Bilgisayar Sistemlerinde SEPIC Dönüştürücü Uygulaması ve Benzetim Çalışması

Karaarslan, Ahmet

doi:10.17671/gazibtd.540127

Cited by 2 publications

(1 citation statement)

References 6 publications

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“…SEPIC regulates the output voltage by switching the MOSFET on and off at constant frequency. For a SEPIC converter operating in a continuous conduction mode (CCM), the duty cycle is given by following formula if the voltage drop of the diode 𝑉 𝐷 is assumed to be 0 V [19].…”

Section: Power Stagementioning

confidence: 99%

Güç Faktörü Ve Flickeri Di̇kkate Alan Bi̇r Tepe Akim Modu Kontrollü Sepi̇c Led Sürücü Tasarimi

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YILDIRIM

2022

Eskişehir Technical University Journal of Science and Technology a - Applied Sciences and Engineering

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In this paper, a peak current mode controlled single ended primary inductor converter (SEPIC) LED driver is proposed to control the brightness of the LED. One string of 37 series connected LEDs is adopted as output of the circuit. The proposed control strategy is based on measuring MOSFET peak current value using a shunt resistor. When this voltage reaches peak threshold value, controller turns off MOSFET. The output current is adjusted to desired levels by changing this peak threshold value. The power factor in the AC power supply side is low because of the full wave bridge rectifier with capacitor filter at the input of the converter. The proposed control strategy is applied with power factor correction (PFC) circuit where input voltage is multiplied by control voltage to achieve high power factor. In PFC circuit, although the line current waveform is slightly distorted due to voltage limitations in integrated circuit (IC) chip used for the proposed control strategy, power factor is kept above 0.9 for operation region between 100mA-300mA. In addition, flicker on LED string is measured for operating current region and flicker limits are revealed. Adjustable output current levels, low flicker on LED string, MOSFET peak current control at each cycle, fast output dynamics, and high power factor are acquired by the proposed control strategy.

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Section: Power Stagementioning

confidence: 99%

Güç Faktörü Ve Flickeri Di̇kkate Alan Bi̇r Tepe Akim Modu Kontrollü Sepi̇c Led Sürücü Tasarimi

ÖRÜKLÜ

YILDIRIM

2022

Eskişehir Technical University Journal of Science and Technology a - Applied Sciences and Engineering

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Edge ai technology in the defense industry via reinforcement learning in simulation environments

Mendı¹

2023

Gümüşhane Üniversitesi Fen Bilimleri Enstitüsü Dergisi

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Edge artificial intelligence (Edge AI) technology helps to avoid vulnerabilities while benefiting from the advantages of cloud technologies, which are widely used today, especially with artificial intelligence and big data. In the case of transferring systems to the cloud, and needs such as protection of sensitive information and high bandwidth emerges in cloud approaches. Edge AI, which provides solutions to issues such as the security of sensitive data and reducing system traffic, while meeting the needs in this field, can offer a new perspective, especially to projects in the military field, when used with digital twin and autonomous system technologies. In this study, we evaluated the “Forces in virtual environment machine learning (FIVE-ML)” simulation system technically in which we use edge AI technology, analyzed the results obtained with the use of this technology. It has been determined that the current work is at the 2nd level in Edge AI levelling system, also there is a 54% performance (in terms of time with accuracy) increase with edge AI. Besides, the accuracy of hitting the target in simulation system is also increased, with the rate of 34%.

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Bilgisayar Sistemlerinde SEPIC Dönüştürücü Uygulaması ve Benzetim Çalışması

Cited by 2 publications

References 6 publications

Güç Faktörü Ve Flickeri Di̇kkate Alan Bi̇r Tepe Akim Modu Kontrollü Sepi̇c Led Sürücü Tasarimi

Güç Faktörü Ve Flickeri Di̇kkate Alan Bi̇r Tepe Akim Modu Kontrollü Sepi̇c Led Sürücü Tasarimi

Edge ai technology in the defense industry via reinforcement learning in simulation environments

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