基于集合卡尔曼滤波的高机动救援车辆主动悬挂控制方法

doi:10.13229/j.cnki.jdxbgxb20211448

Abstract

Abstract:

A control strategy of active suspension systems was proposed for high-mobility rescue vehicles—model predictive control strategy based on ensemble Kalman Filter technology（EnKF-MPC）. Firstly， dynamic model of the active suspension system was completed for high-mobility rescue vehicles. The data of the vehicle dynamic system and the vehicle-mounted positioning system were fused through the Ensemble Kalman Filter technology in order to realize the accurate estimation of the vehicle's pose information； Aiming at the problem of vertical positioning error for the vehicle positioning system， a point cloud matching algorithm was designed to complete the accurate evaluation of the vehicle's vertical direction information； in addition， a model predictive control strategy was proposed， which used the vehicle's pose information obtained by the ensemble Kalman filter algorithm and the road profile information obtained by the on-board lidar as system inputs to control the active suspension system of the vehicle to improve the ride comfort and handling stability of the vehicle. Finally， a real vehicle test was carried out. The research results show that the vertical direction error of the proposed vehicle pose estimation algorithm is about $± 3.100 ? c m$ ， the pitch angle error is about ±0.175°， and the roll angle error is about ±0.210°. Compared with the passive suspension system， the proposed active suspension control method reduced the root mean square value of the vertical displacement by 37%， the pitch angle by 35%， and the roll angle by 35%， which significantly improved the ride comfort and handling stability of the vehicle.

Key words: road transportation, active suspension system, ensemble Kalman filter, model predictive control

CLC Number:

TP273

Wen-hang LI,Tao NI,Ding-xuan ZHAO,Pan-hong ZHANG,Xiao-bo SHI. Active suspension control method of high mobility rescue vehicle based on ensemble Kalman filter[J].Journal of Jilin University(Engineering and Technology Edition), 2022, 52(12): 2816-2826.

Figures/Tables 10

Fig.1

Fig.2

Fig.3

Table 1

Vehicle parameters"

符号	含义	数值	单位
$M$	车身质量	3.6×10⁴	kg
$T$	轮胎的宽度	0.4	m
$H$	车体中心高度	2.1	m
$V$	平均行驶速度	5.00	km/h
$J Y$	Y轴转动惯量	2.46×10⁵	kg·m²
$J X$	X轴转动惯量	1.12×10⁵	kg·m²
$K m i$	轮胎刚度系数	1.90×10⁶	N/m

Table 1

Fig.4

Fig.5

Table 2

Fig.6

Fig.7

Table 3

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路面类型	参数	未融合	EnKF
图4（b）	垂向误差/cm	4.300	2.950
	俯仰角误差/（°）	0.195	0.155
	侧倾角误差/（°）	0.216	0.190
图4（c）	垂向误差/cm	4.630	3.100
	俯仰角误差/（°）	0.216	0.175
	侧倾角误差/（°）	0.253	0.210

路面类型	参数	PAS	MPC	EnKF-MPC
图4（c）	垂向/m	0.0535	0.0417	0.0338
	俯仰角/（°）	0.5500	0.4235	0.3575
	侧倾角/（°）	0.2650	0.1988	0.1722

Active suspension control method of high mobility rescue vehicle based on ensemble Kalman filter

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