考虑未知输入的主动悬架路面高程与等级识别研究

doi:10.19562/j.chinasae.qcgc.2021.02.017

Abstract

Abstract:

The basic premise of improving the ride comfort and driving safety of vehicles via the precise control of active suspension is road elevation and grade identification. In this paper， a Kalman observer considering unknown inputs is designed to obtain the road elevation information. The AR model is established to acquire the road power spectral density， and the root mean square value of the road power spectral density in the interest frequency band is computed to realize the road grade classification. The accuracy of road elevation estimation and road grade classification under different working conditions is analyzed by simulation. Finally， the test bench is built to verify the effectiveness of the proposed road elevation estimation and road grade classification method， which provides necessary conditions for the intelligent control of active suspension.

Key words: active suspension, unknown inputs, Kalman observer, road elevation estimation, road grade classification

Renkai Ding,Yu Jiang,Ruochen Wang,Wei Liu,Xiangpeng Meng,Zeyu Sun. Research on Road Elevation and Grade Identification of Active Suspension Considering Unknown Inputs[J].Automotive Engineering, 2021, 43(2): 278-286.

Figures/Tables 18

参数	数值
簧上质量 $m s$	317.5 kg
簧下质量 $m t$	45.4 kg
弹簧刚度 $k s$	20 000 N/m
轮胎刚度 $k t$	192 000 N/m

References 21

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工况	时间/s	路面等级	车速/ (m·s^-1)	天棚阻尼系数/（N·s·m^-1）	被动阻尼系数/ （N·s·m^-1）
工况一	0-10	B	30	1 262	2 050
	10-20	B	25	1 262	2 050
	20-30	B	20	1 262	2 050
工况二	0-10	B	20	1 262	2 050
	10-20	B	20	2 993	1 293
	20-30	B	20	1 610	1 092
工况三	0-10	B	30	1 262	2 050
	10-20	D	5	1 610	1 092
	20-30	C	15	2 993	1 293

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Research on Road Elevation and Grade Identification of Active Suspension Considering Unknown Inputs

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