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Journal of Optimization
Volume 2014, Article ID 135163, 9 pages
http://dx.doi.org/10.1155/2014/135163
Research Article

Combustion Model and Control Parameter Optimization Methods for Single Cylinder Diesel Engine

1Research Centre for Electrical Power & Mechatronics, Indonesian Institute of Sciences, Komp LIPI Jl Cisitu 21/54D, Gd 20, Bandung 40135, Indonesia
2Graduate School of Information, Production and Systems, Waseda University, 2-7 Hibikino, Wakamatsu-ku, Kitakyushu, Fukuoka 808-0135, Japan

Received 26 May 2014; Accepted 2 September 2014; Published 22 September 2014

Academic Editor: Cheng-Hong Yang

Copyright © 2014 Bambang Wahono and Harutoshi Ogai. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This research presents a method to construct a combustion model and a method to optimize some control parameters of diesel engine in order to develop a model-based control system. The construction purpose of the model is to appropriately manage some control parameters to obtain the values of fuel consumption and emission as the engine output objectives. Stepwise method considering multicollinearity was applied to construct combustion model with the polynomial model. Using the experimental data of a single cylinder diesel engine, the model of power, BSFC, , and soot on multiple injection diesel engines was built. The proposed method succesfully developed the model that describes control parameters in relation to the engine outputs. Although many control devices can be mounted to diesel engine, optimization technique is required to utilize this method in finding optimal engine operating conditions efficiently beside the existing development of individual emission control methods. Particle swarm optimization (PSO) was used to calculate control parameters to optimize fuel consumption and emission based on the model. The proposed method is able to calculate control parameters efficiently to optimize evaluation item based on the model. Finally, the model which added PSO then was compiled in a microcontroller.