In order to improve the vibration isolation performance of the powertrain five point mounting system of parallel hybrid electric vehicle, the dynamic model of the powertrain five point mounting system is established. The optimization objective is to decouple the six degree of freedom energy of the powertrain and distribute the natural frequency reasonably. The stiffness of the five mounting points is the design variable. The genetic algorithm is used to optimize the mounting system. The suspension system of a parallel diesel electric hybrid vehicle is optimized by the above method. The results of dynamic simulation and real vehicle test show that the steering wheel jitter is eliminated after the suspension optimization, which verifies the rationality of the proposed method. At the same time, the genetic algorithm overcomes the shortcoming that SQP is easy to converge to the local optimal solution. The decoupling performance of the suspension system is excellent, and the optimization result is stable and reliable.


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    Titel :

    Decoupling Optimization of Vehicle Powertrain Mounting System Based on Genetic Algorithm


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Hung, Jason C. (Herausgeber:in) / Yen, Neil Y. (Herausgeber:in) / Chang, Jia-Wei (Herausgeber:in) / Zhu, Hongbo (Autor:in)

    Kongress:

    International Conference on Frontier Computing ; 2021 ; Seoul, Korea (Republic of) July 13, 2021 - July 17, 2021


    Erschienen in:

    Frontier Computing ; Kapitel : 191 ; 1335-1341


    Erscheinungsdatum :

    23.05.2022


    Format / Umfang :

    7 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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