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Title: Predicting the concentration and specific gravity of biodiesel-diesel blends using near-infrared spectroscopy

Author
item CORONADO, MARCELO - Kansas State University
item YUAN, WENQIAN - Kansas State University
item WANG, DONGHAI - Kansas State University
item Dowell, Floyd

Submitted to: Applied Engineering in Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/1/2008
Publication Date: 3/1/2009
Citation: Coronado, M., Yuan, W., Wang, D., Dowell, F.E. 2009. Predicting the concentration and specific gravity of biodiesel-diesel blends using near-infrared spectroscopy. Applied Engineering in Agriculture. 25(2): 217-221.

Interpretive Summary: Biodiesel made from different source materials can have different physical and chemical properties. Also, the concentration of biodiesel in biodiesel-diesel blends varies from pump to pump and from user to user. These factors can significantly affect the performance and efficiency of engines fueled with biodiesel. To address these challenges, models based on near-infrared spectroscopy were developed for relatively inexpensive and rapid on-line measurement of the concentration and specific gravity of biodiesel-diesel blends. Five different oils—soybean oil, canola oil, palm oil, waste cooking oil, and coconut oil—and two different brands of commercial-grade No. 2 on-highway diesel and one brand of off-road No. 2 diesel were used in the calibration and validation processes. The predicted concentration and specific gravity of the biodiesel-diesel blends were compared with the actual values. The average prediction error of biodiesel concentrations was about 3%. The specific gravity prediction model had an average error of 0.002. This information is necessary to develop engine electronic control units to adjust fuel injection timing for optimum engine performance.

Technical Abstract: Biodiesel made from different source materials usually have different physical and chemical properties and the concentration of biodiesel in biodiesel-diesel blends varies from pump to pump and from user to user; all these factors have significant effects on performance and efficiency of engines fueled with biodiesel. To address these challenges, models based on near-infrared spectroscopy were developed for relatively inexpensive and rapid on-line measurement of the concentration and specific gravity of biodiesel-diesel blends. Methyl esters of five different oils—soybean oil, canola oil, palm oil, waste cooking oil, and coconut oil—and two different brands of commercial-grade No. 2 on-highway diesel and one brand of off-road No. 2 diesel were used in the calibration and validation processes. The predicted concentration and specific gravity of the biodiesel-diesel blends were compared with the actual values. The maximum and average prediction errors of biodiesel concentration were 5.2% and 2.9%, respectively, from the biodiesel type-specific model. For the general model, the maximum and average prediction errors were 7.5% and 2.6%, respectively. The specific gravity prediction model had a maximum prediction error of 0.005 and an average error of 0.002.