Fuels properties, characterizations and engine and emission performance analyses of ternary waste cooking oil biodiesel-diesel-propanol blends
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Date
2019
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SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
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Abstract
Application of biodiesel synthesized from waste-based raw materials with numerous solvents (higher chain alcohols) in diesel engines is a topic of great interest. This article examines the effect of biodiesel-diesel-propanol ternary blends. Physio-chemical properties, fatty acids composition (FAC), FT-IR, TGA, DSC, NMR along with some selected engine and emissions performance parameters were examined. Biodiesel was produced from waste cooking oil and exhibits excellent FAC that yields kinematic viscosity, cetane number, oxidation stability, higher heating value and iodine value of 3.93mm(2)/s, 58.88, 7.43 h, 39.45 MJ/kg and 64.92 g/100 g. Propanol blended biodiesel depicted an affirmative improvement in cold flow properties and decremented density. FT-IR and NMR results confirms the existence of biodiesel-diesel-propanol and prove their qualities as reliable methods. DSC and TGA results confirm that propanol reduces the onset and crystallization temperatures of the blends. Engine and emissions performance revealed that propanol addition further increased brake specific energy consumption (BSEC) and brake specific fuel consumption (BSFC) and reduced carbon monoxide (CO), exhaust gas temperature (EGT), nitrogen oxides (NOx) and smoke. This study proves the feasibility of the ternary blends with rewarding benefits in cold flow properties and densities besides acceptable engine and emissions performance results.
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Waste cooking oilBiodiesel-propanol-diesel blendsFT-IRNMREngine and emissions analyses
Turkish CoHE Thesis Center URL
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Bencheikh, K., Atabani, A. E., Shobana, S., Mohammed, M. N., Uğuz, G., Arpa, O., Kumar, G., Ayanoğlu, A., & Bokhari, A. (2019). Fuels properties, characterizations and engine and emission performance analyses of ternary waste cooking oil biodiesel–diesel–propanol blends. Sustainable Energy Technologies and Assessments, 35, 321–334. https://doi.org/10.1016/j.seta.2019.08.007
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35
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