Multi objective optimization of HCCI combustion fuelled with fusel oil and n-heptane blends

A review of water injection application on spark-ignition engines

De-NOx characteristics of HC-SCR system employing combined Ag/Al2O3 and CuSn/ZSM-5 catalyst

Based on the experimental ignition delay results of n-butane/hydrogen mixtures in a rapid compression machine, a Genetic Algorithm (GA) optimized Back Propagation (BP) neural network model is originally developed for ignition delay prediction. In the BP model, the activation function, learning rate and the neurons number in the hidden layer are optimized, respectively. The prediction ability of the BP model is validated in wide operating ranges, i.e., compression pressures from 20 to 25 bar, compression temperatures from 722 to 987 K, equivalence ratios from 0.5 to 1.5 and molar ratios of hydrogen ( X H 2 ) from 0 to 75%. Compared with the BP model, the GA optimized BP model could increase the average correlation coefficient from 0.9745 to 0.9890, in the opposite, the average Mean Square Error (MSE) decreased from 2.21 to 1.06. On the other hand, to assess the BP-GA model prediction ability in the never-seen-before cases, a limited BP-GA model is fostered in the X H 2 range from 0 to 50% to predict the ignition delays at the cases of X H 2 =75%. It is found that the predicted ignition delays are underestimated due to the training dataset lacking of “acceleration feature” that happened at X H 2 =75%. However, three possible options are reported to improve the prediction accuracy in such never-seen-before cases.

Development of the ignition delay prediction model of n-butane/hydrogen mixtures based on artificial neural network

In order to improve thermal efficiency of spark ignition engine under super-lean burn conditions (excess air ratio λ≈2.0), thermal stratification technique by in-cylinder water injection toward pis...

Thermal efficiency improvement of super-lean burn spark ignition engine by stratified water insulation on piston top surface

Combustion Characteristic of Offset Orifice Nozzle under Multi Pulse Ultrahigh Pressure Injection and PCCI Combustion Conditions

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Hidenori Kosaka

Papers

Thermal efficiency improvement of super-lean burn spark ignition engine by stratified water insulation on piston top surface

Combustion Characteristic of Offset Orifice Nozzle under Multi Pulse Ultrahigh Pressure Injection and PCCI Combustion Conditions

Study on Effect of Nozzle Hole Length to Diameter Ratio on Near-Field Diesel Spray Characteristics at High Density Conditions