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

作　　者：Hongqing Chu Xiaoxiang Na Huan Liu Yuhai Wang Zhuo Yang Lin Zhang Hong Chen 

机构地区：[1]School of Automotive Studies,Tongji University,Shanghai,China [2]Department of Engineering,University of Cambridge,Cambridge,UK [3]State Key Laboratory of Automotive Simulation and Control,Jilin University,Changchun,China [4]Qingdao Automotive Research Institute,Jilin University,Qingdao,China [5]Dongfeng Commercial Vehicle Technology Center,Dongfeng Motor Corporation,Wuhan,China

出　　处：《Chinese Journal of Mechanical Engineering》2024年第2期294-317,共24页中国机械工程学报（英文版）

基　　金：Supported by International Technology Cooperation Program of Science and Technology Commission of Shanghai Municipality of China(Grant No.21160710600);National Nature Science Foundation of China(Grant No.52372393);Shanghai Pujiang Program of China(Grant No.21PJD075).

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 algorithm achieves a fuel-saving rate of 7.9%without compromising the truck’s travel time.

关 键 词：Heavy-duty truck Predictive cruise control Model predictive control Pontryagin’s maximum principle Real-truck implementation 

分 类 号：U463.6[机械工程—车辆工程]