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Prediction of performance and exhaust emissions of a CI engine fueled with multi-wall carbon nanotube doped biodiesel-diesel blends using response surface method

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  • Solmaz, Hamit
  • Ardebili, Seyed Mohammad Safieddin
  • Calam, Alper
  • Yılmaz, Emre
  • İpci, Duygu

Abstract

This study was designed to analyses the performance and exhaust emissions of a direct-injection diesel engine fueled with multi-walled carbon nanotubes (MWCNTs) included in biodiesel-blended diesel fuel using response surface method (RSM). The influence of input parameters —engine load and MWCNTs concentration — on the response parameters (i.e., BSFC, BTE, CO, NOX, and UHC) were investigated and predicted. MWCNTs were added into B20 fuel (20% biodisesel+80% diesel) in various concentrations (25, 50, 75, and 100 ppm). The tests performed under varying engine load conditions (5, 10, 15, and 20 Nm) at a constant engine speed of 1800 rpm. Multi-regression models for BTE, BSFC, and CO, UHC, and NOX emissions were derived using RSM and were found to be statistically significant. Exhaust UHC and CO concentrations for the studied fuel blend decreases with the addition of MWCNTs into B20 fuel, while NOx emissions drastically increased. The optimal engine working conditions were found to be an engine load of 10 Nm and MWCNTs concentration of 98 ppm. Based on the optimized values, the most optimal results for BTE and BSFC along with CO, UHC, and NOX emissions were found to be 28.57 (%), 269.84 (g/kWh), 0.03 (%Vol.), 44.16 (ppm), and 458.81 (ppm).

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  • Solmaz, Hamit & Ardebili, Seyed Mohammad Safieddin & Calam, Alper & Yılmaz, Emre & İpci, Duygu, 2021. "Prediction of performance and exhaust emissions of a CI engine fueled with multi-wall carbon nanotube doped biodiesel-diesel blends using response surface method," Energy, Elsevier, vol. 227(C).
    • Handle: RePEc:eee:energy:v:227:y:2021:i:c:s0360544221007672
    DOI: 10.1016/j.energy.2021.120518
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    Cited by:

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    2. Kocakulak, Tolga & Babagiray, Mustafa & Nacak, Çağatay & Safieddin Ardebili, Seyed Mohammad & Calam, Alper & Solmaz, Hamit, 2022. "Multi objective optimization of HCCI combustion fuelled with fusel oil and n-heptane blends," Renewable Energy, Elsevier, vol. 182(C), pages 827-841.
    3. Ardebili, Seyed Mohammad Safieddin & Kocakulak, Tolga & Aytav, Emre & Calam, Alper, 2022. "Investigation of the effect of JP-8 fuel and biodiesel fuel mixture on engine performance and emissions by experimental and statistical methods," Energy, Elsevier, vol. 254(PA).
    4. Emmanuelle Soares de Carvalho Freitas & Lílian Lefol Nani Guarieiro & Marcus Vinícius Ivo da Silva & Keize Katiane dos Santos Amparo & Bruna Aparecida Souza Machado & Egidio Teixeira de Almeida Guerre, 2022. "Emission and Performance Evaluation of a Diesel Engine Using Addition of Ethanol to Diesel/Biodiesel Fuel Blend," Energies, MDPI, vol. 15(9), pages 1-12, April.
    5. Haibo Wu & Xingwang Tang & Sichuan Xu & Jiangbin Zhou, 2022. "Research on Energy Saving of PHEV Air Conditioning System Based on Reducing Air Backflow in Underhood," Energies, MDPI, vol. 15(9), pages 1-15, April.
    6. Yakın, Ahmet & Behcet, Rasim & Solmaz, Hamit & Halis, Serdar, 2022. "Testing sodium borohydride as a fuel additive in internal combustion gasoline engine," Energy, Elsevier, vol. 254(PB).
    7. Ma, Shuaifei & Guo, Qi & Wei, Jiangjun & Yin, Zenghui & Zhuang, Yuan & Zhang, Yu & Dai, Qian & Qian, Yejian, 2024. "Analyzing the effect of carbon nanoparticles on the combustion performance and emissions of a DI diesel engine fueled with the diesel-methanol blend," Energy, Elsevier, vol. 300(C).

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