Support Vector Machines for Identification of HCCI Combustion Dynamics

Vijay Manikandan Janakiraman, Jeff Sterniak, Dennis Assanis

Abstract

Homogeneous charge compression ignition (HCCI) is a promising technology for Internal Combustion Engines to improve efficiency and reduce nitrogen oxides emissions. Control of HCCI combustion is often model-based, and it is vital to have a good model of the engine to make control decisions. The HCCI engine is characterized by complex chemical kinetics whose physical modeling is difficult and laborious. Identification is an effective alternative to quickly develop control oriented models for such systems. This paper formulates a Support Vector Regression (SVR) methodology for developing identification models capturing HCCI combustion behavior. Measurable quantities from the engine such as net mean effective pressure (NMEP) and crank angle at 50% mass fraction burned (CA50) can be used to characterize and control the HCCI engine and are considered for identification in this study. The selected input variables include injected fuel mass (FM) and valve events {intake valve opening (IVO), exhaust valve closing (EVC)}. Transient data from a gasoline HCCI engine recorded at stable HCCI conditions is used for training, validating and testing the SVR models. Comparisons with the experimental results show that SVR with Gaussian kernels can be a powerful approach for identification of a complex combustion system like the HCCI engine.

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Paper Citation


in Harvard Style

Janakiraman V., Sterniak J. and Assanis D. (2012). Support Vector Machines for Identification of HCCI Combustion Dynamics . In Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-8565-21-1, pages 385-393. DOI: 10.5220/0004035903850393


in Bibtex Style

@conference{icinco12,
author={Vijay Manikandan Janakiraman and Jeff Sterniak and Dennis Assanis},
title={Support Vector Machines for Identification of HCCI Combustion Dynamics},
booktitle={Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2012},
pages={385-393},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004035903850393},
isbn={978-989-8565-21-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Support Vector Machines for Identification of HCCI Combustion Dynamics
SN - 978-989-8565-21-1
AU - Janakiraman V.
AU - Sterniak J.
AU - Assanis D.
PY - 2012
SP - 385
EP - 393
DO - 10.5220/0004035903850393