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Massachusetts Institute of Technology

Optimally controlling hybrid electric vehicles using path forecasting

Abstract

dc:description.abstract

Hybrid Electric Vehicles (HEVs) with path-forecasting belong to the class of fuel efficient vehicles, which use external sensory information and powertrains with multiple operating modes in order to increase fuel economy. Their main characteristic is that the decision to charge and discharge the battery is made in part by using a prediction of future road conditions. The increasing presence of GPS navigational systems in the standard feature sets of the modern vehicles suggests that path predictive methods applied to HEVs constitute one of the most promising directions towards the solution of serious problems of our era, such as the energy problem, the increasing cost of oil, and the greenhouse gas emissions. In the current project we are given a route and an HEV simulation model, and we aim to minimize the fuel consumption of the vehicle along the route. Towards this direction, we adopt a novel way of decomposing the route into a series of route segments connected to each other and linking the origin to the destination. For each route segment, the road grade, the segment length, and the nominal speed are available. Then, the main idea of our method is to prescribe those set-points of the state of charge of the battery for each road segment, that result in the most fuel efficient travel between the origin and the destination.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2008

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Katsargyri, Georgia-Evangelina
Advisor dc:contributor.advisor
  • Munther A. Dahleh.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/44455
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/44455

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Katsargyri, Georgia-Evangelina. Optimally controlling hybrid electric vehicles using path forecasting. Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/44455