Year: 2017
Type: article
Abstract: High ratio emissions that outcome from incomplete combustion cause air contamination, poorer the performance of the spark ignition (SI) engine and raise fuel consumption. Uncompleted combustion emitted a high ratio of CO, HC, NOx and PM harmful emissions such as come into atmosphere. This study has reviewed existing engine simulation structures using different methods as s as follows Neural Networks (NN), Sliding Mode Control (SMC), Proportional–Integral (PI) Predictive Control (MPC) and DRNN-based MPC method. The existing engine models were compared with the new engine simulation structure model which was proposed by the authors, using Hybrid Fuzzy Logic Control (HFLC) method in term of AFR. The simulation engine model in Matlab/Simulink using new engine simulation has founded that AFR (15.02, 14.4) which closes to the stoichiometric value of 14.7 compared by using Neural Networks (NN) method, a Sliding Mode Control (SMC) method, a Proportional–Integral (PI) control method, Model Predictive Control (MPC) method and DRNN-based MPC method.
Authors: Mohammad Javad Nekooei, Jaswar Koto
Institution: University of Technology Malaysia
Language: English
Topic: Engine and Fuel Emissions
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
Funder: Universiti Teknologi Malaysia
OpenAlex ID: W4410282945