In this paper, a layered control algorithm for energy-efficient predictive cruise control (PCC) algorithm of commercial vehicles that can optimize engine torque and gear in real time is proposed. The predictive cruise upper layer controller constructs a quadratic programming (QP) problem incorporating forward road information to optimize the vehicle driving force in the Model Predictive Control (MPC) framework. The predictive cruise lower layer controller optimizes the gear by finding the offline optimized gear MAP based on the overall vehicle driving force and current vehicle speed obtained from the upper layer controller. The predictive cruise algorithm is validated under highway conditions with slope changes. Compared with the traditional cruise control (CC) algorithm, it can save more than 4% fuel, and can better balance fuel economy, time economy, and driving comfort compared with the PCC algorithm based on indirect method solving. As for its solution speed, it is only twice as fast as the indirect method, which can meet the demand of real-time control.


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    Title :

    Predictive Cruise Control Algorithm Design for Commercial Vehicle Energy Saving Based on Quadratic Programming


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Sun, Fengchun (editor) / Yang, Qingxin (editor) / Dahlquist, Erik (editor) / Xiong, Rui (editor) / Li, Xianning (author) / Lv, Tingting (author) / Yue, Hanqi (author) / Liu, Shuangping (author) / Na, Xiaoxiang (author) / Chen, Hong (author)

    Conference:

    International Conference on Energy Storage and Intelligent Vehicles ; 2022 December 03, 2022 - December 04, 2022



    Publication date :

    2023-05-11


    Size :

    13 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





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