Estimation of the tire slip angle under various road conditions without tire-road information for vehicle stability control
Estimation of the tire slip angle under various road conditions without tire-road information for vehicle stability control
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DOI：
10.1016/j.conengprac.2019.03.005
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发表时间：
2019-05-01
影响因子：
4.9
通讯作者：
Hyun, Youngjin
中科院分区：
文献类型：
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作者：
Joa, Eunhyek;Yi, Kyongsu;Hyun, Youngjin
本文提出了一种基于交互式多模型（IMM）算法的汽车稳定性控制轮胎侧偏角估计器。该算法能够估计轮胎侧偏角在不同的道路条件下，没有轮胎和道路条件的先验知识，仅使用车载传感器。该算法不使用轮胎和道路信息，而是利用多个候选模型来表示各种道路条件下车辆运动的各个方面。每个候选模型是横向车辆动力学和瞬态/稳态轮胎动力学的组合。该算法以概率评估每个候选模型对当前车辆动力学的保真度。此外，在所提出的算法中，多个卡尔曼滤波器被嵌入这些模型候选者作为过程模型。该算法在每个时间步的最终估计是多个嵌入式滤波器的后验状态的线性和与计算的概率作为系数。所提出的估计算法已通过车辆测试进行评估。测试已经进行了干沥青和湿沥青使用豪华轿车配备了高性能的GPS作为参考和数据记录计算机。结果表明，在各种路面条件下，该估计器都能成功地估计出轮胎侧偏角，并具有令人满意的精度
This paper presents a tire slip angle estimator based on an Interacting Multiple Model (IMM) algorithm for vehicle stability control. The proposed algorithm is capable of estimating the tire slip angles under various road conditions without the prior knowledge of tire and road condition by only using on-board vehicle sensors. Instead of employing tire and road information, the proposed algorithm utilizes multiple numbers of model candidates to represent all aspects of vehicle motions under various road conditions. Each model candidate is a combination of lateral vehicle dynamics and transient/steady state tire dynamics. The proposed algorithm evaluates the fidelity of each model candidate to the current vehicle dynamics with probability. Moreover, in the proposed algorithm, multiple numbers of Kalman filters are embedded with these model candidates as process models. The final estimate of the proposed algorithm in each time step is a linear sum of the posteriori states from multiple embedded filters with the calculated probability as coefficients. The proposed estimation algorithm has been evaluated via vehicle tests. The tests have been conducted on dry asphalt and wet asphalt using a luxury passenger car equipped with a high-performance GPS for reference and data logging computer. The results have shown that the proposed estimator can successfully estimate tire slip angles with satisfactory accuracy under various road conditions