Vehicle attitude compensation control of magneto-rheological semi-active suspension based on state observer

被引：20

作者：

Wang, Ruochen ^{[1
]}

Sheng, Fupeng ^{[1
]}

Ding, Renkai ^{[1
]}

Meng, Xiangpeng ^{[1
]}

Sun, Zeyun ^{[1
]}

机构：

[1] Jiangsu Univ, Sch Automot & Traff Engn, 301 Xuefu Rd, Zhenjiang 212013, Jiangsu, Peoples R China

来源：

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING | 2021年 / 235卷 / 14期

基金：

中国国家自然科学基金;

关键词：

Attitude compensation control; magneto-rheological dampers; ride comfort; state observer; NEURAL-NETWORK; SYSTEM; DAMPERS; MODEL;

D O I：

10.1177/09544070211020897

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

This paper presents a vehicle attitude compensation algorithm based on state observer for vehicle semi-active suspension system equipped with four magneto-rheological dampers (MR dampers). The proposed algorithm including magneto-rheological damper control algorithm, attitude compensation control algorithm, and design method of state observer is to effectively improve ride comfort and control vehicle body attitude. First, the actual equivalent damping of magneto-rheological damper is introduced into state observer, and the parameter matrix of suspension system is updated in real time via precise discretization method to enhance the estimation accuracy of state observer. Then, the velocity signal estimated by state observer is employed as the evidence to realize attitude compensation control for vehicle body. Finally, relevant co-simulations and hardware-in-the-loop test are conducted to verify the validity of the proposed control algorithm. Results of simulations and tests demonstrate that the application of the control algorithm proposed in this paper can significantly improve ride comfort of magneto-rheological suspension and optimize vehicle body attitude.

引用

页码：3299 / 3313

页数：15

共 34 条

[1] Fuzzy logic with a novel advanced firefly algorithm and sensitivity analysis for semi-active suspension system using magneto-rheological damper [J].

Ab Talib, Mat Hussin ;

Darus, Intan Zaurah Mat ;

Samin, Pakharuddin Mohd .

JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 2019, 10 (08) :3263-3278

[2] Integrated Vehicle Dynamics System through Coordinating Active Aerodynamics Control, Active Rear Steering, Torque Vectoring and Hydraulically Interconnected Suspension [J].

Ahangarnejad, Arash Hosseinian ;

Melzi, Stefano ;

Ahmadian, Mehdi .

INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY, 2019, 20 (05) :903-915

[3] A stepper motor-driven semi-active variable damper - Part 1: Stepper motor positioning control and performance [J].

Akutain, X. Carrera ;

Carballo, J.M. ;

Savall, J. ;

Viñolas, J. .

International Journal of Vehicle Autonomous Systems, 2005, 3 (2-4) :152-175

[4]

Angelov I, IOP C SERIES MAT SCI, V618

[5] Experimental forward and inverse modelling of magnetorheological dampers using an optimal Takagi-Sugeno-Kang fuzzy scheme [J].

Askari, Mohsen ;

Li, Jianchun ;

Samali, Bijan ;

Gu, Xiaoyu .

JOURNAL OF INTELLIGENT MATERIAL SYSTEMS AND STRUCTURES, 2016, 27 (07) :904-914

[6]

Badam Anjani Prasad Reddy, 2016, Romanian Journal of Automotive Engineering, V22, P5

[7] Experimental calibration of forward and inverse neural networks for rotary type magnetorheological damper [J].

Bhowmik, Subrata ;

Weber, Felix ;

Hogsberg, Jan .

STRUCTURAL ENGINEERING AND MECHANICS, 2013, 46 (05) :673-693

[8]

Boubezoul A, 2017, VEHICLE SYST DYN, V56, P1

[9]

de Wet GJ, 2008, INT J VEHICLE DES, V47, P118

[10] LQR-UKF active comfort control of passenger vehicles with uncertain dynamics [J].

Dertimanis, Vasilis K. ;

Chatzi, Eleni N. .

IFAC PAPERSONLINE, 2018, 51 (15) :120-125

← 1 2 3 4 →