Combustion and emission behavior of N-propanol as partially alternative fuel in a direct injection spark ignition engine

Guo, Jinjing; Zhang, Yahui; Tao, Wei; Lü, Xingcai

doi:10.1016/j.applthermaleng.2018.08.044

Cited by 33 publications

(12 citation statements)

References 35 publications

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“…While alternative fuels are used in a special way in systems that burn a single fuel, gasoline, which is used as current fuel, can be used as a mixture with other fuels, including LPG or diesel. Oxygen content of gasoline fuel can be increased by using 1-Propanol in order to provide better combustion and lower emission values [1], [2]. 1-Propanol contains three carbons in its structure and is defined by the formula 𝐶𝐻3𝐻7𝑂𝐻 [2], [3].…”

Section: Introductionmentioning

confidence: 99%

Using Machine Learning Methods to Predict the Effect of Alternative Fuel Mixtures on Exhaust Emissions

BİLBAN¹,

Aydoğan²

2022

European Journal of Science and Technology

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Machine learning is a science that deals with the design and development processes of algorithms that enable data-based learning. Machine learning methods try to find the most suitable model for new data prediction processes by using the past data. In this study, the data obtained from the engine trials with fuel mixtures of 5%, 10%, 15% by volume using 1-Propanol, 2-Propanol, AVGAS and gasoline fuel were used. Obtained data were compared with 100% gasoline values. In the study, a 4-cylinder engine with direct injection and turbocharging was used. With the obtained measurement results, a database was created to be used in machine learning. With the created database, estimation processes were carried out on ANN, GBA, SVM and AB machine learning models. At the end of the study, it was found that the most suitable model for the estimation of CO, CO2, HC, O2 values was ANN with an R 2 value of 0.9999. For the NO value, it was determined that the AB method was used with an R 2 value of 0.9996. In the estimation process of the CO value, GBA and AB methods are other machine learning methods that can be used as they have a higher value than 0.99 R 2 . CO2, HC and O2, and in the output value estimation process, GBA and AB are other methods that can be used instead of ANN as they have a higher value than 0.99 R 2 . It has been found that there is another machine learning method that can be used for NO value estimation, with an AB 0.99 R 2 value.

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Section: Introductionmentioning

confidence: 99%

Using Machine Learning Methods to Predict the Effect of Alternative Fuel Mixtures on Exhaust Emissions

BİLBAN¹,

Aydoğan²

2022

European Journal of Science and Technology

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“…Alcohols burn with a higher flame rate than gasoline and do not contain elements such as sulfur and phosphorus. All these factors are a great advantage for alcohols (Liu et al, 2020;Qian et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Effect of 1-Propanol/Gasoline Fuel Blends on Engine Performance of Engine with Direct Injection

Gökmen¹,

Aydoğan²

2022

bes

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In this study, the effect of 1-Propanol / Gasoline fuel mixtures on engine performance values has been experimentally investigated. 1-Propanol is a primary alcohol with the formula CH3CH2CH2OH and sometimes represented as PrOH or n-PrOH. It is a colorless liquid and an isomer of 2-propanol. It is formed naturally in small amounts during many fermentation processes and used as a solvent in the pharmaceutical industry, mainly for resins and cellulose esters, and, sometimes, as a disinfecting agent. In this study, 1-Propanol and gasoline were mixed in certain proportions and TSI was applied in a gasoline engine. The changes in the performance of 1-Propanol-gasoline fuel blends used in Direct Injection Engine were investigated in this experimental study. P5 (5% 1-Propanol, 95% gasoline fuel by volume), P10 and gasoline fuel were used as fuel. The tests were performed at full-throttle valve opening and variable engine speeds. At 2500 rpm and below the P5 blends caused a reduction in engine power by 1.68% and engine torque by 3.15%, but reduced BSFC by 11.39%. The P10 blend reduced the BSFC by 14.57%, although it caused a 2.41% reduction in engine power and a 5.71% reduction in engine torque.

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“…Benzin yakıtının oksijen içeriği daha iyi bir yanma ve daha düşük emisyon değerleri sağlaması amacı ile 1-Propanol kullanılarak artırılabilmektedir (Qian et al, 2018). 1-Propanol yapısında üç adet karbon bulundurur ve 3 7 formülü ile tanımlanmaktadır (Gawale & Naga Srinivasulu, 2020).…”

Section: Introductionunclassified

Yanıt Yüzey Metodolojisi Kullanılarak 1-Propanol/Benzin Yakıt Karışımlarının Egzoz Emisyonlarına Etkisinin Araştırılması

Gökmen¹,

Doğan²,

Aydoğan³

2021

European Journal of Science and Technology

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Bu çalışmada, 1-Propanolün benzin ile karıştırılması ile elde edilen yakıt karışımlarının egzoz emisyon değerlerine etkisi yanıt yüzey metodolojisi ile deneysel olarak incelenmiştir. Yanıt Yüzey Metodolojisi (YYM) için giriş faktörleri 1-Propanol oranı ile Motor devri ve yanıt değerleri ise karbonmonoksit (CO), karbon dioksit (CO2), hidrokarbon (HC), Azot Oksit (NO) ve Oksijen (O2) emisyonları olarak belirlenmiştir. Oluşturulan YYM tasarımında 3 Seviye Faktöriyel Tasarım (3SFT) tekniği kullanılarak deneyler planlanmıştır. Deney planları sonucunda motor devri 1500, 2500 ve 3500 d/dk ayrıca 1-propanol oranı ise %5, %10 ve %15 (% hacim) olarak belirlenerek 3 farklı karışım ve %100 Benzin için toplam 12 farklı ölçüm gerçekleştirilmiş ve sonuçlar istatistiksel olarak değerlendirilmiştir. Elde edilen sonuçlara göre CO, CO2, HC, O2 ve NO emisyonları için optimum değerleri sırasıyla %98.58, %98.88, %99.03, %99.33 ve %98.51 doğrulukta % 0.292, %7.07, 45.55 ppm, %7.49 ve 1298.42 ppm olarak tahmin edilmiştir. Sonuçların istatistiksel olarak önemli olması, YYM kullanılarak benzin karışımlarının emisyon değerleri üzerindeki etkilerinin daha az test sayısı ile verimli bir şekilde incelenebildiğini göstermektedir. Çalışma sonuçlarına göre 1-Propanol karışımları tüm devirlerde CO2, HC, O2, NO emisyonlarını azaltmıştır fakat CO emisyonu için en düşük değerler %100 benzin ile yapılan testlerde elde edilmiştir.

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Combustion and emission behavior of N-propanol as partially alternative fuel in a direct injection spark ignition engine

Cited by 33 publications

References 35 publications

Using Machine Learning Methods to Predict the Effect of Alternative Fuel Mixtures on Exhaust Emissions

Using Machine Learning Methods to Predict the Effect of Alternative Fuel Mixtures on Exhaust Emissions

Effect of 1-Propanol/Gasoline Fuel Blends on Engine Performance of Engine with Direct Injection

Yanıt Yüzey Metodolojisi Kullanılarak 1-Propanol/Benzin Yakıt Karışımlarının Egzoz Emisyonlarına Etkisinin Araştırılması

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