The invention provides a feedforward self-learning method, which can effectively solve the modeling error caused by simplifying a four-wheel automobile model into a two-wheel bicycle model, and can reduce the research and development cost of a system. Modeling errors caused by the fact that a four-wheel automobile model is simplified into a two-wheel bicycle model are corrected by introducing a feedforward model correction coefficient Kff, and when an automobile runs actually, a corrected feedforward angle plan theta FF is used for replacing theta FFbasic to serve as a steering angle calculation basis of a steering wheel. Meanwhile, the invention further discloses an LCC control method based on feedforward self-learning.

    本发明提供一种前馈自学习方法,其可以有效的解决由于四轮汽车模型简化为二轮自行车模型带来的建模误差,且可以降低系统研发成本。其通过引入前馈模型修正系数Kff来修正由于四轮汽车模型简化为二轮自行车模型带来的建模误差,车辆实际运行时使用修公正后的前馈角度规划θFF替代θFFbasic作为方向盘的转向角计算基础。同时本申请还公开一种基于前馈自学习实现的LCC控制方法。


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    Titel :

    Feed-forward self-learning method and LCC control method based on feed-forward self-learning


    Weitere Titelangaben:

    一种前馈自学习方法及基于前馈自学习实现的LCC控制方法


    Beteiligte:
    LONG YANG (Autor:in) / KONG GUOLING (Autor:in)

    Erscheinungsdatum :

    2024-03-22


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Chinesisch


    Klassifikation :

    IPC:    G05B Steuer- oder Regelsysteme allgemein , CONTROL OR REGULATING SYSTEMS IN GENERAL / B60W CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION , Gemeinsame Steuerung oder Regelung von Fahrzeug-Unteraggregaten verschiedenen Typs oder verschiedener Funktion



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