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  • © 2010

Automotive Model Predictive Control

Models, Methods and Applications

Editors:

  1. Luigi Re

    1. Institute for Design and Control of Mechatronical Systems, Johannes Kepler University Linz, Linz

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  2. Frank Allgöwer

    1. Institute for Systems Theory and Automatic Control, University of Stuttgart, Stuttgart

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  3. Luigi Glielmo

    1. Facoltà di Ingegneria, Università del Sannio in Benevento, Benevento

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  4. Carlos Guardiola

    1. Departamento de Máquinas y Motores Térmicos, Universidad Politécnica de Valencia (UPV), Valencia, (Spain)

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  5. Ilya Kolmanovsky

    1. Ford Research and Adv. Engineering, Ford Motor Company, Technical Leader, Powertrain Control R&A

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  • Gives the reader access to the uses of a modern and successful method of control in a most important applications area
  • Presents the points of view of industry-based engineers and academic research to give a balanced, practical but cutting-edge perspective

Part of the book series: Lecture Notes in Control and Information Sciences (LNCIS, volume 402)

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Table of contents (17 chapters)

  1. Front Matter

    PDF

  2. Chances and Challenges in Automotive Predictive Control

    1. Chances and Challenges in Automotive Predictive Control

      • Luigi del Re, Peter Ortner, Daniel Alberer
      Pages 1-22

  3. Part I: Models

    1. Front Matter

      Pages 23-23
      PDF

    2. On Board NOx Prediction in Diesel Engines: A Physical Approach

      • Jean Arrègle, J. Javier López, Carlos Guardiola, Christelle Monin
      Pages 25-36

    3. Mean Value Engine Models Applied to Control System Design and Validation

      • Pierre Olivier Calendini, Stefan Breuer
      Pages 37-52

    4. Physical Modeling of Turbocharged Engines and Parameter Identification

      • Lars Eriksson, Johan Wahlström, Markus Klein
      Pages 53-71

    5. Dynamic Engine Emission Models

      • Markus Hirsch, Klaus Oppenauer, Luigi del Re
      Pages 73-87

  4. Part II: Methods

    1. Front Matter

      Pages 105-105
      PDF

    2. An Overview of Nonlinear Model Predictive Control

      • Lalo Magni, Riccardo Scattolini
      Pages 107-117

    3. Optimal Control Using Pontryagin’s Maximum Principle and Dynamic Programming

      • Bart Saerens, Moritz Diehl, Eric Van den Bulck
      Pages 119-138

    4. On the Use of Parameterized NMPC in Real-time Automotive Control

      • Mazen Alamir, André Murilo, Rachid Amari, Paolina Tona, Richard Fürhapter, Peter Ortner
      Pages 139-149

  5. Part III: Applications

    1. Front Matter

      Pages 151-151
      PDF

    3. Model Predictive Control of Partially Premixed Combustion

      • Per Tunestål, Magnus Lewander
      Pages 171-181

    4. Model Predictive Powertrain Control: An Application to Idle Speed Regulation

      • Stefano Di Cairano, Diana Yanakiev, Alberto Bemporad, Ilya Kolmanovsky, Davor Hrovat
      Pages 183-194

    5. On Low Complexity Predictive Approaches to Control of Autonomous Vehicles

      • Paolo Falcone, Francesco Borrelli, Eric H. Tseng, Davor Hrovat
      Pages 195-210

    6. Toward a Systematic Design for Turbocharged Engine Control

      • Greg Stewart, Francesco Borrelli, Jaroslav Pekar, David Germann, Daniel Pachner, Dejan Kihas
      Pages 211-230

    7. An Integrated LTV-MPC Lateral Vehicle Dynamics Control: Simulation Results

      • Giovanni Palmieri, Osvaldo Barbarisi, Stefano Scala, Luigi Glielmo
      Pages 231-255

    8. MIMO Model Predictive Control for Integral Gas Engines

      • Jakob Ängeby, Matthias Huschenbett, Daniel Alberer
      Pages 257-272
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About this book

Automotive control has developed over the decades from an auxiliary te- nology to a key element without which the actual performances, emission, safety and consumption targets could not be met. Accordingly, automotive control has been increasing its authority and responsibility – at the price of complexity and di?cult tuning. The progressive evolution has been mainly ledby speci?capplicationsandshorttermtargets,withthe consequencethat automotive control is to a very large extent more heuristic than systematic. Product requirements are still increasing and new challenges are coming from potentially huge markets like India and China, and against this ba- ground there is wide consensus both in the industry and academia that the current state is not satisfactory. Model-based control could be an approach to improve performance while reducing development and tuning times and possibly costs. Model predictive control is a kind of model-based control design approach which has experienced a growing success since the middle of the 1980s for “slow” complex plants, in particular of the chemical and process industry. In the last decades, severaldevelopments haveallowedusing these methods also for “fast”systemsandthis hassupporteda growinginterestinitsusealsofor automotive applications, with several promising results reported. Still there is no consensus on whether model predictive control with its high requi- ments on model quality and on computational power is a sensible choice for automotive control.
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Keywords

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Editors and Affiliations

  • Institute for Design and Control of Mechatronical Systems, Johannes Kepler University Linz, Linz

    Luigi Re

  • Institute for Systems Theory and Automatic Control, University of Stuttgart, Stuttgart

    Frank Allgöwer

  • Facoltà di Ingegneria, Università del Sannio in Benevento, Benevento

    Luigi Glielmo

  • Departamento de Máquinas y Motores Térmicos, Universidad Politécnica de Valencia (UPV), Valencia, (Spain)

    Carlos Guardiola

  • Ford Research and Adv. Engineering, Ford Motor Company, Technical Leader, Powertrain Control R&A

    Ilya Kolmanovsky

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Bibliographic Information

  • Book Title: Automotive Model Predictive Control

  • Book Subtitle: Models, Methods and Applications

  • Editors: Luigi Re, Frank Allgöwer, Luigi Glielmo, Carlos Guardiola, Ilya Kolmanovsky

  • Series Title: Lecture Notes in Control and Information Sciences

  • DOI: https://doi.org/10.1007/978-1-84996-071-7

  • Publisher: Springer London

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer-Verlag London 2010

  • Softcover ISBN: 978-1-84996-070-0Published: 11 March 2010

  • eBook ISBN: 978-1-84996-071-7Published: 11 March 2010

  • Series ISSN: 0170-8643

  • Series E-ISSN: 1610-7411

  • Edition Number: 1

  • Number of Pages: XIV, 290

  • Number of Illustrations: 152 b/w illustrations

  • Topics: Control and Systems Theory, Automotive Engineering

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Buy it now

eBook USD 139.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 179.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

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