车辆系统垂向与横向耦合的侧倾状态估计

为有效解决复杂行驶工况下车辆耦合侧倾运动状态无法精确获取,进而对车辆系统操纵稳定性与乘坐舒适性兼顾优化无法提供准确输入的难题,本文中设计了基于车辆垂向与横向耦合动力学的双非线性状态观测器算法,以实现复杂行驶工况下车辆耦合侧倾运动状态的实时准确估计。首先,建立了路面激励模型与整车系统垂向与横向耦合动力学模型;接着,利用无迹卡尔曼滤波方法(UKF)与非线性模糊观测(T-S)理论,设计了非线性状态观测算法,以在不同路面激励工况下对车辆系统簧载质量与侧倾状态进行联合估计;最后,运用CarSim■动力学软件,对比分析了在标准A级与C级路面上进行J-turn试验工况下,采用联合状态观测器(UKF&T-S)实时估计车辆侧倾角与侧倾率的观测精度。结果表明,本文所设计的UKF&T-S观测器可有效估计车辆侧倾状态,且与CarSim■仿真数据相比识别状态标准偏差不超过10%。

Vertical and Lateral Coupling Roll State Estimation of Vehicle System

To effectively solve the problem that the coupling roll motion state of vehicle cannot be accurately obtained under complicated driving conditions and the difficulty in providing accurate input for the concurrent optimization of vehicle handling stability and ride comfort,a dual nonlinear state observer algorithm based on vehicle vertical and lateral coupling dynamics is designed to achieve real time accurate estimation of vehicle coupling roll motion state under complicated driving conditions.Firstly,the road excitation model and vehicle vertical and lateral coupling dynamics model are established.Then by utilizing the unscented Kalman filtering(UKF)technique and the nonlinear fuzzy observation(T-S)theory,a nonlinear state observation algorithm is designed and a joint-estimation on the sprung mass and rolling state of vehicle system is conducted under different road excitation conditions.Finally,by applying dynamics software CarSim■,the observation accuracies of vehicle roll angle and rolling rate real time estimated by joint state observer UKF&T-S on standard A-and C-grade roads are comparatively analyzed under J-turn test conditions.The results show that the UKF&T-S observer designed can effectively estimate the roll state of vehicle,with a less than 10%standard deviation of identified state,compared with the CarSim■ simulation data.