Abstract
The autoignition temperature of nheptane and ethanol blended fuel has an important reference significance for studying the reaction controlled compression ignition. The autoignition temperature of nheptane and ethanol blended fuel was predicted by BP neural network, which used nheptane mixing ratio, equivalence ratio and inlet pressure as input and autoignition temperature as output. When there were 16 nodes in a single hidden layer, the mean square error in the iterative process and the training state gradient were the minimum. The results show that the prediction accuracy is higher when the training, verification, test and global linear coefficients R of neural network model are 0.997 78, 0.997 9, 0.994 92 and 0.997 33 respectively. The generalization ability of neural network model for the variation of n heptane mixing ratio, equivalence ratio and inlet pressure is verified and the error between the predicted and experimental values is within the allowable range. Therefore, the predicted values obtained by this model are in good agreement with the experimental values.
Key words
BP neural network /
nheptane andethanol /
ethanol /
blended fuel /
auto-ignition temperature /
prediction
Cite this article
Download Citations
CHEN Ruolong，HAN Yongqiang，LI Runzhao，ZHANG Yiming，AN Dong，SUN Bo.
Prediction on Auto ignition Temperature of N heptane and Ethanol Blended Fuel Based on BP Neural Network[J]. Vehicle Engine. 2018, 0(1): 10-15 https://doi.org/10.3969/j.issn.1001-2222.2018.01.002
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
