Prediction of the Derived Cetane Number and Carbon/Hydrogen Ratio from Infrared Spectroscopic Data

Emad Al Ibrahim,Aamir Farooq

doi:10.1021/acs.energyfuels.0c03899

Abstract

A model for the prediction of the derived cetane number (DCN) and carbon/hydrogen ratio (C/H) of hydrocarbon mixtures, diesel fuels, and diesel–gasoline blends has been developed on the basis of infrared (IR) spectroscopy data of pure components. IR spectra of 65 neat hydrocarbon species were used to generate spectra of 127 hydrocarbon blends by averaging the spectra of their pure components on a molar basis. The spectra of 44 real fuels were calculated using n-paraffin, isoparaffin, olefin, naphthene, aromatic, and oxygenate (PIONA-O) class averages of pure components. It is shown that this strategy retains knowledge of C/H, an important indicator of the chemical structure. Three methods were compared to assess the prediction of DCN and C/H ratio from the assembled IR spectra, i.e., partial least squares regression (PLSR), support vector machine (SVM), and artificial neural network (ANN). It was found that ANNs gave the best performance with DCN prediction errors of ±1.1 on average and C/H prediction errors of ∼0.8%. Lasso-regularized linear models were also used to find simple combinations of wavenumbers that yield acceptable estimations.

Highlights

There are a number of challenges that the transportation sector will have to face over the 3 decades as identified by the World Energy Council (WEC);[1] with the most prominent being urbanization, pressure to cut greenhouse gas emissions, need to limit pollution in megacities, congestion of the aging transport infrastructure, and increase in fuel demand
Performance of these models was compared by standard metrics: root-mean-square error (RMS), mean percentage error (MPE), mean absolute error (MAE), maximum error (MAX), and coefficient of determination (R2)
We extend the simulated IR spectra modeling methodology to carbon/hydrogen ratio (C/H) ratio and derived cetane number (DCN) prediction

Summary

Introduction

There are a number of challenges that the transportation sector will have to face over the 3 decades as identified by the World Energy Council (WEC);[1] with the most prominent being urbanization, pressure to cut greenhouse gas emissions, need to limit pollution in megacities, congestion of the aging transport infrastructure, and increase in fuel demand. While the rise of electrification in the transportation sector seems to tackle some of these challenges, it is expected to only penetrate the light-duty vehicle (LDV) market. Diesel engines in HDVs can reach up to 45% internal combustion engine (ICE) efficiency and have well-developed supporting infrastructure in most parts of the world, making it difficult for electrification through batterydriven trucks or electrified highways to compete.[3] Kalghatgi presents a more detailed discussion on the viability of electrifying HDVs and concludes that it will increase cost, decrease load capacity, and have a long charging time.[4]

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Conclusion