| Description |
1 online resource (89 pages) |
| Series |
SpringerBriefs in Nonlinear Circuits |
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SpringerBriefs in applied sciences and technology |
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SpringerBriefs in Nonlinear Circuits
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SpringerBriefs in applied sciences and technology
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| Contents |
Preface -- Contents -- About the Authors -- 1 Artificial Intelligence for Modeling and Control of Nonlinear Phenomena in Internal Combustion Engines -- 1.1 Neural Networks Architectures for Engine Applications -- 1.2 Use of ANNs for Modeling and Control of Internal Combustion Engines -- 1.2.1 Airâ#x80;#x93;Fuel Ratio Prediction and Control -- 1.2.2 Use of Neural Networks to Predict Combustion Pressure Parameters -- References -- 2 Non-interfering Diagnostics for the Study of Thermo-Fluid Dynamic Processes -- 2.1 Air Motion -- 2.2 Mixture Preparation -- 2.3 Combustion |
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2.4 Pollutants FormationReferences -- 3 Modeling of Particle Size Distribution at the Exhaust of Internal Combustion Engines -- 3.1 Particulate Matter Emissions in Engines -- 3.2 Real-Time Prediction of Particle Sizing at the Exhaust of a Diesel Engine -- References -- 4 Diagnosis and Control of Engine Combustion Using Vibration Signals -- References -- 5 Use of in-Cylinder Pressure and Learning Circuits for Engine Modeling and Control -- 5.1 Cylinder Pressure Analysis and Extraction of Parameters for Engine Combustion Diagnosis and Control |
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5.2 Use of Learning Algorithms in Pressure-Based Engine Controls5.3 Use of Combustion Pressure Signal for Cylinder Air Charge Estimation -- 5.4 Engine Knock Detection and Control Using in-Cylinder Pressure Measurement -- References -- 6 Identification and Compensation of Nonlinear Phenomena in Gasoline Direct Injection Process -- References |
| Summary |
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. The brief contains advanced methodologies --based on neural networks and soft-computing approaches among others-- for the compensation of engine nonlinearities by using the combustion pressure signal and proposes several techniques for the reconstruction of this signal on the basis of different engine parameters, including engine-block vibration and crankshaft rotational speed. Another topic of the book is the diagnosis of the nonlinearities of injection systems and their balancing, which is a mandatory task for the new generation of gasoline direct injection engines. The authors come from both industrial and academic backgrounds, so the brief represents an important tool both for researchers and practitioners in the automotive industry |
| Bibliography |
Includes bibliographical references at the end of each chapters and index |
| Notes |
Print version record |
| Subject |
Internal combustion engines -- Mathematical models
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Internal combustion engines -- Control
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TECHNOLOGY & ENGINEERING -- Mechanical.
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Internal combustion engines -- Mathematical models
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| Form |
Electronic book
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| Author |
Taglialatela-Scafati, Ferdinando
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Lavorgna, Mario
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Mancaruso, Ezio
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Vaglieco, Bianca Maria
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| ISBN |
9783319671406 |
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3319671405 |
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