Near-Infrared Spectroscopy as a Tool for Simultaneous Determination of Diesel Fuel Improvers

Abstract

Diesel and biodiesel blends requires additives to improve fuel quality properties and engine performance. Diesel improvers are added before, during and/or after the fuel is blended. However, no accurate rapid and non-destructive analytical method is used during the fuel production that could determine the exact concentration of various types of improvers in diesel fuel. Thus, the aim of this study was to determine the concentration of several improvers in diesel matrices at the same time. Three types of diesel improvers, i.e., a cold-flow improver (CFI), a conductivity−lubricity improver (CLI), and a cetane number improver (CNI), were simultaneously determined by near-infrared (NIR) spectroscopy combined with multivariate statistical analysis and the partial least squares algorithm. The prediction models yielded high correlation coefficients (R2) >0.99 and satisfactory values of the root mean square error of calibration as follows: CLI 4.2 (mg·kg−1), CFI 4.6 (mg·kg−1), and CNI 5.3 (mg·kg−1). The residual standard deviation of the repeatability was calculated to be around 8%. These results highlight the potential of NIR spectroscopy for use as a fast, low-cost, and efficient tool to determine the concentrations of diesel improvers. Moreover, this technique is suitable for application during refinery production, especially for the purpose of online monitoring to prevent overdoses of additives and save financial expenses.