relation: http://eprints.imtlucca.it/513/
title: Hybrid modeling, identification, and predictive control: an application to hybrid electric vehicle energy management
creator: Ripaccioli, Giulio
creator: Bemporad, Alberto
creator: Assadian, F.
creator: Dextreit, C.
creator: Di Cairano, Stefano
creator: Kolmanovsky, Ilya
subject: HB Economic Theory
subject: TA Engineering (General). Civil engineering (General)
description: 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. 
publisher: Springer-Verlag Berlin Heidelberg
contributor: Majumdar,  Rupak
contributor: Tabuada, Paulo
date: 2009
type: Book Section
type: PeerReviewed
identifier:   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)  
relation: http://www.springerlink.com/content/90127566ul527173/
relation: 10.1007/978-3-642-00602-9_23