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Hybrid modeling, identification, and predictive control: an application to hybrid electric vehicle energy management

Ripaccioli, Giulio and Bemporad, Alberto and Assadian, F. and Dextreit, C. and Di Cairano, Stefano and Kolmanovsky, Ilya Hybrid modeling, identification, and predictive control: an application to hybrid electric vehicle energy management. In: Hybrid Systems: Computation and Control. Lecture Notes in Computer Science (5469). Springer-Verlag Berlin Heidelberg, pp. 321-335. ISBN 978-3-642-00601-2 (2009)

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Abstract

Rising fuel prices and tightening emission regulations have resulted in an increasing need for advanced powertrain systems and systematic model-based control approaches. Along these lines, this paper illustrates the use of hybrid modeling and model predictive control for a vehicle equipped with an advanced hybrid powertrain. Starting from an existing high fidelity nonlinear simulation model based on experimental data, the hybrid dynamical model is developed through the use of linear and piecewise affine identification methods. Based on the resulting hybrid dynamical model, a hybrid MPC controller is tuned and its effectiveness is demonstrated through closed-loop simulations with the high-fidelity nonlinear model.

Item Type: Book Section
Identification Number: 10.1007/978-3-642-00602-9_23
Uncontrolled Keywords: Hybrid systems; Model predictive control; Powertrain control; Hybrid electric vehicles; Piecewise affine systems; Piecewise affine system identification
Subjects: H Social Sciences > HB Economic Theory
T Technology > TA Engineering (General). Civil engineering (General)
Research Area: Computer Science and Applications
Depositing User: Professor Alberto Bemporad
Date Deposited: 27 Jul 2011 08:34
Last Modified: 05 Aug 2011 12:43
URI: http://eprints.imtlucca.it/id/eprint/513

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