Predictive energy management has become a new focus of the automobile industry for its high potential of further reducing energy consumption. Based on previous works on predictive speed optimization using discrete dynamic programming (DDP), this paper introduces a novel approach of applying DDP with variable step size in stage variable discretization, which can realize a better tradeoff between precision and computational cost. In this approach, a “meshing” algorithm searches the points of interest (POI), such as speed limit change, traffic lights, and road curvatures, where changes in vehicle speed are expected. The algorithm increases the step-size resolution close to these points and reduces the resolutions in positions further away from POI, where the optimized vehicle speed is insensitive to the step size. With this approach, the position of POI can be precisely located to solve the DDP problem. In a test case with a relatively high density of POI, the computational cost is reduced by more than 53% by only sacrificing less than 1% of precision compared to a fixed step-size discretization with high resolutions. It can be expected that, with a lower density of POI, the computational cost will be reduced even further.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Variable Step-Size Discrete Dynamic Programming for Vehicle Speed Trajectory Optimization


    Contributors:


    Publication date :

    2019-02-01


    Size :

    2824998 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Train energy-saving speed trajectory optimization method based on dynamic programming

    LU SHAOFENG / CHEN FUWANG / PENG YANG | European Patent Office | 2024

    Free access

    Predictive vehicle speed trajectory optimization

    Ye, Ziqi / Rheinisch-Westfälische Technische Hochschule Aachen | TIBKAT | 2019



    Dynamic Programming Trajectory Optimization by Piecewise Linear Approximation

    Harada, Akinori / Matsuda, Haruki / Miyazawa, Yoshikazu | AIAA | 2015