The University of Southampton
University of Southampton Institutional Repository

Green driving optimization of a series hybrid electric vehicle

Green driving optimization of a series hybrid electric vehicle
Green driving optimization of a series hybrid electric vehicle
This paper develops an indirect optimal control methodology to achieve green driving optimisation for series hybrid electric vehicles. Starting from a given vehicle mission, specified in terms of a road journey that has to be completed in a given amount of time, the power sharing among the powertrain sources and the vehicle speed profile along the journey are optimised and found. The scheme combines parametric modelling of the vehicle and powertrain together with computationally efficient optimal control software to provide an optimization strategy that works in real-time. Simulation results that demonstrate the success of the method and provide further insight into efficient driving, are presented.
978-146735717-3
2200-2207
Lot, R.
ceb0ca9c-6211-4051-a7b8-90fd6f0a6d78
Evangelou, S.A.
9cea686b-66c5-4478-bcfc-5e457366cb4f
Lot, R.
ceb0ca9c-6211-4051-a7b8-90fd6f0a6d78
Evangelou, S.A.
9cea686b-66c5-4478-bcfc-5e457366cb4f

Lot, R. and Evangelou, S.A. (2013) Green driving optimization of a series hybrid electric vehicle. IEEE Conference on Decision and Control 2013, Florence, Italy. 10 - 13 Dec 2013. pp. 2200-2207 . (doi:10.1109/CDC.2013.6760208).

Record type: Conference or Workshop Item (Paper)

Abstract

This paper develops an indirect optimal control methodology to achieve green driving optimisation for series hybrid electric vehicles. Starting from a given vehicle mission, specified in terms of a road journey that has to be completed in a given amount of time, the power sharing among the powertrain sources and the vehicle speed profile along the journey are optimised and found. The scheme combines parametric modelling of the vehicle and powertrain together with computationally efficient optimal control software to provide an optimization strategy that works in real-time. Simulation results that demonstrate the success of the method and provide further insight into efficient driving, are presented.

This record has no associated files available for download.

More information

Published date: 2013
Additional Information: cited By 1
Venue - Dates: IEEE Conference on Decision and Control 2013, Florence, Italy, 2013-12-10 - 2013-12-13
Organisations: Energy Technology Group

Identifiers

Local EPrints ID: 382682
URI: http://eprints.soton.ac.uk/id/eprint/382682
ISBN: 978-146735717-3
PURE UUID: 8a6c8687-2c48-459e-b1b9-aa8de3105857
ORCID for R. Lot: ORCID iD orcid.org/0000-0001-5022-5724

Catalogue record

Date deposited: 03 Nov 2015 12:27
Last modified: 14 Mar 2024 21:31

Export record

Altmetrics

Contributors

Author: R. Lot ORCID iD
Author: S.A. Evangelou

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×