Intelligent techniques for improved engine fuel economy

Research output: ThesisDoctoral Thesis

Abstract

This thesis presents an investigation into a novel method of estimating the trajectory (future direction and elevation) of a vehicle, and subsequently influencing the control of an engine. The technique represents a convenient and robust method of achieving road prediction, to form a fuzzy system that „looks ahead‟, leading potentially to improved fuel consumption and a consequent reduction in exhaust emissions. The work described in this thesis brings together two modern technologies, Neuro-fuzzy techniques and Global Positioning System, and applies them to engine/vehicle control.
Original languageEnglish
QualificationMaster of Philosophy
Awarding Institution
  • University of Brighton
Publication statusPublished - Apr 2011

Fingerprint

Fuel economy
Engines
Fuzzy systems
Fuel consumption
Global positioning system
Trajectories

Bibliographical note

Copyright © and Moral Rights for this thesis are retained by the author and/or other copyright owners.

Cite this

@phdthesis{98bbbb2e7d7e40468416f8bf55dee626,
title = "Intelligent techniques for improved engine fuel economy",
abstract = "This thesis presents an investigation into a novel method of estimating the trajectory (future direction and elevation) of a vehicle, and subsequently influencing the control of an engine. The technique represents a convenient and robust method of achieving road prediction, to form a fuzzy system that „looks ahead‟, leading potentially to improved fuel consumption and a consequent reduction in exhaust emissions. The work described in this thesis brings together two modern technologies, Neuro-fuzzy techniques and Global Positioning System, and applies them to engine/vehicle control.",
author = "Shin Lee",
note = "Copyright {\circledC} and Moral Rights for this thesis are retained by the author and/or other copyright owners.",
year = "2011",
month = "4",
language = "English",
school = "University of Brighton",

}

Lee, S 2011, 'Intelligent techniques for improved engine fuel economy', Master of Philosophy, University of Brighton.

Intelligent techniques for improved engine fuel economy. / Lee, Shin.

2011. 152 p.

Research output: ThesisDoctoral Thesis

TY - THES

T1 - Intelligent techniques for improved engine fuel economy

AU - Lee, Shin

N1 - Copyright © and Moral Rights for this thesis are retained by the author and/or other copyright owners.

PY - 2011/4

Y1 - 2011/4

N2 - This thesis presents an investigation into a novel method of estimating the trajectory (future direction and elevation) of a vehicle, and subsequently influencing the control of an engine. The technique represents a convenient and robust method of achieving road prediction, to form a fuzzy system that „looks ahead‟, leading potentially to improved fuel consumption and a consequent reduction in exhaust emissions. The work described in this thesis brings together two modern technologies, Neuro-fuzzy techniques and Global Positioning System, and applies them to engine/vehicle control.

AB - This thesis presents an investigation into a novel method of estimating the trajectory (future direction and elevation) of a vehicle, and subsequently influencing the control of an engine. The technique represents a convenient and robust method of achieving road prediction, to form a fuzzy system that „looks ahead‟, leading potentially to improved fuel consumption and a consequent reduction in exhaust emissions. The work described in this thesis brings together two modern technologies, Neuro-fuzzy techniques and Global Positioning System, and applies them to engine/vehicle control.

M3 - Doctoral Thesis

ER -