eprintid: 427
rev_number: 16
eprint_status: archive
userid: 7
dir: disk0/00/00/04/27
datestamp: 2011-07-27 08:29:39
lastmod: 2011-11-17 11:26:40
status_changed: 2011-07-27 08:29:39
type: book_section
metadata_visibility: show
contact_email: alberto.bemporad@imtlucca.it
item_issues_count: 0
creators_name: Ripaccioli, Giulio
creators_name: Bernardini, Daniele
creators_name: Di Cairano, Stefano
creators_name: Bemporad, Alberto
creators_name: Kolmanovsky, Ilya
creators_id: 
creators_id: daniele.bernardini@imtlucca.it
creators_id: 
creators_id: alberto.bemporad@imtlucca.it
creators_id: 
title: A stochastic model predictive control approach for series hybrid electric vehicle power management
ispublished: pub
subjects: QA75
divisions: CSA
full_text_status: none
keywords: Markov chain; electric motor; hybrid electric vehicle; hybrid powertrain; internal combustion engine; power management; stochastic model predictive control approach; Markov processes; electric motors; energy management systems; hybrid electric vehicles; internal combustion engines; predictive control
note: Proceeding of the American Control Conference, Baltimore, MD, 2010
abstract: This paper illustrates the use of stochastic model predictive control (SMPC) for power management in vehicles equipped with advanced hybrid powertrains. Hybrid vehicles use two or more distinct power sources for propulsion, and their complex powertrain architecture requires the coordination of all the subsystems to achieve target performances in terms of fuel consumption, driveability, component life-time, exhaust emissions. Many control strategies have been presented and successfully applied, mainly based on heuristics or rules and tuned on certain reference drive cycles. To take into account that cycles are not exactly known a priori in driving routine, this paper proposes a stochastic approach for the power management problem. We focus on a series hybrid electric vehicle (HEV), which combines an internal combustion engine and an electric motor. The power demand from the driver is modeled as a Markov chain estimated on several driving cycles and used to generate scenarios in the SMPC law. Simulation results over a standard driving cycle are presented to demonstrate the effectiveness of the proposed stochastic approach and compared with other deterministic approaches.
date: 2010
date_type: published
publication: 2010 American Control Conference
publisher: IEEE
pagerange: 5844  -5849
event_title: 2010 ACC
event_location: 30 June- 2nd July , 2010
event_dates: Baltimore (MD)
refereed: TRUE
isbn: 978-1-4244-7427-1
book_title: American Control Conference
official_url: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5530504&isnumber=5530425
citation:   Ripaccioli, Giulio and Bernardini, Daniele and Di Cairano, Stefano and Bemporad, Alberto and Kolmanovsky, Ilya  A stochastic model predictive control approach for series hybrid electric vehicle power management.   In:  American Control Conference.   IEEE, 5844 -5849.  ISBN 978-1-4244-7427-1      (2010)