Identification for Automotive Systems [electronic resource] / edited by Daniel Alberer, Håkan Hjalmarsson, Luigi Re.

By: Alberer, Daniel [editor.]Contributor(s): Hjalmarsson, Håkan [editor.] | Re, Luigi [editor.] | SpringerLink (Online service)Material type: TextTextLanguage: English Series: Lecture Notes in Control and Information Sciences: 418Publisher: London : Springer London : Imprint: Springer, 2012Description: XVI, 356p. 172 illus., 129 illus. in color. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9781447122210Subject(s): Engineering | Systems theory | Engineering | Automotive Engineering | Systems Theory, Control | ControlAdditional physical formats: Printed edition:: No titleDDC classification: 629.2 LOC classification: TL1-483Online resources: Click here to access online
Contents:
From the Contents: Challenges and Opportunities for Identification Methods in Automotive Systems -- A Desired Modelling Environment for Automotive Powetrain Controls -- An Overview on System Identification Problems in Vehicle Chassis Control -- Linear Parameter-varying System Identification: The Subspace Approach -- A Tutorial on Numerical Methods for State and Parameter Estimation in Nonlinear Dynamic Systems -- Using Genetic Programming in Nonlinear Model Identification -- Markov Chain Modelling and On-board Identification for Automotive Vehicles.
In: Springer eBooksSummary: Increasing complexity and performance and reliability expectations make modeling of automotive system both more difficult and more urgent. Automotive control has slowly evolved from an add-on to classical engine and vehicle design to a key technology to enforce consumption, pollution and safety limits. Modeling, however, is still mainly based on classical methods, even though much progress has been done in the identification community to speed it up and improve it. This book, the product of a workshop of representatives of different communities, offers an insight on how to close the gap and exploit this progress for the next generations of vehicles.
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From the Contents: Challenges and Opportunities for Identification Methods in Automotive Systems -- A Desired Modelling Environment for Automotive Powetrain Controls -- An Overview on System Identification Problems in Vehicle Chassis Control -- Linear Parameter-varying System Identification: The Subspace Approach -- A Tutorial on Numerical Methods for State and Parameter Estimation in Nonlinear Dynamic Systems -- Using Genetic Programming in Nonlinear Model Identification -- Markov Chain Modelling and On-board Identification for Automotive Vehicles.

Increasing complexity and performance and reliability expectations make modeling of automotive system both more difficult and more urgent. Automotive control has slowly evolved from an add-on to classical engine and vehicle design to a key technology to enforce consumption, pollution and safety limits. Modeling, however, is still mainly based on classical methods, even though much progress has been done in the identification community to speed it up and improve it. This book, the product of a workshop of representatives of different communities, offers an insight on how to close the gap and exploit this progress for the next generations of vehicles.

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