Density Prediction Model of Binary or Ternary Diesel Fuel Blends with Biodiesel and Ethanol for Compression-Ignition Engine Calculations.

Density is an important indicator for evaluating diesel fuel quality that directly affects the injection timing and injection rule of the engine, and also has a significant impact on the spray broken particle size, the spray penetration distance, the spray cone angle, and so forth, which in turn affects the combustion process and pollutant emission of the compression-ignition engine. Therefore, it is important to accurately predict the diesel fuel mixture density in industrial and compression-ignition engines. However, the mathematical models for predicting the density of diesel fuel mixture with changed temperature are relatively lacking and less accurate, especially for ternary diesel fuel mixtures with different physicochemical properties. This paper proposes a mathematical model including binary and ternary diesel mixtures under changed fuel volume fraction and temperature, and published data were used for verification. The data verification results show that: for the density prediction of binary diesel fuel mixtures at constant temperature, the average relative deviation (ARD) is 0.0245%, the RMS error (RMSE) is 0.000344, and the correlation coefficient (R) is 0.9993. For the density prediction of binary diesel fuel mixtures at changed temperature, the ARD is 0.0609%, the RMSE is 0.000695, and R is 0.9980. For the density prediction of ternary diesel fuel mixtures at constant temperature, the ARD is lower than 0.0571%, the RMSE is lower than 0.000610, and R is higher than 0.9861. For the density prediction of ternary diesel fuel mixtures at changed temperature, the ARD is 0.0484%, the RMSE is 0.000513, and R is 0.9996. The diesel mixed fuel density prediction model proposed in this paper has good accuracy and calculation convenience, and provides important reference value for measuring or designing the density of diesel mixed fuel in the field of compression-ignition engines. [ABSTRACT FROM AUTHOR]