<p><P>Internal combustion engines (ICE) still have potential for substantial improvements, particularly with regard to fuel efficiency and environmental compatibility. In order to fully exploit the remaining margins, increasingly sophisticated control systems have to be applied. This book offers an
Introduction to Modeling and Control of Internal Combustion Engine Systems
โ Scribed by Professor Dr. Lino Guzzella, Dr. Christopher H. Onder (auth.)
- Publisher
- Springer Berlin Heidelberg
- Year
- 2004
- Tongue
- English
- Leaves
- 303
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Table of Contents
Front Matter....Pages I-IX
Introduction....Pages 1-19
Mean-Value Models....Pages 21-127
Discrete-Event Models....Pages 129-171
Control of Engine Systems....Pages 173-221
Back Matter....Pages 223-300
โฆ Subjects
Automotive Engineering; Engineering Thermodynamics, Heat and Mass Transfer; Control, Robotics, Mechatronics
๐ SIMILAR VOLUMES
<p><P>Internal combustion engines (ICE) still have potential for substantial improvements, particularly with regard to fuel efficiency and environmental compatibility. In order to fully exploit the remaining margins, increasingly sophisticated control systems have to be applied. This book offers an
<p><p>The increasing demands for internal combustion engines with regard to fuel consumption, emissions and driveability lead to more actuators, sensors and complex control functions. A systematic implementation of the electronic control systems requires mathematical models from basic design through
<p><p>The increasing demands for internal combustion engines with regard to fuel consumption, emissions and driveability lead to more actuators, sensors and complex control functions. A systematic implementation of the electronic control systems requires mathematical models from basic design through
<p><p>This brief provides an overview on the most relevant nonlinear phenomena in internal combustion engines with a particular emphasis on the use of nonlinear circuits in their modelling and control.</p><p>The brief contains advanced methodologies โbased on neural networks and soft-computing appro