【摘要】 以柴油为例，结合遗传优化算法研究了其有限组分模型燃料构建时权重值对目标参数计算值的影响，分析了各目标参数间的关联性，并从模型燃料构成组分的角度探讨了这些影响和关联性的机制，研究同时关注了候选组分数量改变所造成的影响。结果表明，改变权重值时，十六烷值、低热值和烟阈指数计算值变化微弱；而H、C物质的量的比和相对分子质量受权重的影响较大，且低权重时受到权重的影响更高。模型燃料候选组分数量为19时，目标参数之间的关联性与密度、黏度和烟阈指数密切相关，当模型燃料候选组分数量为4时，这一关联性的核心目标参数是黏度、烟阈指数和表面张力。候选组分为19时，受密度和相对分子质量影响组分含量的个数最多，而候选组分为4时，影响组分含量个数最多的是表面张力和相对分子质量。更多还原

【Abstract】 Taking diesel as an example, the influences of weight values on the calculated values of target parameters were investigated by means of the genetic optimization algorithm for the construction of its finite-component surrogate fuel. The correlations among various target parameters were analyzed, and the mechanism behind such influences and correlations was explored from the perspective of surrogate fuel composition. The effects caused by changes in the number of candidate components were also examined. The result shows that when adjusting weight values, the calculated values of cetane number,lower heating value and soot threshold index change slightly. The amount of substance ratio of H and C and molecular weight are influenced by the weight greatly, and the influence of the weight is higher at the lower weight. When the number of surrogate fuel candidate components is 19, the correlation among target parameters is closely related to density, viscosity and soot threshold index. However,when the number of surrogate fuel candidate components is 4, the key target parameters for correlation are viscosity, soot threshold index and surface tension. For the 19-candidate component surrogate fuel, the number of component concentrations affected by density and molecular weight is the largest. For the 4-candidate component surrogate fuel, surface tension and molecular weight have the greatest impact on the number of component concentrations affected.更多还原