Identification for automotive systems

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 toa 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 forthe next generations of vehicles. Examines the subject from both the industrial and the academic point of view. Contains the results of up-to-the-moment research. Offers insights into exploiting progress in the field of identification. INDICE: 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 DynamicSystems. Using Genetic Programming in Nonlinear Model Identification. Markov Chain Modelling and On-board Identification for Automotive Vehicles. Close Loop systems Identification with Application to Diesel Engines. Parameter Identification in Dynamic Systems using the Homotopy Optimization Approach. Tutorial on Applications-oriented Optimal Experiment Design. Engine Calibration using Nonlinear Dynamic Modelling. Representation Limits of Mean Value Engine Models.Identification Methods for Reliable and High Dynamic Off-road Engines. Dynamic Mapping of Diesel Engine through System Identification. Off- and On-Line Identification of Maps Applied to the Gas Path in Diesel Engines. Identification Techniques for Control Oriented Models of Internal Combustion Engines. Modelling for HCCI Control. Comparison of Sensor Configurations for Mass Flow Estimation of Turbocharged Diesel Engines. Black and Gray Box Engine Models. Optimal Finite and Receding Horizon Control for Identification in Automotive Systems.

• ISBN: 978-1-4471-2220-3
• Editorial: Springer London
• Encuadernacion: Cartoné
• Páginas: 361
• Fecha Publicación: 26/11/2011
• Nº Volúmenes: 1
• Idioma: Inglés