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Automotive Model Predictive Control
Models, Methods and Applications English · Paperback / Softback

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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.

Summary

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.

Product details

Assisted by Luigi del Re (Editor), Frank Allgöwer (Editor), Luigi Glielmo (Editor), Carlos Guardiola (Editor), Ilya Kolmanovsky (Editor), Fran Allgöwer (Editor), Luigi Glielmo et al (Editor), Frank Allgoewer (Editor)
Publisher Springer, Berlin
 
Content Book
Product form Paperback / Softback
Publication date 26.07.2011
Subject Natural sciences, medicine, IT, technology > Technology > Electronics, electrical engineering, communication
 
EAN 9781849960700
ISBN 978-1-84996-070-0
Pages 290
Illustrations XIV, 290 p. 152 illus.
Dimensions (packing) 16.1 x 23.7 x 1.2 cm
Weight (packing) 518 g
 
Series Lecture Notes in Control and Information Sciences > 402
Lecture Notes in Control and Information Sciences
Subjects Simulation, Fahrzeugbau, B, Optimization, engineering, Combustion, Automotive Engineering, Control and Systems Theory, Control engineering, Automotive technology & trades, Automotive (motor mechanic) skills, Nonlinear Model Predictive Control
 

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