Real-Time Co-optimization of Gear Shifting and Engine Torque for Predictive Cruise Control of Heavy-Duty Trucks

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外文摘要：Fuel consumption is one of the main concerns for heavy-duty trucks.Predictive cruise control(PCC)provides an intriguing opportunity to reduce fuel consumption by using the upcoming road information.In this study,a real-time implementable PCC,which simultaneously optimizes engine torque and gear shifting,is proposed for heavy-duty trucks.To minimize fuel consumption,the problem of the PCC is formulated as a nonlinear model predictive control(MPC),in which the upcoming road elevation information is used.Finding the solution of the nonlinear MPC is time consuming;thus,a real-time implementable solver is developed based on Pontryagin's maximum principle and indirect shooting method.Dynamic programming(DP)algorithm,as a global optimization algorithm,is used as a performance benchmark for the proposed solver.Simulation,hardware-in-the-loop and real-truck experiments are conducted to verify the performance of the proposed controller.The results demonstrate that the MPC-based solution performs nearly as well as the DP-based solution,with less than 1％deviation for testing roads.Moreover,the proposed co-optimization controller is implementable in a real-truck,and the proposed MPC-based PCC algo-rithm achieves a fuel-saving rate of 7.9％without compromising the truck's travel time.

外文关键词：

Heavy-duty truckPredictive cruise controlModel predictive controlPontryagin's maximum principleReal-truck implementation

作者：

Hongqing Chu、Xiaoxiang Na、Huan Liu、Yuhai Wang、Zhuo Yang、Lin Zhang、Hong Chen

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作者单位：

School of Automotive Studies,Tongji University,Shanghai,China

Department of Engineering,University of Cambridge,Cambridge,UK

State Key Laboratory of Automotive Simulation and Control,Jilin University,Changchun,China

Qingdao Automotive Research Institute,Jilin University,Qingdao,China

Dongfeng Commercial Vehicle Technology Center,Dongfeng Motor Corporation,Wuhan,China

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基金：

International Technology Cooperation Program of Science and Technology Commission of Shanghai Municipality of China国家自然科学基金Shanghai Pujiang Program of China

项目编号：

211607106005237239321PJD075

出版年：

2024

DOI：

10.1186/s10033-024-01015-7

中国机械工程学报

中国机械工程学会

中国机械工程学报

CSTPCD

影响因子：0.765

ISSN：1000-9345

年,卷(期)：2024.37(2)