Kontrollü EGR Soğutma Sistem Tasarımının NOx ve BSFC Üzerine Etkisinin Uyarlamalı Sinirsel Bulanık Çıkarım Sistemi (ANFIS) İle Modellenmesi ve Optimizasyonu

Year 2020, , 2809 - 2821, 15.12.2020

Halil İbrahim Akolaş , Ali Rıza Kaleli

https://doi.org/10.21597/jist.740374

Abstract

Bu çalışma kapsamında dizel motorların egzoz gaz resirkülasyonu (EGR) sistemlerinde kullanılmak üzere egzoz gazlarını soğutan yenilikçi bir sistem tasarımı yapılmıştır. Tasarlanan sistemde 12 V elektrikli pompa ve fan kullanılmıştır. Bu elemanlar için ayrı ayrı PID (Oransal Integral Türev) kontrolcüler tasarlanmış ve kontrolcü parametreleri için optimizasyon yöntemi kullanılmıştır. Emme manifolduna giren gazların miktarı ve sıcaklığı için farklı çalışma koşullarında motor NOx ve fren özgül yakıt tüketimi (brake specific fuel consumption (BSFC)) üzerindeki etkileri analiz edilmiştir. Veriye dayalı yöntemler kullanılarak matematiksel model geliştirilmiştir. Elde edilen matematiksel model sayesinde tasarlanan kontrol sistemi için farklı motor çalışma koşullarında referans EGR akış miktarı ve sıcaklık değeri tanımlanmıştır. Uyarlamalı Sinirsel Bulanık Çıkarım Sistemi (Adaptive Neural Fuzzy Inference System (ANFIS)) ile tanımlanan modellerin gerçek verilerle uyumluluğu istatistiksel olarak analiz edilmiştir.

Keywords

Dizel motor, EGR sistemi, PID, ANFIS

Supporting Institution

Atatürk Üniversitesi Bilimsel Araştırma Projeleri Koordinasyon Birimi

Project Number

2015/362

Modeling and Optimization of the Effect of Controlled EGR Cooling System Design on NOx and BSFC with Adaptive Neural Fuzzy Inference System (ANFIS)

Abstract

In this study, an innovative system was designed to cool exhaust gases to be used in exhaust gas recirculation (EGR) systems of diesel engines. The designed system uses a 12 V electric pump and fan. PID (Proportional Integral Derivative) controllers are designed for these elements and optimization method is used for the controller parameters. For the amount and temperature of the gases entering the intake manifold, their effects on engine NOx and brake specific fuel consumption (BSFC) under different acclimation conditions were analyzed. A mathematical model was developed using data-based methods. The reference EGR flow rate and temperature value for different engine operating conditions have been defined for the control system designed thanks to the obtained mathematical model. The compatibility of models defined with Adaptive Neural Fuzzy Inference System (ANFIS) with real data was statistically analyzed.

Keywords

PID, ANFIS, Diesel engine, EGR system

Project Number

2015/362

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