Novel Functional Group Contribution Method for Surrogate Formulation with Accurate Fuel Compositions

Current surrogate formulation methods usually adopt distillation profiles, density, viscosity, surface tension, molecular weight, research/motor octane number (RON/MON), cetane number (CN), heating value, H/C ratio, and threshold sooting index (TSI) as target properties, but these parameters are most likely unavailable for new fuel molecules and mixtures at the early stage of fuel development. A novel functional group contribution method (GCM) based on accurate fuel compositions is proposed to formulate surrogates effectively and quickly. This method can successfully replicate the density, sound speed, kinematic viscosity, ignition delay times, and speciations of POSF 4658, rapeseed methyl ester, diesel, and fuels for advanced combustion engines (FACE) C gasoline under a broad range of conditions (φ = 0.37–2.0, Tinit = 500–1600 K, Pinit = 1–20 atm), and its predictive capacity is superior to that of traditional methods in most cases. Fuel properties would match automatically between a surrogate and target fuel if the discrepancies of functional groups are minimized. Three important factors contribute to its high reproducibility: first, GCM captures the complicated dependence of fuel physical/chemical properties on the fuel molecular structure and functional groups; second, it correctly assumes that fuel physical and chemical properties are a sum result of the fuel molecular structure and functional groups; third, the functional group interactions and their effect on fuel reactivity are considered in the functional group classification system. The GCM can not only formulate in the normal direction from a complex target fuel to a simple surrogate fuel but also enable starting from a simple target fuel toward a complex surrogate fuel during fuel design in the refinery industry.

当前的替代燃料配制方法通常以蒸馏曲线、密度、粘度、表面张力、分子量、研究法/马达法辛烷值（RON/MON）、十六烷值（CN）、热值、氢碳比以及碳烟阈值指数（threshold sooting index, TSI）作为目标物性，但在燃料开发初期，新型燃料分子及混合物的这类参数大多难以获取。本文提出一种基于精准燃料组分的新型官能团贡献法（functional group contribution method, GCM），可高效快速地完成替代燃料配制。该方法能够在宽泛的工况范围（当量比φ=0.37~2.0、初始温度Tinit=500~1600 K、初始压力Pinit=1~20 atm）下，精准复现POSF 4658、油菜籽甲酯、柴油以及先进燃烧发动机用燃料（FACE）C级汽油的密度、声速、运动粘度、点火延迟时间与物种分布；且在多数工况下，其预测性能优于传统方法。若将官能团差异降至最低，替代燃料与目标燃料的物性可实现自动匹配。该方法具备高重现性源于三大关键因素：其一，官能团贡献法捕捉了燃料物理/化学性质对燃料分子结构与官能团的复杂依赖关系；其二，该方法合理假设燃料物理与化学性质为燃料分子结构与官能团的总和效应；其三，官能团分类体系中考虑了官能团间的相互作用及其对燃料反应活性的影响。官能团贡献法不仅可从复杂目标燃料正向配制至简单替代燃料，还能在炼油工业的燃料设计环节中，从简单目标燃料出发合成复杂替代燃料。