A real-time capable enhanced dynamic programming approach for predictive optimal cruise control in hybrid electric vehicles
Hybrid electric vehicles (HEV) combine both a powerful engine and the ability to reduce fuel consumption through an electric machine by intelligent control of a complex drive train. The driving strategy controls the speed and the operating strategy controls the energy management of the HEV. Both are combined in one optimization. The result is a driver assistance system that is tuned with predictive information about the upcoming route. A novel algorithm based on dynamic programming (DP) is presented that allows real-time application by introducing heuristic model-based optimization space reductions. The main focus is on the design and dimensioning of a slim DP algorithm with the capability to find an optimal control in close real-time.
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Availability:
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Supplemental Notes:
- Abstract reprinted with permission of IEEE.
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Corporate Authors:
Institute of Electrical and Electronics Engineers (IEEE)
3 Park Avenue, 17th Floor
New York, NY United States 10016-5997 -
Authors:
- Wahl, H G
- Bauer, K L
- Gauterin, F
- Holzapfel, M
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Conference:
- 16th International IEEE Conference on Intelligent Transportation Systems (ITSC)
- Location: The Hague , Netherlands
- Date: 2013-10-6 to 2013-10-9
- Publication Date: 2013-10
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 1662-1667
- Monograph Title: 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)
Subject/Index Terms
- TRT Terms: Algorithms; Autonomous intelligent cruise control; Driver support systems; Dynamic programming; Hybrid vehicles; Optimization
- Uncontrolled Terms: Predictive control
- Subject Areas: Energy; Highways; Operations and Traffic Management; Vehicles and Equipment; I73: Traffic Control; I91: Vehicle Design and Safety;
Filing Info
- Accession Number: 01563251
- Record Type: Publication
- ISBN: 9781479929146
- Files: TRIS
- Created Date: May 5 2015 11:00AM