Eco-Coasting Strategies Using Road Grade Preview: Evaluation and Online Implementation Based on Mixed Integer Model Predictive Control
Yongjun Yan, Nan Li, Jinlong Hong, Bingzhao Gao, Hong Chen, Jing Sun,, and Ziyou Song

TL;DR
This paper compares two eco-coasting strategies, fuel cut-off and engine start/stop, using road grade preview, and evaluates their offline and online performance with a novel MIMPC approach to reduce fuel consumption.
Contribution
It introduces a mixed integer model predictive control framework with a new constraint to effectively implement eco-coasting strategies online.
Findings
Engine start/stop outperforms fuel cut-off offline in fuel savings and travel time.
MIMPC reduces fuel consumption effectively without increasing travel time.
The proposed MIMPC approach ensures stable online implementation of eco-coasting strategies.
Abstract
Coasting has been widely used in the eco-driving guidelines to reduce fuel consumption by profiting from kinetic energy. However, the comprehensive comparison between different coasting strategies and online performance of the eco-coasting strategy using road grade preview are still unclear because of the oversimplification and the integer variable in the optimal control problems. Herein, two different coasting strategies (fuel cut-off and engine start/stop) are proposed to reveal the potential benefit of eco-coasting using the road grade preview. Engine drag torque and energy cost used for engine restart are considered in the modeling to give a fair evaluation of the offline and online performance. The offline performance of these two coasting methods is evaluated through dynamic programming (DP) under various driving scenarios with different slope profiles. Offline simulation shows…
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Taxonomy
TopicsVehicle emissions and performance · Advanced Combustion Engine Technologies · Electric and Hybrid Vehicle Technologies
MethodsEmirates Airlines Office in Dubai
