Optimally Controlling Hybrid Electric Vehicles using Path Forecasting
Name
Katsargyri-2009-Optimally Controlling Hybrid Electric Vehicles using Path Forecasting.pdf
Size
611.46 KB
Format
Adobe PDF
Checksum (MD5)
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Author(s)
Kolmanovsky, Ilya V.
Michelini, John
Kuang, Ming L.
Phillips, Anthony M.
Katsargyri, Georgia-Evangel
Rinehart, Michael David
Dahleh, Munther A.
Date Issued
July 2009
Journal
American Control Conference, 2009. ACC '09.
Publisher
Institute of Electrical and Electronics Engineers
Citation
Katsargyri, G.-E. et al. “Optimally controlling Hybrid Electric Vehicles using path forecasting.” American Control Conference, 2009. ACC '09. 2009. 4613-4617.
Version
Final published version
Abstract
The paper examines path-dependent control of Hybrid Electric Vehicles (HEVs). In this approach we seek to improve HEV fuel economy by optimizing charging and discharging of the vehicle battery depending on the forecasted vehicle route. The route is decomposed into a series connection of route segments with (partially) known properties. The dynamic programming is used as a tool to quantify the benefits offered by route information availability.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/ACC.2009.5160504
