame with the rotor under healthy and faulty operations. Different fault conditions like stator inter-turn short circuits, defective rotor bars, and combination thereof are considered. A TS model for every case is developed based on the precise nonlinear model. Simulation outcomes prove the validity of the new models in simulating the dynamic response of the motor under faulty operating modes. The residual signals are used to compare the performance of the model in fault isolation. The proposed method offers a classification that inherently separates between fault types. Such a contribution presents an efficient real-time fault detection and predictive maintenance facility, which renders it suitable for hardware-in-the-loop application in intelligent drive systems.