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针对汽车纵向安全辅助系统道路自适应的要求,提出了一种道路纵向附着系数估计方法.该方法能够同时适应高滑移率和低滑移率工况.首先基于简化魔术轮胎模型,利用递归最小二乘方法实时初步估计出纵向附着系数,然后将所估计出的附着系数与轮胎模型参数作为扩充状态,利用扩展卡尔曼滤波算法,滤除信号噪声,实现轮胎模型系数的自适应调整,最终实时获取准确的道路纵向附着系数估计,并通过车辆动力学软件Carsim仿真验证了算法的有效性和可行性.结果表明该算法优于传统算法,在高滑移率和低滑移率工况下都能够快速、准确地估计出道路附着系数,误差小于0.1,响应时间小于1 s,满足车辆纵向安全辅助系统的需要.
In order to meet the requirements of road safety of vehicle longitudinal safety auxiliary system, a longitudinal road adhesion coefficient estimation method is proposed, which can adapt to both high slip rate and low slip rate.Firstly, based on the simplified magic tire model, The longitudinal adhesion coefficient was estimated by real-time two-way method. Then, the estimated adhesion coefficient and tire model parameters were used as the expansion state. The extended Kalman filter algorithm was used to filter the signal noise to adjust the tire model coefficients adaptively. Finally, Obtaining accurate longitudinal longitudinal adhesion coefficient estimation and validating the feasibility and feasibility of the algorithm through the vehicle dynamics software Carsim simulation results show that the algorithm is superior to the traditional algorithm, both in the high slip rate and low slip rate conditions It can quickly and accurately estimate the road adhesion coefficient, the error is less than 0.1, and the response time is less than 1 s, which meets the needs of longitudinal safety support system.