Optimally Controlling Hybrid Electric Vehicles using Path Forecasting
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 segmen...
| Main Authors: | , , , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
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Institute of Electrical and Electronics Engineers
2010
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| Online Access: | http://hdl.handle.net/1721.1/59409 https://orcid.org/0000-0003-4858-3463 https://orcid.org/0000-0002-1470-2148 |
| _version_ | 1826206554583465984 |
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| author | Kolmanovsky, Ilya V. Michelini, John Kuang, Ming L. Phillips, Anthony M. Katsargyri, Georgia-Evangel Rinehart, Michael David Dahleh, Munther A. |
| author2 | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
| author_facet | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Kolmanovsky, Ilya V. Michelini, John Kuang, Ming L. Phillips, Anthony M. Katsargyri, Georgia-Evangel Rinehart, Michael David Dahleh, Munther A. |
| author_sort | Kolmanovsky, Ilya V. |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T13:34:46Z |
| format | Article |
| id | mit-1721.1/59409 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T13:34:46Z |
| publishDate | 2010 |
| publisher | Institute of Electrical and Electronics Engineers |
| record_format | dspace |
| spelling | mit-1721.1/594092022-09-28T14:46:16Z Optimally Controlling Hybrid Electric Vehicles using Path Forecasting Kolmanovsky, Ilya V. Michelini, John Kuang, Ming L. Phillips, Anthony M. Katsargyri, Georgia-Evangel Rinehart, Michael David Dahleh, Munther A. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology. Laboratory for Information and Decision Systems Dahleh, Munther A. Katsargyri, Georgia-Evangel Rinehart, Michael David Dahleh, Munther A. 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. Ford Motor Company 2010-10-19T18:39:29Z 2010-10-19T18:39:29Z 2009-07 Article http://purl.org/eprint/type/JournalArticle 978-1-4244-4523-3 0743-1619 INSPEC Accession Number: 10775880 http://hdl.handle.net/1721.1/59409 Katsargyri, G.-E. et al. “Optimally controlling Hybrid Electric Vehicles using path forecasting.” American Control Conference, 2009. ACC '09. 2009. 4613-4617. https://orcid.org/0000-0003-4858-3463 https://orcid.org/0000-0002-1470-2148 en_US http://dx.doi.org/10.1109/ACC.2009.5160504 American Control Conference, 2009. ACC '09. 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. application/pdf Institute of Electrical and Electronics Engineers IEEE |
| spellingShingle | Kolmanovsky, Ilya V. Michelini, John Kuang, Ming L. Phillips, Anthony M. Katsargyri, Georgia-Evangel Rinehart, Michael David Dahleh, Munther A. Optimally Controlling Hybrid Electric Vehicles using Path Forecasting |
| title | Optimally Controlling Hybrid Electric Vehicles using Path Forecasting |
| title_full | Optimally Controlling Hybrid Electric Vehicles using Path Forecasting |
| title_fullStr | Optimally Controlling Hybrid Electric Vehicles using Path Forecasting |
| title_full_unstemmed | Optimally Controlling Hybrid Electric Vehicles using Path Forecasting |
| title_short | Optimally Controlling Hybrid Electric Vehicles using Path Forecasting |
| title_sort | optimally controlling hybrid electric vehicles using path forecasting |
| url | http://hdl.handle.net/1721.1/59409 https://orcid.org/0000-0003-4858-3463 https://orcid.org/0000-0002-1470-2148 |
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