Path dependent receding horizon control policies for hybrid electric vehicles

• Main Authors: Kolmanovsky, Ilya V. (Author), Michelini, John (Author), Kuang, Ming L. (Author), Phillips, Anthony M. (Author), Katsargyri, Georgia-Evangel (Contributor), Rinehart, Michael David (Contributor), Dahleh, Munther A. (Contributor)
• Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), Massachusetts Institute of Technology. Laboratory for Information and Decision Systems (Contributor)
• Format: Article
• Language: English
• Published: Institute of Electrical and Electronics Engineers, 2010-10-19T19:17:08Z.
• Subjects: Article
• Online Access: Get fulltext

Future hybrid electric vehicles (HEVs) may use path-dependent operating policies to improve fuel economy. In our previous work, we developed a dynamic programming (DP) algorithm for prescribing the battery state of charge (SoC) set-point, which in combination with a novel approach of route decomposition, has been shown to reduce fuel consumption over selected routes. In this paper, we propose and illustrate a receding horizon control (RHC) strategy for the on-board optimization of the fuel consumption. As compared to the DP approach, the computational requirements of the RHC strategy are lower. In addition, the RHC strategy is capable of correcting for differences between characteristics of a predicted route and a route actually traveled. Our numerical results indicate that the fuel economy potential of the RHC solution can approach that of the DP solution.
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