The combustion of n-butanol/diesel fuel blends and its cyclic variability in a direct injection diesel engine

被引:82
|
作者
Rakopoulos, C. D. [1 ]
Rakopoulos, D. C. [1 ]
Giakoumis, E. G. [1 ]
Kyritsis, D. C. [2 ]
机构
[1] Natl Tech Univ Athens, Sch Mech Engn, Dept Thermal Engn, Internal Combust Engines Lab, Athens 15780, Greece
[2] Univ Illinois, Dept Mech Sci & Engn, Urbana, IL 61801 USA
关键词
diesel engine; combustion; n-butanol blends; heat release; stochastic analysis; cyclic (combustion) variability; ETHANOL-DIESEL; BIO-DIESEL; CRUDE GLYCEROL; VEGETABLE-OILS; EMISSIONS; PERFORMANCE; OPERATION; BIOFUELS;
D O I
10.1177/2041296710394256
中图分类号
O414.1 [热力学];
学科分类号
摘要
An experimental study is conducted to evaluate the effects of using blends of diesel fuel with n-butanol (normal butanol) up to 24 per cent (by volume), which is a promising fuel that can be produced from biomass (bio-butanol), on the combustion behaviour of a standard, high-speed, direct injection (DI), 'Hydra' diesel engine located at the authors' laboratory. Combustion chamber and fuel injection pressure diagrams are obtained at four different loads using a developed, high-speed, data acquisition, and processing system. A heat release analysis of the experimentally obtained cylinder pressure diagrams is developed and used. Plots of histories in the combustion chamber of the gross heat release rate and other related parameters reveal some interesting features, which shed light on the combustion mechanism when using these blends. These results, combined with the differing physical and chemical properties of the n-butanol against those for the diesel fuel, aid the correct interpretation of the observed engine behaviour performance based on and emissions. Moreover, given the concern for the rather low cetane number of the n-butanol that may promote cyclic (combustion) variability, its strength is also examined as reflected in the pressure indicator diagrams, by analysing for the maximum pressure and its rate, dynamic injection timing and ignition delay, by using stochastic analysis for averages, standard deviations, probability density functions, autocorrelation, power spectra, and cross-correlation coefficients.
引用
收藏
页码:289 / 308
页数:20
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