多采样率EKF软测量在汽车状态估计中的应用  

Application of multi-rate EKF soft computing in vehicle state estimation

作　　者：周聪[1] 肖建[1] 盛瀚民[1] 

机构地区：[1]西南交通大学电气工程学院,成都610031

出　　处：《电子测量与仪器学报》2012年第2期132-137,共6页Journal of Electronic Measurement and Instrumentation

基　　金：国家自然科学基金(编号:51177137;61134001)资助项目

摘　　要：由于多采样率数字控制系统具有许多单采样率数字控制系统所不具备的优点，在深入研究多采样率数字控制系统和EKF算法的基础上，提出一种基于输入多采样率EKF的软测量算法，并将其应用于汽车的横摆角速度、质心侧偏角和纵向车速的估计。通过Carsim和Matlab／Simulinkl联合仿真与蒙特卡罗实验，结果表明该算法有利于获取更多的输入量信息，提高状态估计器的性能，比单采样率EKF算法的估计精度高10％～40％。Since multi-rate digital control system has more advantages than single rate digital control system, based on an analysis on multi-rate digital control systems and EKF algorithm, an input multi-rate extended Kalman filter （IMREKF） is proposed and applied to estimate yaw rate, slip angle and longitudinal velocity in vehicle＇s running. Co-simulation and Monte Carlo experiment are carried out based on Carsim and Matlab/Simulink. The results prove that IMREKF improves the ability of state estimator and input information acquirement, which has increased 10% to 41% in estimation accuracy than single rate EKF algorithm.

关 键 词：汽车动力学 软测量 状态估计 多采样率数字控制系统 卡尔曼滤波器 

分 类 号：U461.6[机械工程—车辆工程] TP273.2[交通运输工程—载运工具运用工程]