Articles

Access the latest knowledge in applied science, electrical engineering, computer science and information technology, education, and health.

Filter Icon

Filters article

Years

FAQ Arrow
0
0

Source Title

FAQ Arrow

Authors

FAQ Arrow

30,938 Article Results

Photovoltaic-inductive wireless charging for electric vehicles

10.11591/ijpeds.v17.i2.pp849-857
Azra Zaineb , P. Nagabushanam , Kalagotla Chenchireddy , Radhika Dora , Naresh Jella , Shabbier Ahmed Sydu
The growing demand for electric vehicles (EVs) necessitates efficient and eco-friendly charging methods. This study presents a photovoltaic-inductive wireless charging (PIWC) system, which integrates solar energy harvesting with inductive power transfer (IPT) to enable seamless operation without physical connectors. The system utilizes solar photovoltaic (PV) panels to generate renewable energy, which is then converted and transmitted wirelessly using resonant inductive coupling. This eliminates the need for physical connections, reducing wear and maintenance while supporting both stationary and dynamic charging applications. To enhance performance, maximum power point tracking (MPPT) controllers optimize solar energy utilization. Power electronics and control strategies regulate the energy transfer, ensuring efficient and stable operation. Additionally, IoT-based monitoring enables real-time system analysis and performance tracking. Through simulations and prototype evaluations, the system's feasibility, efficiency, and environmental impact are assessed. Results indicate that PIWC can minimize grid dependency, providing a sustainable, autonomous, and convenient charging solution for EVs. This innovation contributes to cleaner transportation and the advancement of renewable energy-driven mobility.
Volume: 17
Issue: 2
Page: 849-857
Publish at: 2026-06-01

Resilient EV charging station network design using AI algorithms

10.11591/ijpeds.v17.i2.pp1543-1552
Deepa Somasundaram , N. Krishnamoorthy , J. Vijay Anand , R. Priyanka , T. Santhana Krishnan , Kirubakaran Dhandapani
This paper proposes an AI-driven resilient network design framework for optimal electric vehicle (EV) charging station placement under stochastic demand and dynamic grid constraints. The proposed approach uniquely integrates long short-term memory (LSTM) based spatiotemporal demand forecasting with a hybrid genetic algorithm-particle swarm optimization (GA-PSO) model for multi-objective station placement. In addition, a deep reinforcement learning (DRL) agent is incorporated to enhance adaptive resilience under real-time grid disturbances. The framework minimizes installation cost, reduces user travel distance, and improves grid stability while ensuring equitable accessibility. The model is evaluated under multiple scenarios, including peak demand, station outages, renewable intermittency, and grid capacity reduction. Results demonstrate that the proposed hybrid AI framework achieves a resilience index of 0.92, reduces travel distance by 54%, and lowers installation cost by up to 16% compared to conventional approaches such as linear programming (LP) and K-means clustering. The integration of renewable energy further reduces peak grid dependency by 18%. The proposed methodology provides a scalable and practical solution for designing sustainable and resilient EV charging infrastructure in smart urban environments.
Volume: 17
Issue: 2
Page: 1543-1552
Publish at: 2026-06-01

Design simulation and analysis of an MPPT technique using ANNs integral backstepping and SMC for PV systems

10.11591/ijpeds.v17.i2.pp1288-1303
Naoufal Zhani , Hassane Mahmoudi
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.
Volume: 17
Issue: 2
Page: 1288-1303
Publish at: 2026-06-01

Advanced soft-switching high-gain Re Boost Luo converter for enhanced efficiency in photovoltaic systems

10.11591/ijpeds.v17.i2.pp1177-1187
Vendoti Suresh , Dondapati Ravi Kishore , T. Vijay Muni , P. Hari Krishna Prasad , Pydi Bala Krishna , A. V. G. A. Marthanda
This work presents an innovative approach to improving efficiency and performance in photovoltaic (PV) systems through the development of a soft-switching high-gain Re Boost Luo converter. This converter integrates advanced soft-switching techniques to minimize switching losses, thereby enhancing overall system efficiency, which is crucial for applications requiring substantial voltage amplification from PV sources. The Re Boost Luo converter, with its inherent high-gain capability, facilitates superior voltage conversion ratios, enabling optimal energy extraction from PV panels across varying environmental conditions. The presented converter's design focuses on reducing electromagnetic interference (EMI) and alleviating stress on switching components, thereby extending their operational lifespan and reliability. Detailed modeling and performance analysis were carried out using the MATLAB/Simulink simulation environment, which allowed for comprehensive evaluation of the converter's functionality. Simulation results confirm that the converter achieves significant improvements in voltage gain, energy conversion efficiency, and system reliability, effectively addressing common challenges associated with high-voltage PV applications. This study underscores the converter's potential to advance renewable energy technologies by providing a robust solution for high-efficiency energy conversion in PV systems.
Volume: 17
Issue: 2
Page: 1177-1187
Publish at: 2026-06-01

Neuro-fuzzy control on a permanent magnet synchronous generator integrated in a wind system

10.11591/ijpeds.v17.i2.pp1304-1312
Mohammed Aoumri , Ibrahim Yaichi , Harrouz Abdelkader , Patrice Wira
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.
Volume: 17
Issue: 2
Page: 1304-1312
Publish at: 2026-06-01

Control strategy for the combined operation of grid-connected inverter and charger

10.11591/ijpeds.v17.i2.pp1396-1407
Quang-Tho Tran , Quang-Sang Le
Solar power sources and electric vehicles (EVs) are increasingly used because of their environmental friendliness and sustainability. They are typically connected to the power grid through devices such as inverters and chargers to either generate or receive electrical energy. These devices contain a DC voltage bus. Therefore, the combined control of these two types of devices can improve their overall operational efficiency. This article proposes a grid-connected converter with an integrated battery-charging function. In addition, it presents a control strategy for the coordinated operation of this converter during both charging and power generation at the DC bus. In this algorithm, the battery is treated as a priority load, which allows the system to eliminate the AC-DC converter used in conventional chargers. A total peak power of 9 kWp is used to investigate the processes of power generation and battery charging. The total harmonic distortions of grid current are less than 2.86% in different operational cases and meet the grid codes. The obtained results are analyzed under varying irradiance conditions to verify the effectiveness of the proposed control method.
Volume: 17
Issue: 2
Page: 1396-1407
Publish at: 2026-06-01

Simulation and comparison of trapezoidal triangle carrier signal with different reference signal for 1500 V DC bus 3 level ANPC inverter

10.11591/ijape.v15.i2.pp492-504
Miteshkumar N. Priyadarshi , Sandeep Chakravorty
High voltage application to generate staircase output to reduce the total harmonic distortion (THD), the multilevel topologies gaining more and more attractions, and new topologies have been developed. This paper discuss about the advantage of active neutral point clamp (ANPC) topology over neutral point clamp (NPC), flying capacitor neutral point clamp (FCNPC) and T-type neutral point clamp (TNPC) topologies are discussed when it used for DC bus voltage of 1500 V. For ANPC topology several PWM techniques are used to calculate the total harmonic distortion, including phase opposition pulse width modulation (PODPWM), phase disposition pulse width modulation (PDPWM), and alternative phase opposition disposition pulse width modulation (APODPWM), phase shifted pulse width modulation (PSPWM), bus clamping PWM (BCPWM), trapezoidal triangle PWM (TRPWM), third harmonic injected PWM (THIPWM), and sinusoidal PWM (SPWM), three-phase sinusoidal signals with a 13th harmonic signal (THISDPWM). Also, the parasitic inductance model of ANPC topology is discussed. To use 1200 V switching device the most efficient PWM technique for a 1500 V DC bus, 3 phase 3 level ANPC inverter is determined by comparing the RMS value of phase voltage, THD, and peak voltage across the switching device. PSIM has been used to simulate a 3 level inverter using various PWM techniques.
Volume: 15
Issue: 2
Page: 492-504
Publish at: 2026-06-01

Smart IoT-based temperature-controlled cooling system for solar panels using Arduino

10.11591/ijape.v15.i2.pp781-792
Mula Sreenivasa Reddy , Kondragunta Rama Krishnaiah , Anjali Devi Gorla , Anantha Sravanthi Peddinti , Sanam Nagendram , Mohammad Najumunnisa , Bodapati Venkata Rajanna , Shaik Hasane Ahammad , Gongati Pandu Ranga Reddy
The efficiency of solar photovoltaic panels declines significantly as their surface temperature increases beyond optimal levels. This paper presents a smart, temperature-controlled cooling system based on an Arduino UNO microcontroller to enhance solar panel performance by mitigating overheating. The system integrates a DS18B20 temperature sensor and a moisture sensor to monitor real-time environmental conditions. When the temperature exceeds a defined threshold, the Arduino activates a CPU fan and water pump to dissipate heat effectively. Experimental testing demonstrated an efficiency improvement of approximately 10% to 12% during peak solar conditions. A hysteresis logic-based system with autonomous control is used to control the amount of energy and water utilized, by only cooling when required. An LCD screen displays real-time information locally on-site, while an ESP8266 WiFi module sends information to a "cloud" so that remote monitoring can occur through the ThingSpeak cloud service. The entire system operates entirely from solar energy and is capable of being operated off-the-grid as well as being environmentally friendly. Due to its low cost, modularity, and energy efficiency, this smart cooling solution provides a viable solution for rural areas or areas with limited resources to enhance the performance of photovoltaic systems.
Volume: 15
Issue: 2
Page: 781-792
Publish at: 2026-06-01

Investigation of the photoluminescence properties of quantum dots using theoretical simulation

10.11591/ijape.v15.i2.pp942-947
Le Doan Duy , Le Xuan Thuy
This study investigates the optical behavior of CdSe quantum dots, a class of semiconductor nanomaterials widely studied for light-emitting, photovoltaic, and bioimaging applications owing to their size-dependent electronic structure. The objective is to clarify the relationship between quantum dot size, size distribution, and emission characteristics through experimental and simulated optical spectra. UV-Vis absorption, photoluminescence, and simulated PL spectra were analyzed for CdSe quantum dots excited at 325 nm. The experimental PL spectrum exhibits a single and narrow emission band assigned to the 1Se → 1Sh transition, which is blue-shifted compared with bulk CdSe, confirming strong quantum confinement in 2-3 nm particles with a very narrow size distribution of less than 1%. A large Stokes shift of 0.93 eV is observed, attributed to confinement effects and surface-related states. Simulated photoluminescence (PL) spectra for 3-6 nm quantum dots show progressive red-shifting and spectral broadening with increasing particle size, while smaller quantum dots display stronger PL intensity due to enhanced confinement and more efficient radiative recombination. Parameter analysis further reveals that size deviation and linewidth broaden emission and reduce intensity without changing the peak wavelength. These findings provide useful guidance for optimizing CdSe quantum dots for QLEDs, bioimaging, and broadband optoelectronic devices.
Volume: 15
Issue: 2
Page: 942-947
Publish at: 2026-06-01

A novel single-stage high-voltage gain DC-DC boost converter for on-board PEV charging system

10.11591/ijape.v15.i2.pp610-619
Motepalli Siva Rama Ganesh , S. Sasikumar , B. Suresh Babu
Currently, the utilization of plug-in electric vehicles is quickly increasing in the vehicle industry owing to reduced costs of transportation, no need for fossil fuels, simple servicing, no fuel expense, and lower environmental effect compared to internal-combustion motor vehicles. In actuality, these motor vehicles function based on available battery energy that are charged by a utility-grid-supplied charging station. In this charging facility, a power converter defined on-board charger is generally used to charge the batteries, which improves the utility grid specifications by reducing the presence of harmonics and power factor regulation. An active two-stage load conditioning approach is commonly employed, however it doubles the conversion stages, requires larger switching components, complicated circuitry, large switching losses, and decreased efficiency, among other issues. To address these issues, a unique single-stage on-board EV charger has been used to regulate utility-grid specifications and seamless management of battery state-of-charge using a load-side DC-DC conditioning method. The major goal of this study is to propose a unique DC-DC boost converter that provides substantial voltage gain, consistent input current, minimal current ripples, and highest efficiency among numerous converters. The effectiveness of the proposed unique single-stage on-board EV charger has been evaluated through MATLAB/Simulink application, and the simulation findings have been presented.
Volume: 15
Issue: 2
Page: 610-619
Publish at: 2026-06-01

Performance evaluation of several basic types of DC-DC converters for small-scale wind turbine connected to isolated load

10.11591/ijape.v15.i2.pp674-691
Rizki Mendung Ariefianto , Rini Nur Hasanah , Hadi Suyono , Tri Nurwati , Eduard Muljadi , Hazlie Mokhlis
Small-scale wind turbines (SSWT) encounter a primary issue in power extraction, making the integration of DC-DC converters with maximum power point tracking (MPPT) crucial for performance enhancement. This study focuses on an evaluation of basic DC-DC converters, which offer many benefits when applied to SSWT systems. By considering efficiency, suitability, and electrical stress aspects, six DC-DC converter topologies consisting of boost, buck-boost, SEPIC, Cuk, zeta, and Luo, were tested under perturb and observe (P&O) and incremental conductance (INC) MPPT strategies. A 6.5-kW SSWT system, including a DC-DC converter and MPPT was designed in detail using PSIM. The results show that boost converter demonstrated the best overall performance in terms of power extraction, efficiency, and stress reduction, although its operation was limited to a narrower wind speed range. The zeta converter achieved efficiency and power extraction comparable to the boost converter with stable operation over a broader wind speed range, while the buck–boost converter offered step-up/step-down capability but experienced higher voltage and current stress. The SEPIC and Cuk converters showed low overall performance compared to others, whereas the Luo converter was better suited for low-wind-speed conditions.
Volume: 15
Issue: 2
Page: 674-691
Publish at: 2026-06-01

Comparative performance analysis of MPPT algorithms for wind power generation: P&O, INC, and TSR methods

10.11591/ijape.v15.i2.pp894-904
Muhammad Aulia Desky , Yulianta Siregar , Maksum Pinem
Wind energy has great potential, especially in areas with high wind speeds such as Southeast Aceh. However, wind speed fluctuations reduce turbine efficiency, necessitating maximum power point tracking (MPPT) for optimization. This study compared three MPPT methods perturb and observe (P&O), incremental conductance (INC), and tip speed ratio (TSR) to identify the most effective technique. Using MATLAB Simulink, simulations were conducted with wind speed data from Southeast Aceh and a DC-DC boost converter. Results showed the P&O method performed best, producing 847.83 W at 10 m/s, compared to 702.40 W for INC and 324.35 W for TSR. P&O also achieved the highest current output, reaching 16.45 A, while INC and TSR produced 13.66 A and 6.34 A, respectively. At lower wind speeds, P&O continued to outperform the other methods. This study concludes that the P&O method is the most effective method to improve the efficiency of wind turbines in Southeast Aceh, while INC shows moderate performance and TSR is the least effective method due to fluctuating wind speeds in a short time, so that TSR cannot maintain its maximum value. Therefore, P&O is recommended as the optimal MPPT technique for wind power plants in this region.
Volume: 15
Issue: 2
Page: 894-904
Publish at: 2026-06-01

Energy-aware dynamic adjustment integrated kookaburra optimization based efficient routing in WSN

10.11591/ijape.v15.i2.pp724-734
Shobanbabu R. Jaganathan , R. Sathya , R. Karthikeyan
In this paper a novel kookaburra optimization algorithm based dynamic adjustment strategy (KOA-DAS) method has been proposed in this paper for the energy efficient (EE) clustering and routing in wireless sensor network (WSN). The satin bowerbird optimization (SBO) is utilized for optimum cluster head (CH) selection. The proposed KOA-DAS model is utilized for an efficient routing through considering the fitness functions like distance from CH to base station (BS), remaining energy and intra-communication cost. The suggested framework has been assessed using a MATLAB simulator. The efficacy of the suggested KOA-DAS framework has been determined using evaluation metrics including execution time, average residual energy, network lifetime (NL), latency, packet delivery ratio (PDR), computation cost, energy consumption (EC), and alive nodes. The suggested KOA-DAS framework achieves the lowest energy efficiency by 23.44%, 19.31%, and 14.44% than the ASFO, EELCR, and K-LionER approaches. The proposed model effectively selects the CH and routing through dynamically adjusting parameters, which results in minimum EC and extending NL.
Volume: 15
Issue: 2
Page: 724-734
Publish at: 2026-06-01

Comparison of differential evolution optimization technique with other techniques in solving multi-objective optimal power flow

10.11591/ijape.v15.i2.pp663-673
Vineeta S. Chauhan , Jaydeep Chakravorty , Siddharthsingh K. Chauhan
Optimal power flow (OPF) is a complex, non-linear optimization problem focused on determining the steady-state operating parameters of power systems for economic and secure operation. The challenge intensifies due to numerous system constraints that must be satisfied simultaneously. Although various evolutionary algorithms (EAs) have been applied to OPF in recent decades, these algorithms often use unconstrained search strategies. A common approach to handle constraint violations is the static penalty function, which penalizes infeasible solutions. However, selecting suitable penalty coefficients typically involves time-consuming trial and error, affecting overall performance. This study explores the integration of advanced constraint handling (CH) techniques within the differential evolution (DE) framework to enhance the performance of optimal power flow (OPF) solutions. In particular, it looks at three approaches: a hybrid ensemble of two CH techniques (ECHT), a self-adaptive penalty method (SP), and superiority of viable solutions (SF). The IEEE 30-bus and IEEE-57 bus benchmark systems are used to evaluate the efficacy of these techniques under a variety of OPF goals, including lowering emissions and generation costs, cutting power losses, and enhancing voltage stability. We took into consideration both weighted-sum multi-objective and single-objective formulations. The simulation outcomes indicate that the proposed CH-DE approaches deliver robust and competitive optimization results, demonstrating improved constraint handling capabilities when compared to contemporary methods in the literature.
Volume: 15
Issue: 2
Page: 663-673
Publish at: 2026-06-01

Regenerative braking with battery management system in E-bike

10.11591/ijape.v15.i2.pp565-572
B. P. Divyashree , G. Lakith , H. N. Sukanya , Nagaling M. Gurav , Neeli Mallikarjuna , Unnam Anil
Energy neither be created nor be destroyed, but it can be transformed into other forms as per the law of conservation of energy. This information is epitomized by the regenerative braking system (RBS), which transforms kinetic energy into mechanical energy, thus recuperating waste energy into mechanical energy and making it beneficial. The regenerative braking have significant impact in electric vehicle technology due to the contemporary energy challenges and dwindling resources. Regenerative braking involves apprehending the lost kinetic energy during braking and converting it into a storable or instantly usable form. The recuperated kinetic energy can be reintegrated into vehicle’s power system or stored for further use, often in a battery, especially lithium-ion batteries which are managed by a battery management system (BMS) to ensure optimal performance and longevity. The utilization of various sensors by BMS to monitor parameters such as temperature, current, and voltage, entitling it to assess the battery’s health and determine its state of charge and discharge. Additionally, the BMS protects the battery against cavernous discharge and over-voltage, which can result from rapid discharging and charging currents, thereby optimizing the utilization of battery energy. In this article, the design of an electrical regenerative braking system with a battery management system in an electric bicycle (E-bike) applications are presented. The results show that the system works well in both battery-operated and regenerative modes. When in regenerative mode, the voltage and current stay within the specified range and are suitable for charging batteries. On the other hand, during regular operation, the increase in energy consumption is matched with the battery mode mileage.
Volume: 15
Issue: 2
Page: 565-572
Publish at: 2026-06-01
Show 34 of 2063

Discover Our Library

Embark on a journey through our expansive collection of articles and let curiosity lead your path to innovation.

Explore Now
Library 3D Ilustration