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Eco-Coasting Controller Using Road Grade Preview: Evaluation and Online Implementation Based on Mixed Integer Model Predictive Control

delete2023-10-01
delete16
PRE
AI
Y
Yongjun Yan
N
Nan Li
洪金龙 (Jinlong Hong) *
高炳钊 (Bingzhao Gao)
J
Jia Zhang
陈宏 cover
陈宏 (Hong Chen)
孙婧 cover
孙婧 (Jing Sun)
Z
Ziyou Song *
DOI:10.1109/TVT.2023.3271656delete
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Abstract

Abstract

En 中文
Coasting is a common method used in eco-driving to reduce fuel consumption by utilizing kinetic energy. However, in order to avoid excessive computation induced by integer coasting maneuvers, the powertrain model used in eco-driving controllers that rely on look-ahead road information has been oversimplified. This oversimplification assumes that the engine goes to idle when coasting, which significantly limits the fuel-saving potential. To address this issue, we propose an eco-coasting strategy that calculates the optimal timing and duration of coasting maneuvers using road information preview. Different from the engine-idling method, two control-oriented coasting methods, fuel cut-off method and engine start/stop method are formulated for the model-based optimal control. To evaluate and choose the best coasting mechanism for eco-coasting strategy, dynamic programming (DP) is performed to provide the globally optimal performance (i.e., benchmark results) for evaluating the engine-idling method, fuel cut-off method, and engine start/stop method. Based on the offline simulation results, the engine start/stop method consistently outperforms the fuel cut-off method in terms of both fuel consumption and travel time. This is attributed to the engine start/stop method eliminating the engine drag torque during deceleration, despite the additional energy cost required for engine restart being taken into account in the modeling, thus providing a fair evaluation. Then, the online performance of the eco-coasting strategy with engine start/stop mechanism is evaluated using Mixed Integer Model Predictive Control (MIMPC). We propose a tailored mixed-integer programming algorithm to facilitate online implementation. Simulation results show that the proposed eco-coasting strategy achieves near-optimal performance compared to DP and outperforms the rule-based method.
Keywords:
Eco-coasting strategy
Engine start/stop mechanism
Mixed-integer model predictive control

Journal

IEEE Transactions on Vehicular Technology cover
IEEE Transactions on Vehicular Technology
IF:
7.1
Papers:
1.8W
Citations:
6.6W

Organization

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Auburn University
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B
beijing institute of technology
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5.5W
Papers: 4.0W
Citations: 63
T
tongji university
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Papers: 5.9W
Citations: 98
A
auburn university system
Scholars:
1.1W
Papers: 9.5K
Citations: 9
J
Jilin University
Scholars:
8.7W
Papers: 5.5W
Citations: 8.9K
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