Dolcini / Canudas-de-Wit / Béchart Dry Clutch Control for Automotive Applications

1. Auflage 2010
ISBN: 978-1-84996-068-7
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 144 Seiten, eBook

Reihe: Advances in Industrial Control

Dry Clutch Control for Automated Manual Transmission Vehiclesanalyses the control of a part of the powertrain which has a key role in ride comfort during standing-start and gear-shifting manoeuvres. The mechanical conception of the various elements in the driveline has long since been optimised so this book takes a more holistic system-oriented view of the problem featuring: a comprehensive description of the driveline elements and their operation paying particular attention to the clutch, a nonlinear model of the driveline for simulation and a simplified model for control design, with a standing-start driver automaton for closed loop simulation, a detailed analysis of the engagement operation and the related comfort criteria, different control schemes aiming at meeting these criteria, friction coefficient and unknown input clutch torque observers, practical implementation issues and solutions based on experience of implementing optimal engagement strategies on two Renault prototypes.

Zielgruppe

Research

Autoren/Hrsg.

Dolcini, Pietro J.

Canudas-de-Wit, Carlos

Béchart, Hubert

Inhaltsverzeichnis

Mechanical System and Comfort Requirements.- Powertrain.- Clutch Comfort.- Dry Clutch Engagement Control.- Synchronization Assistance.- Optimal Standing-start.- Clutch Friction and Torque Observer.- Experimental Results and Control Evaluation.- Open Problems and Conclusions.

Leseproben

"5 Optimal Standing-start (p. 71--72)

5.1 Principle

The solution of the optimal control problem through the use of a quadratic programming formulation has raised the activation time limitation imposed by the solution of the TPBVP over long intervals, allowing calculation of a complete optimal standing-start trajectory. This kind of solution could be used for the control of a AMT or a clutch-by-wire system where the clutch has to be controlled by the gearbox control unit from the very beginning of the engagement. In the previous chapter the solution of the optimal control problem has been obtained under the hypothesis of a constant engine torque.

This condition, perfectly reasonable for a short activation time over the last part of the engagement, is very hard if not downright impossible to assure when considering a whole standing-start operation. The possibility of having an engine torque evolution described by an homogeneous linear system could partially solve this di?culty but does not allow for a change of the driver’s wish during the engagement.

Taking into account these changes not only increases the driving comfort but is essential for security since the driver has to be always able to intervene in the vehicle behavior in order to react to a rapid change in his environment. To meet the opposing needs of taking into account the driver’s input and having some simple hypothesis on future input allowing for an optimal planning, the trajectory is not computed once and for all at the beginning of the engagement and then simply tracked by feedback, but periodically updated to follow the changes in the driver’s input and the actual behavior of the vehicle.

5.2 Exact Dynamic Replanning

5.2.1 Model Predictive Control

The model-based predictive control (MPC) is a control strategy that, in its most general formulation, consists in solving an optimal control problem in QP formulation for a simpli?ed and/or liberalized system over a ?nite time horizon of Nh samples and issuing the ?rst Nc control samples before using the newly measured or estimated system state x0 as the starting point for a new optimization. Compared to the previous control schemes the MPC strategy shows two main advantages, the ?rst being that a change in the driver’s input can be readily taken into account in the next optimization. The second advantage is that trajectory stabilization does not need to be assured by an external feedback loop since each new optimal trajectory has as a starting point the measured or estimated system state x0 that directly takes into account the actual system behavior."

Über Autor(innen)

Professor Canudas-de-Wit was born in Villahermosa, Tabasco, Mexico in 1958. He received his B.Sc. degree in electronics and communications from the Technological Institute of Monterrey, Mexico in 1980. In 1984 he received his M.Sc. in the Department of Automatic Control, Grenoble, France. In 1985 he was visiting researcher at Lund Institute of Technology, Sweden. In 1987 he received his Ph.D. in automatic control from the Polytechnic of Grenoble (Department of Automatic Control), France. Since then he has been working at the same department as "Directeur de Recherche at the CNRS", where he teaches and conducts research in the area of nonlinear control of mechanical systems, and on networked controlled systems. His research topics includes: vehicle control, adaptive control, identification, control of walking robots, systems with friction, AC and CD drives, and networked controlled systems. He has established several industrial collaboration projects with major French companies (FRAMATOME, EDF, CEA, IFREMER, RENAULT, SCHNEIDER, ILL). He has written a book in 1988 on adaptive control of partially known systems: theory and applications (Elsevier). In 1991, he edited Advanced Robot Control (978-3-540-54169-1), in Lecture Notes in Control and Information Sciences and, in 1997, Theory of Robot Control (978-3-540-76054-2) in Communications and Control Engineering. He was an associate editor of IEEE Transactions on Automatic Control, from 1992, to 1997, and of Automaticafrom 1999, to 2002. His research publications include: more than 120 International conference papers, and more than 47 published papers in international journals. He has supervised 20 Ph. D. students.