Accurate estimation of road peak adhesion coefficient is of great significance in vehicle active safety systems. In order to prevent the vehicle from running out of control in actual driving process, the estimation algorithm should be able to adapt to various working conditions, and transmit estimated information of road peak adhesion coefficient to Electronic Control Unit (ECU) of the vehicle timely and accurately. Therefore, a new preprocessment method for the fusion estimation algorithm of road adhesion coefficient is proposed. The core of this method is the equal ratio relationship between the longitudinal, lateral peak adhesion coefficients and the utilization adhesion coefficient under adjacent typical roads. According to this relationship, this method accomplishes normalization of the tyre model in the form of introducing parameters from the outside, so that the tyre model can be combined with the filtering algorithm to be applied to estimation, which solves the problem that the precise tyre model cannot be used for road adhesion coefficient estimation due to its complex construction. This method can adapt to most of tyre models in the field of vehicle dynamics. In addition, the existing estimation algorithms need sufficient excitation (when the comprehensive slip ratio is 0.15–0.20) to estimate the accurate road peak adhesion coefficient. This method can greatly reduce the system error caused by insufficient road excitation, and can also obtain accurate estimation results when the excitation is insufficient. Finally, in order to verify the preprocessment method, the magic formula tyre model is used to describe the tyre characteristics. After processing by the preprocessment method, the road peak adhesion coefficient is estimated in combination with Unscented Kalman Filter (UKF). The high accuracy and timeliness of the estimated results in simulation and real vehicle tests verify the effectiveness of the preprocessment method.

道路峰值附着系数的准确估计在车辆主动安全系统中具有重要意义。为防止车辆在实际行驶过程中出现失控，估计算法应能适应各种工况，及时将路面峰值附着系数估计信息传递给车辆的电子控制单元（ECU）。准确。为此，提出了一种道路附着系数融合估计算法的预处理方法。该方法的核心是相邻典型道路下纵向、横向峰值附着系数与利用附着系数的等比关系。根据这种关系，该方法通过从外部引入参数的形式完成轮胎模型的归一化，从而可以将轮胎模型与滤波算法相结合进行估计，解决了精确轮胎模型不能用于道路的问题。由于其复杂的结构，粘附系数估计。该方法可以适应车辆动力学领域的大部分轮胎模型。此外，现有的估计算法需要足够的激励（当综合滑移率为0.15-0.20时）来估计准确的道路峰值附着系数。这种方法可以大大降低道路激励不足引起的系统误差，在激励不足时也能得到准确的估计结果。最后，为了验证预处理方法，神奇公式轮胎模型用于描述轮胎特性。通过预处理方法处理后，结合无迹卡尔曼滤波器（UKF）估计道路峰值附着系数。估计结果在仿真和实车测试中的高精度和及时性验证了预处理方法的有效性。