Real-time Tire-road Longitudinal Adhesion Estimation Based on Exponential Sum Linear Parameterization

Abstract

Abstract: The wheel dynamics modeling and FFRLS （forgetting factor recursive least-square） were utilized to develop a method of tire-road adhesion estimations in longitudinal braking conditions. The modeling object was an FWD （front wheel drive） EV（electric vehicle） equipped with an EHB（electro-hydraulic brake）. Firstly， a maximized regenerative brake distribution strategy was introduced. The regenerative brake wheels would tend to be locked before other wheels in heavy brake conditions. Secondly， a real-time adhesion estimation method was designed to lowering the risks of wheel locks. The linear parameterization of ES（exponential sum） was introduced to fit non-linear Burckhardt friction model， the on-line simulations and HiL（hardware-in-loop） tests were conducted. Results show that the proposed linear method may run in real-time， and has better estimation accuracy and convergence rate compared with linear Kiencke method.

Key words: adhesion estimation, exponential sum（ES）, optimal slip ratio, linear parameterization

摘要：

利用动力学建模和遗忘因子递推最小二乘算法，对电动汽车纵向制动工况中轮胎-路面附着特性的峰值点估计方法进行研究。以匹配电子液压制动系统的前驱电动汽车为建模对象，提出了一种最大化能量回收的制动分配策略；针对再生制动轮优先趋于抱死这一现象，设计了一种附着条件实时估计算法，以降低利用附着系数进入非线性区域的风险。利用指数和线性模型对非线性Burckhardt摩擦模型进行拟合，并进行了在线辨识的仿真和硬件在环试验，结果表明该算法满足实时性要求，且相较于Kiencke线性化方法，具有更佳的估计精度和收敛速度。

关键词: 附着条件估计, 指数和, 最优滑移率, 线性参数化

CLC Number:

U461.3

XIONG Zhe, GUO Xuexun, PEI Xiaofei, ZHANG Jie. Real-time Tire-road Longitudinal Adhesion Estimation Based on Exponential Sum Linear Parameterization[J]. China Mechanical Engineering.

熊喆, 过学迅, 裴晓飞, 张杰. [电动汽车稳定性控制]指数和线性参数化的轮胎-路面纵向附着条件实时估计方法[J]. 中国机械工程.

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