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Öğe A High Gain Switched-Inductor-Capacitor DC-DC Boost Converter for Photovoltaic-Based Micro-Grid Applications(China Electric Power Research Inst, 2024) Ertekin, DavutMaximum power point tracking (MPPT) systems are being developed to produce switching pulses with proper duty ratios for power switches to exert photovoltaic (PV) panels under maximum instantaneous generated power, usually through a traditional DC-DC boost converter. The fundamental issue, particularly for micro-grid and small-scale green DC or AC energy applications, is that the voltage supplied by the MPPT boost converter is insufficient. In order to increase resulting MPP voltage, this research proposes a new high-voltage gain DC-DC boost converter for a cascade connection with an MPPT boost converter. Input side of the proposed converter employs a switched-inductor cell to reduce input current source ripples which is a critical problem in PV systems for high-reliability applications. Additionally, a switched-capacitor cell is used at the converter's output side to boost voltage gain and reduce voltage stress across converter's power switches, which is a crucial factor for longer life of PV panel and proposed converter components, particularly semiconductor devices. Performance of the converter is assessed while taking into account variations in irradiation and temperature brought on by changing weather conditions. A prototype converter at a laboratory scale is utilized and examined. Outcomes of hardware tests support the findings of theoretical and simulation studies.Öğe A Levenberg–Marquardt Learning-Based Artificial Neural Network Controller for Battery Charging in Hydrogen and Solar-Powered Electric Vehicle Stations(John Wiley and Sons Ltd, 2026) Özden, Mustafa; Ertekin, DavutGreen energy and renewable energy sources (RESs) are between the most important topics in power, energy, and transportation and are crucial for sustainability for next generations. When a hydrogen fuel cell or solar array is used for the electric vehicle (EV), the next step is using an efficient, high power, and simple structure based power electronics converter to storage the energy of these RESs into the battery pack. The integration of artificial intelligence into the control and optimization of DC–DC power converters presents promising opportunities in improving energy management and efficiency in EV sector. This study presents a low-input current and low voltage stress topology for application in fuel cell to battery charging systems in EVs. A current filter by forming a switched inductor cell at the input side of the converter guarantees a small ripple for input sources that enhances the longevity and long-life of the FC stacks or solar panels. The application of the switched capacitor circuits at the input and end sides of the converter decreases the voltage stress across the semiconductor devices and enhances the mean time to failure rate of the converter that is between the most important features of a converter. The presented topology enhances the input voltage to 7 and 19 times for duty ratios equal to 0.5 and 0.8, respectively, while the switch experiences three and nine times the input voltage for the same duty ratios, which is considerable. The configuration of the diodes and capacitors in the switched capacitor, by dividing the total voltage stress, results in impressively low voltage ripples. This converter includes one power switch, which minimizes the complexity of the controller and enhances the feasibility. The converter design incorporates a three-layer, three-input artificial neural network structure. The regression values were 0.982 for training, 0.983 for testing, and 0.9827 overall, indicating minimal prediction error and confirming the effective training of the neural network model. The laboratory test results for power levels around 200 W have been presented and confirm the correctness of the proposed algorithm and the application of the proposed converter. To obtain 0.5 A for the load under a 350 VDC output voltage, the input source presents an average current equal to 8 A, and the switch experiences around 160 V voltage stress across the drain–source pins. Results show that Inductor L2 has lower current stress than Inductor L1. © 2026 Wiley-VCH GmbH.Öğe Adaptive neuro fuzzy control of a high gain bidirectional power converter for photovoltaic-hydrogen renewable electric vehicles with enhanced lifespan and reliability(Elsevier Gmbh, 2026) Ertekin, Davut; Ozden, MustafaThe demand for green energy and application of hydrogen or photovoltaic (PV) for electrical vehicles (EVs) are enhancing steadily each day. DC-DC converters are critical power conversion systems that regulate voltage and current levels for battery packs in electric vehicles (EVs) powered by fuel cells (FCs) or PV panels and set the voltage for electric motor through an inverter circuit. The longevity of renewable energy sources (RESs) such as the FCs and PV arrays is heavily influenced by the current drawn by the DC-DC converter. Additionally, the converter topology must be cost-effective, minimize voltage and current stresses on semiconductor devices, offer ease of control, and provide flexible voltage outputs to meet the dynamic demands of the battery pack. This study introduces a switching DC-DC power converter designed specifically for FC-based electric vehicles (FCEVs), controlled by an innovative adaptive neuro fuzzy controller (ANFC). The high gain of the proposed converter enables the energy obtained from FCs and PV cells to be stored in a high-voltage battery pack and subsequently used to drive the electric motor and other electric vehicle components (such as lighting, heating, or cooling). This implies that, in an electric vehicle, it is sufficient to use only the proposed power converter instead of employing separate DC-DC converters for different energy sources such as PV or FCs. Subsequently, the stored energy can be used to operate the motor by providing the input voltage to the inverter. This approach makes the overall system more efficient and cost-effective. At the end of the simulation studies, it was observed that the proposed controller successfully ensures the control of the DC-DC converter, that no overshoot or oscillation occurs at the converter output, that an extremely short settling time of 0.016 s is achieved, and that a very low steady-state error of 0.7 is obtained. Experimental results for the proposed power converter are presented, thereby validating the theoretical findings.Öğe ARVIN converter: a bidirectional DC/DC converter for grid-connected G2V/V2G energy storage and electrification approaches(Springer, 2024) Ertekin, DavutBidirectional DC-DC converters play a crucial role in enabling the transfer of energy between low-voltage and high-voltage sides, a fundamental requirement in applications like vehicle-to-grid and grid-to-vehicle scenarios. The motivation behind the application of common ground converters is the quest for enhanced reliability and safety while also seeking to prevent electromagnetic interferences and address the issue of dvdt\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\frac{{\text{d}}v}{{\text{d}}t}$$\end{document} between the input and output sides. This paper introduces an enhanced SEPIC converter with a common ground configuration, incorporating a quadratic switched-inductor cell. This innovative design allows for both voltage step-up and step-down operations in both directions of energy flow. The converter exhibits substantial gains and efficiency. To validate the theoretical findings, a 300W laboratory prototype of the converter was constructed and tested. Control and switching operations are managed by a DSP-based microcontroller operating at a sampling speed of 80 Mb/s, utilizing a fuzzy logic control technique. The Arvin converter, as suggested, offers numerous advantages that can be encapsulated as follows: It introduces a common ground-based high-gain topology, governed by a simple fuzzy logic controller, thus eliminating the requirement for intricate current and voltage equations for circuit elements. It makes the bidirectional energy flow possible and adopts a cost-effective, non-isolated configuration with a reduced count of semiconductor devices and passive components. The designed circuit was named ARVIN in honor of my 7-year-old son.Öğe Design and experimental validation of an artificial neural network-SVPWM controller for a novel micro grid-tied fuel cell-based 3-phase boost inverter(Elsevier Ltd, 2024) Baltacı, Kübra; Ertekin, Davut; Bayrak, GökayA grid-tied fuel cell (FC) system demands efficient power conversion, power quality preservation, grid stability, power flow management, renewable energy source (RES) integration, and enhanced grid resilience. Achieving these goals requires a precise inverter circuit switch approach. A boost power converter connected to the FC stack ensures voltage regulation, power conditioning, efficient power transfer, system integration, control, and protection. This enhances FC system adaptability and compatibility across various applications, minimizing input current ripples for prolonged FC lifespan. This study introduces a novel DC-DC boost converter with an artificial neural network (ANN) controller to reduce FC input current ripples and enhance FC stack-generated voltage for grid applications. It also presents a space vector sinusoidal pulse width modulation (SVPWM) technique for FC-based three-phase grid-tied inverters. This offers improved voltage utilization, precise voltage and current control, reduced harmonic distortion, rapid response, flexibility, scalability, reduced total harmonic distortion (THD), and over-modulation capability. The proposed SVPWM technique utilizes a digital signal processing (DSP)-based controller, combining high-speed processing, precision, and real-time capabilities to enhance system performance and efficiency. © 2023 Hydrogen Energy Publications LLCÖğe Design and Implementation of the Python-Driven Digital Horn System: A Novel Approach for Electric Vehicle Sound Systems(Mdpi, 2024) Tekin, Hakan; Karsiyaka, Hikmet; Ertekin, DavutElectric and hybrid vehicles are known for their significant reduction in road noise. However, concerns have emerged regarding their silent operation, potentially increasing risks for other road users. To mitigate this, the Acoustic Vehicle Alert System (AVAS) has been mandated by regulations such as R138 by UNECE in the USA and Europe. This regulation dictates the generation of sound in electric vehicles of categories M and N1 during normal, reverse, and forward motion without the internal combustion engine engaged. Compliance involves meeting specific sound requirements based on vehicle mode and condition. This paper introduces a Python-based approach to designing digital horn sounds, leveraging music theory and signal processing techniques to replace traditional mechanical horns in electric vehicles equipped with AVAS devices. The aim is to offer a practical and efficient means of generating digital horn sounds using this software. The software includes an application capable of producing and customizing horn sounds, with the HornSoundGeneratorGUI class providing a user-friendly interface built with the Tkinter library. To validate the digital horn produced sounds by the software and ensure compliance with AVAS regulations, comprehensive electrical and acoustic tests were conducted in a fully equipped quality laboratory. The results demonstrated that the sound levels achieved met the required 105-107 dB/2 m standard specified by the regulation.Öğe Enhanced grid stability and prolonging life span in renewable energy power converters using an advanced Sugeno-type AI-based neuro-fuzzy control(Springer Science and Business Media Deutschland GmbH, 2025) Özden, Mustafa; Ertekin, Davut; Baltacı, KübraA significant challenge lies in renewable energy sources incapacity to generate high voltages and their limited life spans when subjected to high-ripple conditions. This study introduces an innovative Sugeno-type neuro-fuzzy controller for an interleaved power converter configuration aimed at mitigating the input current ripples associated with these renewable energy sources, directly addressing the longevity concern controlled by an advanced neuro-fuzzy controller. The proposed converter employs a switched capacitor (SC) cell to amplify the generated voltage within the boost converter framework. Key attributes of the proposed converter include high voltage gain, enhanced efficiency and the utilization of short-duty ratio time intervals to minimize conduction power losses at elevated voltages. Furthermore, through interleaved configuration, the current ripple from the source is diminished while the SC cell concurrently amplifies the voltage gain. A Sugeno-type neuro-fuzzy control method, based on artificial intelligence, is employed for the proposed converter to drive the switches and produce an accurate output voltage. Since the converter is primarily built on a fuzzy controller, the proposed method is mathematically simple and easy to implement. The main contribution of the proposed control approach lies in the sampling of both the input and reference, as well as the output voltages, and the generation of precise duty cycles based on the sampled reference output voltage. Due to its capability of generating high voltages, the proposed converter and control system are suitable for use in DC grids and vehicle-to-grid applications. © The Author(s) 2025.Öğe Evaluation and Implementation of EMI/EMC Compliance for a Proposed Power Electronics- Based Converter Topology for Electric Vehicles(Kaunas Univ Technology, 2024) Tekin, Hakan; Vatansever, Seyit; Ertekin, DavutThe demand for high-gain, efficient, and costeffective power converters with simple control mechanisms to connect electric vehicle batteries to the grid is increasing. This study introduces a switched capacitor-based power boost converter circuit to meet these needs. The minimal number of power switches in the circuit simplifies control operations and improves practical applicability. The proposed converter boosts the battery pack voltage by a factor of 5 and 11 for duty ratios of 0.5 and 0.8, respectively, which is significant compared to conventional boost converters. However, designing an electromagnetic interference (EMI) filter is crucial when a power converter board requires the application of a wide range of switching frequencies to enhance electromagnetic compatibility (EMC) immunity. Therefore, as the next step, the EMI/EMC filter design stages were discussed for the proposed converter. For this purpose, 15 printed circuit board (PCB) design rules were checked using the Altium Designer EMI Design Rule Checker, and board EMI/EMC compatibility was analysed. The resonance between the power and ground layers in the PCB was assessed using the plane resonance analyser. The results of simulation and laboratory tests are presented, which confirms the theoretical studies. On the basis of the software results, the points on the electronic board most susceptible to visual interferences have been identified. To minimise these EMI/EMC errors, it is suggested to add electronic components, such as capacitors, at these points according to mathematical and software findings.Öğe Levenberg-Marquardt Algorithm-Based Neural Network Smart Control Strategy for a Low-Input Current Ripple and High-Voltage Gain Power Converter in Fuel-Cells Energy Systems(Ieee-Inst Electrical Electronics Engineers Inc, 2025) Ozden, Mustafa; Ertekin, Davut; Siano, PierluigiA crucial aspect of DC-DC converters employed in renewable energy sources such as fuel cells is their ability to exhibit substantial increases in DC voltage and maintain an efficient structure while minimizing input current ripple. These factors play a pivotal role in enhancing the longevity of these energy sources and ensuring their compatibility with high-voltage AC and DC grids. This study introduces a high-gain DC-DC step-up converter that incorporates a continuous input current cell and a switched capacitor voltage-boosting output cell to address these requirements. The control process of this proposed converter is executed using an artificial neural network based on the Levenberg-Marquardt learning algorithm. The primary difference in this research lies in obtaining the artificial neural network-based controller directly from the circuit's characteristic equations, rather than generating it through another controller. A feedback control strategy has been formulated, where the artificial neural network consistently produces duty increment values based on the reference voltage. Additionally, the network's input includes not only the reference signal but also the circuit input voltage and output current value. As a result, the stability of the circuit's output voltage is maintained against variations in input voltage and load changes. A laboratory-designed workbench underwent testing, and the experimental results substantiated the theoretical inquiries and simulation outcomes.Öğe Neuro-fuzzy-SVPWM switched-inductor-capacitor-based boost inverter for grid-tied fuel cell power generators, design and implementation(Pergamon-Elsevier Science Ltd, 2024) Ertekin, Davut; Ozden, Mustafa; Deniz, Adnan; Toprak, Muhammed ZeydHydrogen energy shows promise as a renewable energy source for various applications like battery and electric vehicle charging stations, as well as grid connections. However, high current ripple from fuel cells (FCs) and inadequate voltages for grid use pose challenges. This study presents a novel solution using neural fuzzy network control in a high-gain DC-DC boost converter to address these issues. The suggested converter charges in parallel and discharges in series, minimizing the current ripple range in the fuel cell network. Additionally, the switchcapacitor cell efficiently increases the output voltage. In this study, a Neuro-fuzzy system with 9 rules is trained meticulously over 50 epochs using hybrid optimization and grid partition methods, achieving a low training error of 0.045 with 522,064 samples. The neural fuzzy network, employing the weighted average method for Defuzzification, produces duty cycle values from 0.02 to 0.5 in response to input signals. Additionally, an innovative Space Vector Pulse Width Modulation (SVPWM) approach within the inverter circuit enhances voltage generation precision and power quality for grid delivery, notably reducing current ripple and ensuring stable power supply. This combined with the neural fuzzy network in the converter efficiently converts hydrogen energy into AC voltage for seamless grid integration, revolutionizing boost converter efficiency and advancing hydrogen energy utilization across various energy sectors.Öğe Novel Control Scheme to Reduce THD in Bidirectional Three-Phase Inverter Using a Three-Phase Unfolder for the Grid Forming Operation(Wiley, 2025) Celebi, Mehmet; Ertekin, DavutRecent trends emphasise the significance of bidirectional power conversion systems in grid-forming operations. Minimising total harmonic distortion (THD) in these systems is crucial for enhancing power quality, efficiency and equipment lifespan. This study proposes a novel reference signal modification control scheme to reduce THD in a bidirectional inverter by adjusting the DC-Link Voltage reference based on AC load feedback. Comparative analysis with conventional systems across various load types demonstrates superior performance, particularly with induction machine loads. The proposed control model involves multiple stages, including error computation, averaging, dynamic error handling, reference modification and regulation using a PI control block. This approach effectively manages error dynamics in the inverter topology and eliminates electromagnetic interference in the PCB without determining any additional theoretical approach. Both simulated and experimental results validate the theoretical analyses, showcasing the efficacy of the proposed method. Its simplicity in modifying the reference voltage makes it suitable for situations where controllers lack the capability to effectively manage desired outputs.Öğe The Design and Practical Realization of an Adaptable Grid Integrating Hydrogen Fuel Cell Setup With a Fuzzy-Logical Controller-Based SVPWM Boosted Inverter(Ieee-Inst Electrical Electronics Engineers Inc, 2024) Ertekin, Davut; Baltaci, Kubra; Toprak, Muhammed Zeyd; Celebi, Mehmet; Ozden, Mustafa; Siano, PierluigiThe primary and fundamental requirement for a fuel cell (FC) stack is its reliable operation under various operating conditions. When FC stacks are used as the input voltage source with high ripple currents, the overall lifespan of the FC system decreases. Hence, power converter configurations need to minimize the current ripples originating from these sources. Additionally, the generated voltage from the FC stack is often lower than the required voltage level for grid connection. This paper presents a fuzzy logic controller (FLC)-equipped high-gain single-switched DC-DC boost converter. The proposed power converter topology utilizes an improved switched inductor and switched capacitor configuration to minimize input current ripples and enhance the voltage gain. The switched inductor cell is designed in such a way that its inductors charge and discharge simultaneously, effectively minimizing the input current ripple. Additionally, the proposed DC-DC boost converter utilizes a switched capacitor cell to double the generated voltage. The FLC offers real-time visualization and digital signal processing capabilities, and it is compatible with MATLAB software. For grid connection purposes, a space vector pulse width modulation (SVPWM)-based switching system is recommended, utilizing a full bridge inverter. The SVPWM technique is implemented by representing the desired output voltage with an equivalent vector VREF rotating counterclockwise, integrated with a digital signal processing (DSP)-based controller. The DSP microcontroller employed in this study operates at an 80 Mb/sec sampling speed and offers several advantages, including the ability to perform complex calculations, implement advanced control algorithms, and process signals in real-time. These capabilities contribute to enhanced performance, efficiency, and accuracy. Laboratory studies have been conducted to validate the accuracy and effectiveness of the theoretical investigations.Öğe Başlıksız(MDPI, 2021) Bayrak, Gökay; Ertekin, Davut; Alhelou H.H.; Siano P.Each country must determine the Grid Code conditions and apply these criteria to integrate distributed generation (DG) systems into the existing electricity grid and to ensure a stable power system. Thus, experimental studies are required to provide an effective, national, and specific Grid Code. In this study, the Turkish Grid Code’s electrical criteria were examined, and the application of these criteria was carried out on a developed PV-based DG. A real-time energy management system (RTEMS) was proposed in the study. Electrical parameters on the developed DG were monitored in real-time by considering IEEE 1547, IEEE 929–2000, and Turkey’s electrical criteria. A practical grid code study was firstly investigated in detail about the Turkish Grid Code by a developed real-time monitoring-control and protection system. The proposed RTEMS method in the study is implemented as an inverter-resident system; thus, it provides advantages over many energy management systems embedded in the inverter. The degradation in power quality and non-detection zone (NDZ) problems encountered in active and passive island mode detection methods developed embedded in the inverter are eliminated in the proposed method. With the RTEMS method, where under and over-voltage, under and over voltage frequency, and unintentional island mode events can be detected in real-time, both the existing grid-code requirements are met, and the existing power quality and NDZ problem is eliminated with the recommended inverter-independent RTEMS method.Öğe Başlıksız(Institute of Electrical and Electronics Engineers Inc., 2021) Ertekin, Davut; Bilgiç, Mesut Berke; Mutlu, BülentPower electronics circuits are one of the vital and important parts of the industrial applications, where different levels of the DC and AC voltages and currents are necessary to be applied to the different electronic and electrical devices and machines including the test approaches or working under industrial voltages. Meanwhile, many of these devices are designed to work under a certain and fixed industrial level of voltages like 48VDC, 24VDC, 12VDC or 5VDC, but sometimes, another levels of the voltage for a special device can be an issue. Therefore, the converting an AC voltage to a fixed, controllable and robust DC voltage under different level of the load values is necessary. Furthermore, the variation of the input AC voltage also should be considered and the load DC voltages should be hold fixed. This paper uses a Full-wave rectifier circuit to convert the AC voltage to the DC voltage and in the next step this voltage is enhanced and fixed by using a DC-DC step-up converter. Both rectifier and boost converters are high gain since sometimes it is necessary to convert the grid 220VAC to a small DC voltage or enhance a small DC to a higher DC voltage. The proposed converter can be used separately as a high gain AC-DC rectifier or a high gain DC-DC converter, or the combination of the proposed converters can be used to reach a desired DC voltage through an input AC voltage. It can be considered depending on the area where the converter is used. Theoretical analysis is presented and simulation results confirm the correctness of the topology under different working conditions.Öğe Başlıksız(Springer, 2022) Tekin, Hakan; Bulut, Kübra; Ertekin, DavutHigh-voltage and efficient power converter topologies equipped with the simple and practical controller circuits are necessary, especially for integration between the low-power and low-voltage renewable energy sources (RESs) like the photovoltaic (PV) arrays and the grid. These converters can be used widely in electrical vehicles (EVs) or charging stations, aquatic, medical, transportation application and other cases. This study proposes a switched capacitor (SC)-based quadratic boost converter (QBC) structure that provides high-voltage gain at low duty cycles equipped with the fuzzy logic control (FLC) technique. The output gain of the proposed converter is higher than a second-order step-up converter or a conventional QB circuit thanks to the presented switched-capacitor topology and the manipulation of the switches in conventional QBC. By using the second switch to the conventional QBC, the voltage stress across the main power switch will decrease that enhance the reliability and long-life of the converter. Since the SC block acts as an intermediate layer between the QB and load through the capacitors and diodes of this block, the voltage and current stresses of the power switches and diodes on the QB side are less than stresses for semiconductors for classical QB and boost converter. In this study, the proposed QBC and controller system are analyzed mathematically in detail and in MATLAB/SIMULINK environment. A 200 W prototype was developed in the laboratory to validate the proposed converter and computerized analysis. Finally, the theoretical and experimental results were compared and verified.Öğe Başlıksız(Wiley, 2021) Ertekin, Davut; Bayrak, Gökay; Subramaniam, UmashankarIn Micro-grid applications, accuracy and sensitivity of the Demand Side Management (DSM) process decrease when the load impedance changes. In this study, the impact of the DSM is analyzed and the interleaved structure is presented for DC-DC converter blocks equipped with adaptive PI controllers. This approach reinforces a same voltage source that can be a serial and parallel connection of Photovoltaic (PV) panels in different power rates as the input voltage source to enhance the voltage to the micro-grid DC level and is modeling the power transmission in Renewable Energy Sources (RESs) that they produce limited amounts of power. For the voltage droop problem, the Power-Voltage (P-V) approach is selected. Since the resistive loads are considered in this study, this approach can control DC currents based and depending on the DC voltages in DC micro-grid applications. For per controller block, different values of the gain coefficients are tested and the optimal droop coefficients are presented. All simulations have been done in MATLAB/SIMULINK and a prototype by power around 1kW is tested. The results of the hardware implementation confirm the theoretical and simulation outcomes.Öğe Başlıksız(Elsevier, 2021) Yılmaz, Alper; Kucuker, Ahmet; Bayrak, Gökay; Ertekin, Davut; Shafie-Khah, Miadreza; Guerrero, Josep M.Artificial intelligence (AI) approaches are usually coupled with the wavelet transform (WT) for feature extraction to classify the power quality disturbances (PQDs). Therefore, selecting a useful WT-based signal processing approach is required for a reliable classification, especially in real-time applications. In this study, a new hybrid, un-decimated wavelet-transform (UWT)-based feature extraction method using a support vector machine (SVM) with a "' a trous" algorithm is proposed to classify PQDs in distributed generators (DGs). The proposed method was performed in a real-time application of a DG system to classify PQDs. The derived features were tested on five different machine learning (ML) models by determining the most appropriate classification technique for the proposed UWT-based feature extraction method. An experimental DG system is constituted in the laboratory using a LabVIEW environment, and the proposed method is tested under different grid conditions. Besides, other well-known and studied conventional ML methods were also tested under 25 dB, 30 dB, and 40 dB noise and compared to the developed method. The experimental and simulation results show that the features extracted with the proposed UWT-based method provide much more successful results in classification than the existing wavelet methods in the literature. Furthermore, the proposed method's noise sensitivity performance is much better than other conventional wavelet algorithms, especially in real-time applications.
