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.