Robust eco-cooperative adaptive cruise control with gear shifting

Yunli Shao, Zongxuan Sun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

This research proposes a real-time implementable robust eco-cooperative adaptive cruise control (Eco-CACC) strategy with the consideration of gear shift. Vehicle acceleration is optimized in real-time to vary the vehicle power demand to improve the fuel efficiency. The effects of different gear ratios on the fuel consumption rate are explicitly considered during the optimization process. A robust optimization method is adopted to ensure the controller performance under traffic prediction uncertainties. Using this approach, the optimal solution is guaranteed to provide fuel savings and satisfy constraints at the same time for any actual traffic profile within the uncertainty set. The optimal control problem is discretized and solved using a nonlinear programming (NLP) solver for an 8-vehicle platoon scenario. The results show that the proposed controller can achieve 23.5% fuel saving with perfect traffic prediction, and 16.6% fuel saving with prediction uncertainties.

Original languageEnglish (US)
Title of host publication2017 American Control Conference, ACC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4958-4963
Number of pages6
ISBN (Electronic)9781509059928
DOIs
StatePublished - Jun 29 2017
Event2017 American Control Conference, ACC 2017 - Seattle, United States
Duration: May 24 2017May 26 2017

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619

Other

Other2017 American Control Conference, ACC 2017
CountryUnited States
CitySeattle
Period5/24/175/26/17

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