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Öğe Öğe Öğe Design of an off-grid model of micro-smart grid connection of an asynchronous motor fed with LUO converter(2018) Aksöz, AhmetThis paper proposes a model for a photovoltaic (PV)-based micro-smart grid system connection with asynchronous motor driving via LUO converters. LUO converter is a kind of DC–DC converter developed by Fang Lin Luo. It occupies less space than many other converters owing to a small number of electronics elements. In this model, a method was developed for forecasting the total power output under particular conditions of Ankara city (Capital of Turkey). PV cell parameters are determined firstly, and then PV array is formed including cells designed in order to calculate cumulative effect. It has tried to catch an approximation of necessary energy for systems that use the three-phase asynchronous machine using actual irradiation and temperature values. Then PV array output voltage, which is 12 V, has been converted 325 V thanks to LUO converter. Finally, space vector PWM has used for PWM production that supplies 325 V DC to 220 V AC via LUO converter for driving asynchronous motor. Instead of taking energy from the grid, energy saving is achieved by producing necessary energy from the solar panels. Thus, industrial consumption causing disruptive effects at grid can be decreased. The capability of system is demonstrated using MATLAB/Simulink simulation models.Öğe Elektrikli bir scooterda rejeneratif frenleme uygulamasının deneysel araştırılması(2023) Aksöz, AhmetBAP projesiÖğe Ensemble Learning Framework for DDoS Detection in SDN-Based SCADA Systems(2023) Aksöz, AhmetSupervisory Control and Data Acquisition (SCADA) systems play a crucial role in overseeing and controlling renewable energy sources like solar, wind, hydro, and geothermal resources. Nevertheless, with the expansion of conventional SCADA network infrastructures, there arise significant challenges in managing and scaling due to increased size, complexity, and device diversity. Using Software Defined Networking (SDN) technology in traditional SCADA network infrastructure offers management, scaling and flexibility benefits. However, as the integration of SDN-based SCADA systems with modern technologies such as the Internet of Things, cloud computing, and big data analytics increases, cybersecurity becomes a major concern for these systems. Therefore, cyber-physical energy systems (CPES) should be considered together with all energy systems. One of the most dangerous types of cyber-attacks against SDN-based SCADA systems is Distributed Denial of Service (DDoS) attacks. DDoS attacks disrupt the management of energy resources, causing service interruptions and increasing operational costs. Therefore, the first step to protect against DDoS attacks in SDN-based SCADA systems is to develop an effective intrusion detection system. This paper proposes a Decision Tree-based Ensemble Learning technique to detect DDoS attacks in SDN-based SCADA systems by accurately distinguishing between normal and DDoS attack traffic. For training and testing the ensemble learning models, normal and DDoS attack traffic data are obtained over a specific simulated experimental network topology. Techniques based on feature selection and hyperparameter tuning are used to optimize the performance of the decision tree ensemble models. Experimental results show that feature selection, combination of different decision tree ensemble models, and hyperparameter tuning can lead to a more accurate machine learning model with better performance detecting DDoS attacks against SDN-based SCADA systems.Öğe Fake Voice Detection: A Hybrid CNN-LSTM Based Deep Learning Approach(Institute of Electrical and Electronics Engineers Inc., 2024) Oyucu, Saadin; Çelimli, Derya Betül Ünsal; Aksöz, AhmetThis study focuses on developing and evaluating a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) based deep learning model for detecting fake voice recordings. The proposed model addresses the critical issue of artificial intelligence-generated speech mimicking human voices, which can potentially be used for malicious purposes, thereby endangering individuals' privacy and safety. A comprehensive dataset comprising 5,889 real and 5,889 fake voice samples was utilized for this research. The dataset underwent rigorous preprocessing, including segmentation into fixed-length windows and normalization. The hybrid CNN-LSTM model was then trained and validated systematically involving exploratory data analysis and extensive hyperparameter tuning. The experimental results demonstrated that the proposed model achieved an accuracy of 99.2%, an F1 score of 99.2%, a recall of 99.4%, and a precision of 99.0%, indicating its robust performance in distinguishing between real and fake voices. The findings underscore the potential of the hybrid CNN-LSTM model as a powerful tool for safeguarding digital communications against the growing threat of fake voices. © 2024 IEEE.Öğe Öğe Improving Performance of Three-Phase Slim DCLink Drives Utilizing Virtual Positive Impedance Based Active Damping Control(2018) Aksöz, AhmetIn this paper, a virtual positive impedance (VPI) based active damping control for a slim DC-link motor drive with 24 section space vector pulse width modulation (SVPWM) is proposed. Utilizing the proposed control and modulation strategy can improve the input of current total harmonic distortion (THD) while maintaining the cogging torque of the motor. The proposed system is expected to reduce the front-end current THD according to international standards, as per IEC 61000 and IEEE-519. It is also expected to achieve lower cost, longer lifetime, and fewer losses. A permanent magnet synchronous motor (PMSM) is fed by the inverter, which adopts the 24 section SVPWM technique. The VPI based active damping control for the slim DC-link drive with/without the 24 section SVPWM are compared to confirm the performance of the proposed method. The simulation results based on MATLAB are provided to validate the proposed control strategy.Öğe Inductive Power Transfer for Electric Vehicle Charging Applications: A Comprehensive Review(2022) Aksöz, AhmetNowadays, Wireless Power Transfer (WPT) technology is receiving more attention in the automotive sector, introducing a safe, flexible and promising alternative to the standard battery chargers. Considering these advantages, charging electric vehicle (EV) batteries using the WPT method can be an important alternative to plug-in charging systems. This paper focuses on the Inductive Power Transfer (IPT) method, which is based on the magnetic coupling of coils exchanging power from a stationary primary unit to a secondary system onboard the EV. A comprehensive review has been performed on the history of the evolution, working principles and phenomena, design considerations, control methods and health issues of IPT systems, especially those based on EV charging. In particular, the coil design, operating frequency selection, efficiency values and the preferred compensation topologies in the literature have been discussed. The published guidelines and reports that have studied the effects of WPT systems on human health are also given. In addition, suggested methods in the literature for protection from exposure are discussed. The control section gives the common charging control techniques and focuses on the constant current-constant voltage (CC-CV) approach, which is usually used for EV battery chargers.Öğe "Multi-Stage Learning Framework Using Convolutional Neural Network and Decision Tree-Based CV-Ahmet AKSÖZ Classification for Detection of DDoS Pandemic Attacks in SDN-Based SCADA Systems(2024) Aksöz, AhmetSupervisory Control and Data Acquisition (SCADA) systems, which play a critical role in monitoring, managing, and controlling industrial processes, face flexibility, scalability, and management difficulties arising from traditional network structures. Software-defined networking (SDN) offers a new opportunity to overcome the challenges traditional SCADA networks face, based on the concept of separating the control and data plane. Although integrating the SDN architecture into SCADA systems offers many advantages, it cannot address security concerns against cyber-attacks such as a distributed denial of service (DDoS). The fact that SDN has centralized management and programmability features causes attackers to carry out attacks that specifically target the SDN controller and data plane. If DDoS attacks against the SDN-based SCADA network are not detected and precautions are not taken, they can cause chaos and have terrible consequences. By detecting a possible DDoS attack at an early stage, security measures that can reduce the impact of the attack can be taken immediately, and the likelihood of being a direct victim of the attack decreases. This study proposes a multi-stage learning model using a 1-dimensional convolutional neural network (1D-CNN) and decision tree-based classification to detect DDoS attacks in SDN-based SCADA systems effectively. A new dataset containing various attack scenarios on a specific experimental network topology was created to be used in the training and testing phases of this model. According to the experimental results of this study, the proposed model achieved a 97.8% accuracy rate in DDoS-attack detection. The proposed multi-stage learning model shows that high-performance results can be achieved in detecting DDoS attacks against SDN-based SCADA systems.Öğe An Optimized Overcurrent Protection Study Using Enough Number of SFCL at Optimal Points of a Distributed Real City Grid(2021) Aksöz, AhmetIn this paper, a new approach to an optimized overcurrent protection in a distributed real city grid is presented. A superconducting fault current limiter (SFCL) can be used for solving overcurrent problems. The most important overcurrent problem in the grid are the short circuit currents, especially in high voltage lines. Therefore, many devices connected to the grid could be damaged. In spite of the protection advantages of the SFCLs, using them for all connection nodes of the grid is an expensive and complicated solution. If the optimal points of the grid to use the SFCL are decided, the most appropriate number of SFCL can be used. A 2.026 MW powered distributed real city grid application is realized in Sincan providence in Ankara City. Also, the distribution line is 0.4 kV and the transmission line is 34.5 kV. Besides, the distributed grid is fed by two generators and two renewable energy sources which are a wind turbine and a solar power plant. Electricity consuming parts of the grid are greenhouses, loads and electrical transmission/distribution/customer lines. In order to analyse the grid, two options are simulated. Firstly, any resistive type superconducting fault current limiters (RSFCL) have been used for short-circuit protection. Results of the first option are not acceptable according to overcurrent standards. The second option is that RSFCLs are used at the optimal points of the grid. Optimal nodes are founded by the genetic algorithm. When the RSFCL is positioned at the determined optimal points, the fault current in some busbars has been obtained 82.78% less.Öğe Optimum Enerji Verimliliğini Hedefleyen Rastgele Ağaçlar ve Yapay Arı Kolonisi Yöntemi ile Otonom Robotlarda Yol Planlama Algoritması(2019) Torun, Yunis; Ergül, Züleyha; Aksöz, AhmetOperatörsüz hareket eden robotların (otonom robotlar) hareket sırasında engellere çarpmadan, en kısa yol ve en yumuşak yolu seçerek hedef konumuna ulaşması büyük önem taşımaktadır. Bu çalışma, yol planlama eyleminde sezgisel ve klasik yöntemlerin avantajlarını birleştirmek, dezavantajlarını ise minimize etmek için, iki yöntemin melez kullanımı ile gerçekleştirildi. Öncesinde klasik yöntemlerden, Rastgele Ağaçlar yöntemi (Rapidly-exploring Random TreeRRT) ve sezgisel yöntemlerden de Yapay Arı Kolonisi yöntemi (Artificial bee colony-ABC) ayrı ayrı harita üzerinde değerlendirildi. Akabinde bu iki yöntemin melez kullanılmasıyla oluşturulan yaklaşım değerlendirildi. Söz konusu yapılan bu melez değerlendirme, önceden keşfedilmiş, başlangıç ve hedef noktası belli bir haritada yapıldı. Yol kriterlerini optimize ederek, MATLAB Robotik Sistem Araç Kutusu (Robotic System Toolbox) üzerinden benzetimi gerçekleştirildi. Sunulan melez algoritmada, takip edilen yol hesaplanırken, enerji verimliği ile birlikte yol güvenliği de dikkate alındı. İki tekerli mobil robotun enerji tüketimini RRT, ABC ve melez RRTABC yöntemlerinin kullanılması ile elde edilen yollarda hesaplandı ve karşılaştırıldı. Yapılan karşılaştırmalar sonucunda melez algoritmanın daha verimli çalıştığı gözlemlendi.Öğe PMSM Control using the 3DSVPWM to Decrease Motor Torque Ripple and Motor Current THD with a New Model(2019) Saygın, Ali; Aksöz, AhmetIn this paper, a new model for a PMSM (permanent magnet synchronous motor) driver is proposed. The proposed model is envisionedas a better modulating drive current waveform. In the proposed system the modulating drive motor current waveform is more similarto ideal sinusoidal waveform. Advanced IGBTs and snubber circuits can be employed in the design of the driver to obtain highperformance with a simultaneous reduction in THD (total harmonic distortion) and torque ripple of the motor. The proposed conceptoffers a significant decreasing for driver harmonics compared to classical SVPWM used. The inverter can be operated in 3-phase and20 kHz switching frequency. A PMSM motor is operated at 3kW and 48V with the proposed model is evaluated via simulation with acorresponding SVPWM (space vector pulse width modulation) method. Results of torque ripple and THD of the motor currents on themodel are discussed.Öğe Pozisyon Doğruluğu için Kalıcı Mıknatıslı Senkron Motorlarda Luenberg Durum Gözlemcisi Tabanlı Resolver Dijital Konverter Tasarımı(2020) Torun, Yunis; Aksöz, AhmetBu çalışmada, geri besleme sinyalleri olarak bir resolver sensörün çıkış sinyalleri kullanılarak bir elektrik motorunun pozisyon kontrolü sunulmuştur. Resolver sensörü, motor rotor açısının konum verisini elde etmek için kullanılır. KMSM (Kalıcı mıknatıslı Senkron Motor)'un enerji verimliliği motor pozisyon hatalarından etkilenir. Çünkü motor pozisyonu hataları enerji kaybına neden olur. Artan pozisyon doğruluğu aynı zamanda enerji verimliliğini de arttırır. Resolver sensörü yüksek çözünürlüğe sahiptir, ancak bu doğruluk optimize edilebilir. RDK (resolver dijital konverter) içerisinde bir gözlemci yöntemi kullanılabilir. Özellikle, Luenberg durum gözlemcisi kararlı halde daha iyi parametreler üretir. KMSM’lerde referans hızda nominal yük altında Luenberg durum özlemcisi tabanlı RDK tasarımı klasik RDK ile karşılaştırılmıştır. İlk olarak, KMSM'un matematiksel modeli kararlı durumda bulunmuştur. Ek olarak, resolver ve RDK teorik olarak açıklanmıştır. Böylece, hata değerleri PMSM için bulunabilir. Ayrıca, RDK içerisinde Luenberg durum gözlemcisi, 7,07 V(rms) ve 400Hz’lik bir resolver için tasarlanmıştır. Mutlak pozisyonu ve maksimum doğruluğu veya minimum elektrik hatasını elde etmek için bir benzetim modeli gerçekleştirilmiştir. Önerilen Luenberg durum gözlemcisi esaslı yöntem modelde uygulanmaktadır. Bu nedenle, Luenberg durum gözlemcisi enerji verimliliğine dayalı RDK performansı, klasik RDC kullanarak tartışılmaktadır.Öğe Prediction and modelling of energy consumption on temperature control for greenhouses(2018) Aksöz, AhmetPrediction of the energy consumption is the most important topic for planning to build an energy power station. This energy power station can be non-renewable sources power plants or renewable power plants like wind and solar. Prediction of the energy consumption also figures out load modeling problem in new smart grid applications. In this study, energy consumption model is developed for temperature control of a greenhouse. Artificial Neural Network based modeling is advanced with temperature of inner, temperature of outer and temperature of soil. So, these temperatures are inputs in the ANN based model. In addition, the output of the ANN is energy demand that is strongly related with temperature data.Öğe A review of Modular Multilevel Converter for Stationary Applications(2020) Aksöz, AhmetA modular multilevel converter (MMC) is an advanced voltage source converter applicable to a wide range of medium and high-voltage applications. It has competitive advantages such as quality output performance, high modularity, simple scalability, and low voltage and current rating demand for the power switches. Remarkable studies have been carried out regarding its topology, control, and operation. The main purpose of this review is to present the current state of the art of the MMC technology and to offer a better understanding of its operation and control for stationary applications. In this study, the MMC configuration is presented regarding its conventional and advanced submodule (SM) and overall topologies. The mathematical modeling, output voltage, and current control under different grid conditions, submodule balancing control, circulating current control, and modulation methods are discussed to provide the state of the MMC technology. The challenges linked to the MMC are associated with submodule balancing control, circulating current control, control complexity, and transient performance. Advanced nonlinear and predictable control strategies are expected to improve the MMC control and performance in comparison with conventional control methods. Finally, the power losses associated with the advanced wide bandgap (WBG) power devices (such as SiC, GaN) are explored by using different modulation schemes and switching frequencies. The results indicate that although the phase-shifted carrier-based pulse width modulation (PSC-PWM) has higher power losses, it outputs a better quality voltage with lower total harmonic distortion (THD) in comparison with phase-disposition pulse width modulation (PD-PWM) and sampled average modulation pulse width modulation (SAM-PWM). In addition, WBG switches such as silicon carbide (SiC) and gallium nitride (GaN) devices have lower power losses and higher efficiency, especially at high switching frequency in the MMC applications.Öğe SEPIC converter with an LC regenerative snubber for EV applications(2020) Aksöz, AhmetA Single-Ended Primary-Inductor Converter (SEPIC) converter with an Inductor-Capacitor (LC) regenerative snubber is proposed to reduce Electromagnetic Interference (EMI) for Electric Vehicle (EV) applications. The switching energy is transferred through a capacitor to an inductor which is coupled to SEPIC inductors. This technique reduces the number of components and also returns some of switching energy to SEPIC converter. The mathematical analysis and optimization of LC snubber with respect to number of turns is also presented. Spice simulations and experimental results are provided to verify its performance. The proposed LC regenerative snubber reduces the peak voltage by 16 V on the switching transistor during the switching transient. It is also indicated that 8 dB reduction is achieved in the EMI measurements at ringing frequency and 10 dB reduction at high frequency band.Öğe Signal Injection Based Initial Rotor Position Alignment for PMSM Driven FSTP Inverter(2020) Aksöz, AhmetA PMSM drive with an incremental encoder or using sensorless control requires alignment to a predetermined rotor position (initial position) or initial rotor position detection at start-up. It is desired to lock the rotor to a known state (usually zero angle) at start-up if the initial rotor position detection is not available or difficult to obtain. In this work, a simple and proper zero angle initial rotor position alignment of four-switch three-phase (FSTP) inverter-based PMSM drive is proposed. Low-frequency voltage signal is applied to the d-axis voltage reference of the open-loop FSTPI based PMSM drive scheme without requiring complex trigonometric calculations, PI current regulators and current sensing. Therefore, fluctuated capacitor voltages at the DC-link are obtained allowing current flown through phase a locking the rotor with zero angle, properly. The proposed method has been implemented using a low-cost FSTP voltage source inverter (VSI) for PMSM drive with a floating-point TMS320F28335 DSP. The effectiveness and the feasibility of the proposed zero angle initial rotor position alignment method for PMSM driven by FSTP inverter have been demonstrated through experimental results.Öğe Switched Reluctance Motors and Drive Systems for Electric Vehicle Powertrains: State of the Art Analysis and Future Trends(2021) Aksöz, AhmetThis paper presents a detailed literature review on switched reluctance motor (SRM) and drive systems in electric vehicle (EV) powertrains. SRMs have received increasing attention for EV applications owing to their reliable structure, fault tolerance ability and magnet free design. The main drawbacks of the SRM are torque ripple, low power density, low power factor and small extended speed range. Recent research shows that multi-stack conventional switched reluctance motors (MSCSRM) and multi-stack switched reluctance motors with a segmental rotor (MSSRM-SR) are promising alternative solutions to reduce torque ripples, increase torque density and increase power factor. Different winding configurations such as single-layer concentrated winding (SLC), single layer mutually coupled winding (SLMC), double layer concentrated winding (DLC), double layer mutually coupled winding (DLMC) and fully-pitched winding (FP) are introduced in the literature in recent years to increase average torque and to decrease torque ripples. This research analyzes winding methods and structure of the SRMs, including conventional and segmental rotors. They have been compared and assessed in detail evaluation of torque ripple reduction, torque/power density increase, noise/vibration characteristics and mechanical structure. In addition, various drive systems are fully addressed for the SRMs, including conventional drives, soft-switching drives, drives with standard inverters and drives with an integrated battery charger. In this paper, the SRM control methods are also reviewed and classified. These control methods include strategies of torque ripple reduction, fault-diagnosis, fault-tolerance techniques and sensorless control. The key contributions of this paper provide a useful basis for detailed analysis of modeling and electromechanical design, drive systems, and control techniques of the SRMs for EV applications.Öğe Yerli Uçuş Kontrol Kartına Sahip Zirai Görüntüleme Dronu(2023) Aksöz, AhmetYerli Uçuş Kontrol Kartına Sahip Zirai Görüntüleme Dronu-KOSGEB PROJESİ
