作　　者： (刘进）; (赵熙俊）;

机构地区： 中国北方车辆研究所,北京100072

出　　处： 《车辆与动力技术》 2017年第3期1-7,共7页

摘　　要： 采用非线性三自由度单轨模型和考虑轮胎侧偏特性的非稳态轮胎模型,建立了用于状态估计的非线性状态方程.结合自主车辆的现有传感器配置,梳理了横向运动状态的观测(输入)和估计(输出).基于扩展卡尔曼滤波提出了横向运动状态估计的方法,开发了状态估计算法,实现了基于MATLAB/Simulink的离线状态估计平台.最后,通过对典型工况的仿真模拟以及对样车数据的离线回放验证了算法性能.试验结果表明算法能够合理、有效、准确地估计自主车辆行驶过程中的横摆角速度、横向速度、横向加速度、路面附着系数等横向运动状态,对车辆质量、转动惯量、路面附着系数的变化具有较好的鲁棒性. A state estimation of autonomous vehicle＇ s lateral dynamics using extended kalman filter is presented,which adopted single-track 3 DOF non-linear vehicle model,as well as non-steady tire dynamic model. Based on the sensor configuration of common autonomous vehicles,measured and estimated states are determined exactly. Due to non-linear model behavior,the extended kalman filter is utilized for state estimation and an off-line state estimator based on MATLAB/Simulink is implemented.The performance of the proposed method is analyzed with simulation scenarios and real data replay. The experimental results show that the proposed method has good performance and is robust to key parameters of lateral dynamics.

关 键 词： 自主驾驶车辆 横向运动状态 状态估计 扩展卡尔曼滤波