Yazar "Toprak, Muhammed Zeyd" seçeneğine göre listele

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    Design and implementation of a new dual-layer type 2 FLC-based energy management system for a fuel cell electric vehicle
    (Elsevier Ltd, 2026) Yılmaz, Alper; Toprak, Muhammed Zeyd; Bayrak, Gökay
    This study presents a new dual-layer energy management strategy (EMS) based on Interval Type-2 Fuzzy Logic Control (IT2 FLC) for a 1 kW PEMFC–ultracapacitor (UC) hybrid fuel cell electric vehicle. The proposed strategy enhances power distribution stability and fuel cell lifespan by leveraging the fast dynamic response of UC to mitigate the slow transient behavior of PEMFCs. A custom-designed full-bridge push-pull converter is developed to regulate power flow between energy sources, ensuring a stable 96V DC output despite variations in input voltage. Experimental validation on a real-scale prototype confirms robust voltage regulation within ±1 V and effective UC participation during transients, with instantaneous support up to 1000 W, thereby reducing fuel cell stress. Under scaled FTP-75 and WLTP Class-1 cycles, the IT2FLC consistently outperforms PID and Type-1 FLC, improving tracking by >80 % versus PID while limiting MAE and RMSE to <0.02 m/s and <0.03 m/s, respectively, with negligible overshoot. © 2026 Hydrogen Energy Publications LLC
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    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 Zeyd
    Hydrogen 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.
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    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, Pierluigi
    The 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.