基于双扩展卡尔曼滤波器的汽车轮胎侧向力与侧偏刚度估计

Estimation of Tyre Lateral Forces and Cornering Stiffness Based on Dual Extended Kalman Filter

轮胎力与轮胎侧偏刚度信息不易测量,一般利用观测器估计,而利用轮胎模型的侧向力估计精度依赖于参考模型精度,为此设计了双扩展卡尔曼滤波器,利用两个平行通道分别估计轮胎侧向力与侧偏刚度。侧偏刚度估计降低了对轮胎模型精度的依赖,有效保证了不同轮胎特性下的侧向力估计精度。在Carsim环境下的仿真结果表明,设计算法对不同轮胎配置能够快速准确地辨识侧偏刚度,并且均表现出很高的轮胎力估计精度。

The tyre forces and cornering stiffness can not be measured easily, which usually are estimated. The accuracy of lateral force estimation algorithm based on tyre models highly depends on the reference model accuracy. Hence this paper proposed an observer based on dual extended Kalman filter （DEKF）. Tyre lateral forces and corne- ring stiffness are observed by two parallel channels respectively. The cornering stiffness estimation reduces the dependence on tyre model accuracy, which can effectively ensure the lateral force estimation performance with respect to different tire characteristics. The simulation results in Carsim environment show that, the proposed observer can identify the cornering stiffness quickly, and also maintain high tyre force estimation accuracy with respect to different tyre configurations.