THERMAL SCIENCE

International Scientific Journal

Authors of this Paper

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Ravi Kumar Naradasu

,

Jyothirmai S

,

Ramesh R

TOWARDS ARTIFICIAL INTELLIGENCE BASED DIESEL ENGINE PERFORMANCE CONTROL UNDER VARYING OPERATING CONDITIONS USING SUPPORT VECTOR REGRESSION

ABSTRACT
Diesel engine designers are constantly on the look-out for performance enhancement through efficient control of operating parameters. In this paper, the concept of an intelligent engine control system is proposed that seeks to ensure optimized performance under varying operating conditions. The concept is based on arriving at the optimum engine operating parameters to ensure the desired output in terms of efficiency. In addition, a Support Vector Machines based prediction model has been developed to predict the engine performance under varying operating conditions. Experiments were carried out at varying loads, compression ratios and amounts of exhaust gas recirculation using a variable compression ratio diesel engine for data acquisition. It was observed that the SVM model was able to predict the engine performance accurately.
KEYWORDS
variable compression ratio diesel engine, SVM, performance, EGR
PAPER SUBMITTED: 2012-04-13
PAPER REVISED: 2012-08-23
PAPER ACCEPTED: 2012-10-22
DOI REFERENCE: https://doi.org/10.2298/TSCI120413218N
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2013, VOLUME 17, ISSUE Issue 1, PAGES [167 - 178]
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Towards artificial intelligence based diesel engine performance control under varying operating conditions using support vector regression

© 2024 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence