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Developments in Predictive and Optimization-Based Control of Automotive Powertrain Systems

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Abstract:
Automotive systems are rapidly evolving to provide better functionality and value to customers, and to satisfy increasingly stringent requirements and regulations. New automotive technologies are introduced or combined in new ways at a rapidly increasing pace. Role and importance of electronic control is increasing, and so are the opportunities for applications of advanced control, estimation, prediction and diagnostic algorithms as well as of emerging control system paradigms. Along these lines, the presenter will review several recent case studies and examples of applying prediction-based and optimization-based control to control of powertrain systems. These will include adaptive posicast control of engine idle speed and air-to-fuel ratio, and Model Predictive Control of engine idle speed. Opportunities for preview-based control of boosted engines will be highlighted. Optimal control and Model Predictive Control of Hybrid Electric Vehicles and constrained control of vehicle active steering will be also touched upon.

Type of Seminar:
Public Seminar
Speaker:
Dr Ilya V. Kolmanovsky
Ford Research and Advanced Engineering, Ford Motor Company, Dearborn,
Date/Time:
Oct 27, 2008   14:15
Location:

ETH Zentrum, Gloriastrasse 35, Building ETZ, Room E 6
Contact Person:

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Biographical Sketch:
Ilya Kolmanovsky studied as an undergraduate at Moscow Aviation Institute in Russia. He received his M.S. and Ph.D. degrees in Aerospace Engineering in 1993 and 1995, respectively, and his M.A. in Mathematics in 1995, all from the University of Michigan, Ann Arbor. In 1996. Dr. Kolmanovsky joined Ford Research Laboratory of Ford Motor Company in Dearborn, Michigan, as a technical specialist. At Ford he has been conducting research on control, modeling and systems development of advanced technology automotive gasoline and diesel powertrains, and is presently a staff technical specialist. Dr. Kolmanovsky has also made contributions to nonlinear control of non-holonomic systems with applications to multi-body spacecraft, nonlinear control of systems with pointwise-in-time state and control constraints, control of systems with complex dynamics, including switching systems, stochastic systems, systems with delays and systems described by partial differential equations.