建立了拉曼光谱法结合偏最小二乘法（PLS）测定柴油十六烷值的方法。采集124个含有不同十六烷值柴油样品的拉曼光谱图，通过对校正集和预测集数量、光谱预处理方法、主因子数及光谱范围进行优化，建立了PLS模型。优化后的建模条件为：校正集和预测集的数量分别为103和21，采用卷积平滑和标准正态变量变换对光谱进行预处理，选择主因子数为7，对700~1 700 cm^-1和2 700~3 100 cm^-1两个光谱范围同时进行建模。结果显示：PLS模型的校正均方根误差为0.913，校正相关系数为0.954 3，预测均方根误差为0.911，预测相关系数为0.924 6。利用该模型对柴油进行分析，所得结果与标准发动机法测定结果相符，绝对误差为-2.9~2.9。

A method for the determination of cetane value of diesel oil by Raman spectroscopy combined with partial least square (PLS) was established. 124 Raman spectra of diesel oil samples with different cetane values were collected. The amount of calibration set and prediction set, the spectral pretreatment method, the number of principal factor and the spectral region were optimized to accomplish PLS model. The optimized modeling conditions were as follows. The quantity of calibration set and prediction set was 103 and 21, respectively. The spectra was preprocessed by smoothing convolution and standard normal variable change.The number of principal factor was 7. The spectral regions were 700-1 700 cm^-1 and 2 700-3 100 cm^-1. The results showed that the root mean square error of correction of the PLS model was 0.913, the correlation coefficient was 0.954 3, the root mean square error of prediction of model was 0.911 and the prediction coefficient was 0.924 6. This model was used to analyze diesel oil, and the results of PLS model were consistent with the results of standard engine method, with absolute error in the range of -2.9-2.9.