Matlab基于软测量技术的汽车行驶状态估计
关键词 ： 状态估计；Kalman 滤波；软测量；Carsim；二自由度
Title Vehicle state estimation based on soft computing
Abstract
It is very important for gathering status of cars accurately and real-time. However, since
some problem ,such as the technology, cost and noise, many car status parameters
cannot be measured directly, effectively and easily,which has caused great difficulties
for vehicle safety control. This paper realized using soft measurement and KF theory,
combined with the car two degrees of freedom model cars with state estimation. First,
using analysis ,establish the general dynamics model and appropriately simplified
2-DOF vehicle model and program verification; Then, select the more complex double
shift lane lines in Carsim, the simulation experiments using real vehicle parameters
preparing for the next verification of filtering algorithm; Finally, based on state
estimation and KF filtering combined soft computing, build car model. In the Matlab
environment, use the input signal and the observed signal from Carsim to validate
filtering algorithm, and compare with actual output value from Carsim and the
filtered estimates. KF algorithm satisfies the requirements of the estimator of Vehicle
driving state.
Keywords :state estimation; Kalman filters; soft computing; Carsim; two
degrees-of-freedom
目 次
1 引言 1
1.1 课题研究的提出及意义 1
1.2 软测量技术 2
1.2.1 软测量技术产生的背景 2
1.2.2 软测量技术简介 2
1.2.3 国内外研究现状 3
1.2.4 软测量技术的应用 4
1.3 汽车行驶状态估计 5
1.4 研究内容和方法 6
2 整车动力学建模 7
2.1 线性二自由度汽车动力学模型 8
2.2 模型验证 10
2.2.1 整车参数 11
2.2.2 模型仿真 12
2.3 本章小结 15
3 Carsim 仿真实验 . 16
3.1 Carsim 软件介绍 . 16
3.2 双移线试验 16
3.3 本章小结 18
4 基于软测量技术的汽车行驶状态估计 19
4.1 状态估计 19
4.2 Kalman 滤波 19
4.2.1 Kalman 简介 20
4.2.2 经典 Kalman 滤波算法 . 21
4.3 软测量模型 23
4.4 试验验证 24
4.4.1 有无噪声对结果的影响 24
上一篇：2D 激光传感器位移测量及其应用