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International Journal of Power Electronics and Drive Systems (IJPEDS)
Published by Institute of Advanced Engineering and Science
ISSN : -     EISSN : 20888694     DOI : -
Core Subject : Engineering,
Control & Systems Engineering Electrical & Electronics Engineering
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.
Arjuna Subject : -
Articles 63 Documents
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Search results for , issue "Vol 15, No 2: June 2024" : 63 Documents clear
Performance evaluation of BLDC motor drive mounted in aerial vehicle (drone) using adaptive neuro-fuzzy Rao, Gurrala Madhusudhana; Prasanna, B. Lakshmi; Rayudu, Katuri; Kondaiah, Vempalle Yeddula; Thrinath, Boyanasetti Venkata Sai; Gopal, Talla Venu
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 15, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v15.i2.pp733-743

Abstract

The development of autonomous drones equipped with cameras and various sensors has paved the way for their application in agriculture and perimeter security. These aerial drones require specific power, acceleration, high torque, and efficiency to meet the demands of agricultural tasks, utilizing built-in brushless DC (BLDC) motors. However, a common challenge drone’s face is maintaining the desired speed for extended periods. Enhancing the performance of BLDC motors through advanced controllers is crucial to address this issue. This research paper proposes optimizing the size and speed of brushless DC motors for aerial vehicles using an adaptive fuzzy inference system and supervised learning techniques. When these drones carry loads, the BLDC motors must dynamically adjust the drone's speed. During this phase, the motors must control their speed and torque using artificial intelligence controllers like adaptive neuro-fuzzy inference systems (ANFIS) to enhance the drone's functionality, resilience, and safety. This research has conducted analyses focused on improving the performance of BLDC motors explicitly personalized for unmanned aerial vehicle (UAVs). The proposed method will be implemented using MATLAB/Simulink, expecting to significantly enhance the BLDC motor's performance compared to conventional controllers. Comparative analyses will be conducted between traditional and ANFIS controllers to validate the effectiveness of the proposed approach.
Multi-objective algorithm for hybrid microgrid energy management based on multi-agent system Tyass, Ilham; Bellat, Abdelouahed; Raihani, Abdelhadi; Mansouri, Khalifa
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 15, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v15.i2.pp1235-1246

Abstract

In the dynamic landscape of renewable energies, microgrid systems emerge as a promising avenue for fostering sustainable local energy generation. However, the effective management of energy resources holds the key to unlocking their full potential. This study assumes the task of creating a multi-objective optimization algorithm for microgrid energy management. At its core, the algorithm places a premium on seamlessly integrating renewable energy sources and orchestrating efficient storage coordination. Leveraging the prowess of a multi-agent system, it allocates and utilizes energy resources. Through the combination of renewable sources, storage mechanisms, and variable loads, the algorithm promotes energy efficiency and ensures a steady power supply. This transformative solution is underscored by the algorithm's remarkable performance in practical simulations and validations across diverse microgrid scenarios, offering a prevue into the future of sustainable energy utilization.
A review on soft computing techniques used in induction motor drive application Durgasukumar, Gadwala; Prasad, Repana Ramanjan; Gorantla, Srinivasa Rao
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 15, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v15.i2.pp753-768

Abstract

In this paper, hybrid models based on fuzzy systems and neural networks are reviewed. A fuzzy inference system is explicitly represented by expertise for induction motor drives, incorporating the learning capability of artificial neural networks. Researchers have been attracted to neuro-fuzzy techniques for training and inference in induction motor drives due to their efficiency. According to the classification of research articles from 2000 to 2020, this article presents a review of different artificial neural network techniques, fuzzy and neuro-fuzzy systems. The main objective is to provide a concise overview of current neuro-fuzzy research and to enable readers to identify appropriate methods according to their research interests. 
The implementation of an optimized neural network in a hybrid system for energy management Jarmouni, Ezzitouni; Mouhsen, Ahmed; Lamhamdi, Mohamed; Ennajih, Elmehdi; Ennaoui, Ilias; Krari, Ayoub
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 15, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v15.i2.pp815-823

Abstract

In the face of increasing global energy demand and volatile energy prices, many countries are searching for solutions to ensure their energy independence. One of the most popular solutions is to incorporate renewable energy sources in their energy systems. While there are many advantages to integrating renewable energy sources, it is important to note that their intermittent operation can present challenges. Energy storage and smart grid management systems are key solutions to overcome these challenges and ensure sustainable, reliable use of renewable energy sources. In this article, we present an intelligent electrical energy management system for hybrid energy systems. This management system is based on a multi-layer neural network that has undergone an architecture optimization phase to improve the accuracy of real-time energy management and simplify its implementation. The management model that was built demonstrated highly good performance across a range of test circumstances.
Performance evaluation of bridgeless isolated SEPIC-Luo converter for EV battery charging using PI and ANN controller Dhandapani, Meena; Ravichandran, Padmathilagam; Shanmugam, Arulvizhi; Pachaivanan, Nammalvar
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 15, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v15.i2.pp935-946

Abstract

Electric vehicle (EV) rechargeable battery packs that employ traditional power factor correction (PFC) circuit design have performance limitations due to their substantial conductivity loss that ensures at the input of a diode bridge rectifier (DBR). This study suggests a bridgeless (BL) isolated single ended primary inductance converter (SEPIC) - Luo converter to address the problem. As a result, the input current exhibits a power factor operation of unity throughout the charging process. DBR elimination and current conduction through a remarkably small number of circuits both significantly reduce conduction losses. The use of an artificial neural network (ANN) and proportional integral (PI) controller enhances the converter's performance with a stable DC link voltage. The suggested converter overall operation is thoroughly described in terms of variety of operating modes and simulation-based effectiveness. Here, with the assistance of the hysteresis current controller (HCC), the input current disruptions are reduced. Constant current and voltage management is used to successfully charge the EV battery, resulting in improved efficacy and inherent PFC. By utilizing simulation outcomes achieved from MATLAB, the performance of proposed BL isolated SEPIC-Luo in boosting the power quality of EV charger system is examined.
Comparing fuzzy logic and backstepping control for a buck boost converter in electric vehicles Ennajih, Elmehdi; Allali, Hakim; Jarmouni, Ezzitouni; Ennaoui, Ilias
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 15, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v15.i2.pp883-891

Abstract

Significant advances have been made in the control of DC/DC converters, owing to the effective combination of linear and nonlinear approaches. The above-mentioned approaches have greatly improved the efficiency as well as stability of the converter, even when faced with changing conditions. Nevertheless, the emergence of artificial intelligence has introduced new perspectives in the domain. The objective of the article is to examine two separate methodologies for controlling a boost-buck converter: using a nonlinear approach, especially backstepping, and utilizing artificial intelligence through fuzzy logic. The main aim of this work is to illustrate the inherent stability and robustness of fuzzy logic controllers compared to backstepping control in managing effectively various variations and challenges encountered in converter control.
Multi-objective economic load dispatch using hybrid NSGA-II and PVDE techniques Chandrashekhar, Mothala; Dhal, Pradyumna Kumar
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 15, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v15.i2.pp1266-1275

Abstract

Over decades, numerous methods have been used to optimize objective functions. Where cost and emissions clash. The improved non-dominated sorting genetic algorithm (NSGA-II) employs elitism to discover the optimum value and speed convergence in multi-objective optimization problems. Population variant differential evolution algorithm alters differential evolution (DE). The main distinction between DE and population variant differential evolution algorithm (PVDE) is population replenishment. NSGA-II and PVDE are combined in the suggested hybrid approach. The hybrid technique solves multi-objective optimization problems efficiently by combining two or more methods. The hybrid technique solves multi-objective optimization problems well. This optimization problem pits cost vs pollution. The hybrid approach exposes half the population to the NSGA-II algorithm and half to the PVDE algorithm. In optimization problems with opposing aims, such as minimizing costs and emissions, a hybrid technique is utilized to find the optimal solution. Elitist diversity-preserving strategies avoid optimization issues becoming converging too soon. A 10-generator IEEE 39 bus test system was validated using this method. The hybrid NSGA-II and PVDE methodology achieves global optimal solutions with more durability, simplicity, and optimization performance than existing methods.
The wind turbine's direct power control of the doubly-fed induction generator Hammoudi, Ben Ali; Serhoud, Hicham
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 15, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v15.i2.pp1201-1210

Abstract

The study suggests a comprehensive approach to modeling and controlling variable-speed wind turbine systems that utilize doubly fed induction generators (DFIGs). To make sure that energy is transferred efficiently between the DFIG rotor and the grid, a two-level inverter with perfect bidirectional switches is used. Using the tip speed ratio algorithm and taking into consideration the randomness in wind speed, the maximum power at the wind turbine is optimized. Then, the control strategy utilizes direct power control (DPC) due to its various advantages. The advantages of employing this control technique are manifold. Firstly, it eliminates the necessity for rotor current control loops. Secondly, it obviates the need for controllers such as PI controllers to manage torque and flux. Furthermore, it has yielded exceptional simulation results when implementing direct power control (DPC) within the MATLAB/Simulink environment, specifically in the context of a doubly fed induction generator (DFIG) wind power system.
Fast synchronization with enhanced switching control for grid-tied single-phase square wave inverter using FPGA Sithananthan, Tharnisha; Bakar, Afarulrazi Abu; Sannasy, Balarajan; Utomo, Wahyu Mulyo; Taufik, Taufik
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 15, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v15.i2.pp1105-1116

Abstract

Research on grid synchronization has been conducted worldwide by researchers in conjunction with the development of innovative technologies, such as dedicated short-range communication (DSRC) and cellular vehicle-to-everything (C-V2X). However, grid-connected inverters face several challenges, mainly the mismatch in voltage amplitude, frequency, and phase angle, as well as grid voltage disturbance and grid faults. Thus, the control algorithm of this research mainly focused on a half-cycle algorithm to design an enhanced digital switching control for fast synchronization using an FPGA. The control algorithm was developed based on zero-crossing detection (ZCD) and digital phase-locked loop (PLL) modeling techniques using the hardware description language (HDL) and a combination of digital logic blocks in Quartus II software, where the proposed switching was applied using the square-wave switching technique through a 300-watt full-bridge experimental prototype. The performance of the proposed technique was studied, where the total harmonic distortion (THD) for voltage and current resulted in a percentage reduction of 89.29% and 78.05% for voltage and current, respectively, after filter implementation. Also, the resulting signal synchronized in every half cycle and matched the voltage amplitude, frequency, and phase angle of the grid signal in 10 ms.
Review of DC-DC boost converter derived topologies for renewable energy applications Thulasiraman, Nivethaa; Viswanathan, Lavanya; Sriramalakshmi, Palanidoss
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 15, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v15.i2.pp947-957

Abstract

This paper deals with three different power converter topologies for boosting the available dc input voltage. The converters considered for the study are conventional DC-DC boost converter, quasi switched boost DC-DC converter (qSBC) and quasi Z source converter (qZSC). The converters are designed for an input voltage of 24 V to deliver a power of 200 W to a resistive load. The steady-state analysis of all three topologies is discussed to determine the key characteristics of the proposed topologies. All the converters are simulated in MATLAB/Simulink environment and the outcomes are explained in detail. The performance comparison of the converters such as switch stress, diode stress and boost factor versus duty ratio are presented. Thus, this comparison helps to choose a suitable boost converter topology for a specific application.

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