To assess the knocking properties of natural gas (NG) when it is used as fuel for vehicles is vital to optimize the design and functioning of their motors. Analytical efforts in this field are needed as the engines used to define it empirically are not available anymore, and existent mathematical algorithms yield different accuracy. The hybridization of gas-phase infrared spectrometry and partial least squares multivariate regression is presented first time to address the determination of the methane number (MN) of NG samples. It circumvents the need for the previous knowledge of the NG composition required to apply dedicated equations. The use of true NG samples to develop the models is also quite new in the field. Proof-of-concept studies were made with synthetic spectra and, then, a collection of liquefied NG samples for which MN values were computed by the National Physics Laboratory algorithm (NPL) from their sample composition were used to develop operative models. Additional validation was made with a collection of synthetic standard mixtures prepared for two European projects (EMRP LNG II and EMPIR LNG III) whose service methane numbers (SMN) were measured with an engine. The FTIR-PLS approach yielded statistically unbiased predictions with average standard errors around 0.4% MN when compared to the NPL-MN and SMN values, and standard deviations of the means ca. 1% MN. The approach is fast, cost effective as it involves standard instrumentation, and can be considered compliant with the green chemistry principles.

评估天然气（NG）用作车辆燃料时的爆震性能对于优化其电机的设计和功能至关重要。由于用于凭经验定义它的引擎不再可用，因此需要在该领域进行分析，并且现有的数学算法会产生不同的准确性。首次提出了气相红外光谱法和偏最小二乘多元回归的杂交方法，以解决NG样品甲烷值（MN）的确定问题。它避免了需要应用专用方程式的天然气成分的先前知识。使用真正的NG样本开发模型在该领域中也是相当新的。用合成光谱进行概念验证研究，然后，收集了一系列液化的NG样品，这些样品通过国家物理实验室算法（NPL）根据其样品组成计算了MN值，用于开发操作模型。为两个欧洲项目（EMRP LNG II和EMPIR LNG III）准备的合成标准混合物的集合进行了进一步的验证，其使用发动机测量了使用甲烷数（SMN）。与NPL-MN和SMN值相比，FTIR-PLS方法得出的统计无偏预测的平均标准误差为MN约0.4％，均值的标准偏差为ca。MN为1％。该方法快速，经济高效，因为它涉及标准仪器，并且可以认为符合绿色化学原理。