An experimental based ANN approach in mapping performance-emission characteristics of a diesel engine operating in dual-fuel mode with LPG
作者： Amitav Chakraborty , Sumit Roy , Rahul Banerjee
DOI: 10.1016/J.JNGSE.2015.11.024
关键词:
摘要: Abstract The present study tries to harness the synergistic exploits of diesel-LPG dual fuel platform coupled with artificial neural network for addressing environmental intimidation due pollution, rigorous emission legislatives and future energy insecurity. operation resulted in higher brake thermal efficiency at high load, injection duration, which recorded a maximum rise 11% compared base line operation. At 25%, 50% 75% load optimal duration 15,000 μs registered 52%, 29% 13% BSFC diesel similar BSEC. Also rates LPG share can be observed highest 15,000 μs. A lower rate 45%, 65%, 27% NOx Soot is also penalty HC CO emission. An ANN model was developed predict BSFC, BTE, NOx, PM, based on experimental results, as input parameters network. capable predicting performance commendable accuracy relative values (R2), RMSE MAPE 0.99878, 0.020254 & 4.02% 0.99999, 0.61806 0.331536% 0.991299, 0.013617 4.31% 1.24 0.443% finally 0.99918, 0.37011 1.71% Soot.
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