The invention relates to a road adhesion coefficient estimation method, device and equipment and a medium, and the method comprises the steps: constructing an adaptive robust three-order volume Kalman filter and an adaptive robust five-order volume Kalman filter based on a vehicle dynamics model, inputting the tire force into a self-adaptive robust three-order volume Kalman filter and a self-adaptive robust five-order volume Kalman filter respectively to determine a first road adhesion coefficient and a second road adhesion coefficient; iteratively updating the noise covariance and the error covariance in the measurement stage, and determining a first priori error corresponding to an adaptive robust third-order volume Kalman filter and a second priori error corresponding to an adaptive robust fifth-order volume Kalman filter; and detecting whether the first priori error exceeds a second priori error, and if so, outputting the second road adhesion coefficient as the road adhesion coefficient of the intelligent electric vehicle. The precision and efficiency of road adhesion coefficient estimation can be remarkably improved.
本申请涉及一种路面附着系数估计方法、装置、设备及介质,方法包括:基于车辆动力学模型构建自适应鲁棒三阶容积卡尔曼滤波器以及自适应鲁棒五阶容积卡尔曼滤波器,并将轮胎力分别输入至自适应鲁棒三阶容积卡尔曼滤波器以及自适应鲁棒五阶容积卡尔曼滤波器中,以确定第一路面附着系数以及第二路面附着系数;对测量阶段的噪声协方差以及误差协方差进行迭代更新,确定自适应鲁棒三阶容积卡尔曼滤波器相对应的第一先验误差以及自适应鲁棒五阶容积卡尔曼滤波器相对应的第二先验误差;检测第一先验误差是否超过第二先验误差,若超过,将第二路面附着系数作为智能电动汽车路面附着系数输出。本申请能够显著提高路面附着系数估计的精度和效率。
Road adhesion coefficient estimation method, device, equipment and medium
路面附着系数估计方法、装置、设备及介质
2024-06-07
Patent
Electronic Resource
Chinese
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