Optimizing cetane improver concentration in biodiesel-diesel blend via grey wolf optimizer algorithm

Ileri E., KARAOĞLAN A. D., AKPINAR Ş.

FUEL, cilt.273, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 273
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1016/j.fuel.2020.117784
  • Dergi Adı: FUEL
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Agricultural & Environmental Science Database, Biotechnology Research Abstracts, Chimica, Communication Abstracts, Compendex, INSPEC, Metadex, Pollution Abstracts, Civil Engineering Abstracts
  • Anahtar Kelimeler: Biodiesel, Fuel additive, Diesel engine, Regression, Grey wolf optimizer, 2-ETHYLHEXYL NITRATE, ENGINE PERFORMANCE, EXHAUST EMISSIONS, N-BUTANOL, NOX EMISSIONS, FUEL, COMBUSTION, CONSUMPTION, PARAMETERS, HAZELNUT
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

Biodiesel and their blends with diesel have long been used as alternative fuels in diesel engines. In particular, B20 is recommended in most studies since it reduces the exhaust emissions and provides satisfactory engine torque close to diesel fuel. On the other hand, low cetane number of biodiesel leads to higher oxides of nitrogene (NOx) emission when compared to those of the diesel fuel. Formation of NOx emissions has a strong correlation with cetane number of fuels, which increases with the reduction of the cetane number. The current paper focuses on finding the optimum 2-ethylhexyl nitrate (EHN) (cetane improver) concentration and the engine speed for 20 vol% canola oil methyl ester and 80 vol% diesel fuel blend (B20). For that reason, experimental design is created and the experiments have been done on TDI diesel engine at full load and different engine speed conditions to be able to model the problem as an optimization problem by means of the regression modelling. Accordingly, the developed model in consequence of the test results of the engine is optimized via the grey wolf optimizer (GWO) algorithm taking into account of engine performance and emission parameters viz. brake torque, brake power, brake specific fuel consumption (BSFC), brake thermal efficiency (BTE), NOx, and carbon dioxide (CO2), to identify the rate of concentration of EHN in B20 and engine speed. Finally, confirmation tests were employed to compare the output values of the concentration that were identified through the GWO algorithm, and further statistical analyses indicate the consistency between the real experimental results and the results obtained through the GWO algorithm. The optimum EHN concentration and engine speed was determined as 743 mg/L and 3221 rpm respectively. Test results of engine performance indicated that brake power and BSFC of optimum blend at 3221 rpm decreased while brake torque and BTE increased in comparison with those of B20 without EHN. CO2 and NOx exhaust emissions decreased as 11.19% and 4.63% respectively.