Gear shifting strategy of automatic transmission has an important impact on the fuel economy of vehicles. For plug-in hybrid electric commuting vehicles, to develop the driving cycle and working mode adaptive gear shifting strategy of automatic transmission is of great significance to improve the vehicle energy economy. Three main efforts have been made to distinguish our work from exiting research. First, based on the fixity and repeatability of the driving cycle for plug-in hybrid electric commuting vehicles, the typical driving cycle of plug-in hybrid electric commuting vehicle is constructed by the self-organized mapping and K-means clustering methods. Second, in the typical plug-in hybrid electric commuting vehicle driving cycle constructed herein, the working points with the best energy economy are calculated by improved dynamic programming for each working mode of the plug-in hybrid electric commuting vehicle, considering the working efficiency of the power components and transmission. On this basis, the optimal gear shifting strategy of automatic transmission for the plug-in hybrid electric commuting vehicle in each working mode is extracted. Third, the simulation tests are conducted which compare the formulated adaptive gear shifting strategies with the traditional engine fuel economy-based gear shifting strategy. The simulation results illustrate that the adaptive gear shifting strategies increase the energy economy by 3.32%. The proposed gear shifting strategy development method can provide a reference for further optimization of automatic transmission gear shifting strategies of plug-in hybrid electric commuting vehicle for real applications.


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    Titel :

    Development of adaptive gear shifting strategies of automatic transmission for plug-in hybrid electric commuting vehicle based on optimal energy economy


    Beteiligte:
    Shen, Peihong (Autor:in) / Zhao, Zhiguo (Autor:in) / Li, Jingwei (Autor:in) / Guo, Qiuyi (Autor:in)


    Erscheinungsdatum :

    2020-03-01


    Format / Umfang :

    15 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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