Prediction of Reformed Gas Composition for Diesel Engines with a Reformed EGR System Using an Artificial Neural Network
Open Access
- 11 November 2020
- Vol. 13 (22), 5886
- https://doi.org/10.3390/en13225886
Abstract
Facing the reinforced emission regulations and moving toward a clean powertrain, hydrogen has become one of the alternative fuels for the internal combustion engine. In this study, the prediction methodology of hydrogen yield by on-board fuel reforming under a diesel engine is introduced. An engine dynamometer test was performed, resulting in reduced particulate matter (PM) and NOx emission with an on-board reformer. Based on test results, the reformed gas production rate from the on-board reformer was trained and predicted using an artificial neural network with a backpropagation process at various operating conditions. Additional test points were used to verify predicted results, and sensitivity analysis was performed to obtain dominant parameters. As a result, the temperature at the reformer outlet and oxygen concentration is the most dominant parameters to predict reformed gas owing to auto-thermal reforming driven by partial oxidation reforming process, dominantly.This publication has 19 references indexed in Scilit:
- Performance and emissions of a series hybrid vehicle powered by a gasoline partially premixed combustion engineApplied Thermal Engineering, 2019
- PM and NOx reduction characteristics of LNT/DPF+SCR/DPF hybrid systemEnergy, 2018
- Particulate matter formation and its control methodologies for diesel engine: A comprehensive reviewRenewable and Sustainable Energy Reviews, 2017
- Numerical Study of the Performance and Emission of a Diesel-Syngas Dual Fuel EngineMathematical Problems in Engineering, 2017
- Effect of exhaust gas recirculation on advanced diesel combustion and alternate fuels - A reviewApplied Energy, 2016
- Numerical investigation of a dual-loop EGR split strategy using a split index and multi-objective Pareto optimizationApplied Energy, 2015
- H2 effects on diesel combustion and emissions with an LPL-EGR systemInternational Journal of Hydrogen Energy, 2013
- Prediction of diesel engine performance using biofuels with artificial neural networkExpert Systems with Applications, 2010
- Low-Load Dual-Fuel Compression Ignition (CI) Engine Operation with an On-Board Reformer and a Diesel Oxidation Catalyst: Effects on Engine Performance and EmissionsEnergy & Fuels, 2010
- Urea-SCR: a promising technique to reduce NOx emissions from automotive diesel enginesCatalysis Today, 2000