The invention discloses a vehicle speed estimation method for a two-wheeled vehicle, and the method comprises the steps: obtaining a vehicle speed observation value at a current moment, and obtaining the longitudinal acceleration of a vehicle body in real time; obtaining a vehicle speed estimation value and a longitudinal acceleration estimation value at the previous moment and absolute values of the first difference value and the second difference value, and obtaining a prediction noise covariance matrix and an observation noise covariance matrix corresponding to the current moment by performing fuzzy logic reasoning on the absolute values; constructing a Kalman filtering equation based on the observation noise covariance matrix at the current moment, the longitudinal acceleration, the vehicle speed observation value and the prediction noise covariance matrix at the previous moment, and estimating a vehicle speed estimation value and a longitudinal acceleration estimation value at the current moment by using the Kalman filtering equation; according to the method, the vehicle speed estimation value and the longitudinal acceleration estimation value at the current moment are estimated by calculating the time-varying prediction noise covariance matrix and the observation noise covariance matrix, and the estimation accuracy is improved.

    本发明公开了一种用于两轮车的车速估计方法,其通过获取当前时刻下的车速观测值,并实时获取车身的纵向加速度;获取上一时刻的车速估计值与纵向加速度估计值以及第一差值与第二差值的绝对值,并通过对各绝对值进行模糊逻辑推理得到当前时刻对应的预测噪声协方差矩阵和观测噪声协方差矩阵,基于当前时刻下的观测噪声协方差矩阵、纵向加速度、车速观测值以及上一时刻的预测噪声协方差矩阵构建卡尔曼滤波方程,利用卡尔曼滤波方程估算当前时刻的车速估计值与纵向加速度估计值,即本发明通过计算出时变的预测噪声协方差矩阵和观测噪声协方差矩阵,估算当前时刻下的车速估计值与纵向加速度估计值,提高了估算的准确性。


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    Title :

    Vehicle speed estimation method for two-wheeled vehicle


    Additional title:

    一种用于两轮车的车速估计方法


    Contributors:
    XIA QINGCHAO (author) / YU YAWEN (author) / JIN BO (author) / SHAN DONGSHENG (author) / CHEN ZAN (author)

    Publication date :

    2024-03-08


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    IPC:    G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / B62J Fahrrad- oder Motorradsättel oder -sitze , CYCLE SADDLES OR SEATS / G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung



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