Suspension semi-active control of vehicles based on road profile classification

Ye Chen Qin; Ming Ming Dong; Feng Zhao; Liang Gu

doi:10.3969/j.issn.1005-3026.2016.08.016

Suspension semi-active control of vehicles based on road profile classification

Ye Chen Qin, Ming Ming Dong, Feng Zhao, Liang Gu^*

^*Corresponding author for this work

School of Mechanical Engineering

Beijing Institute of Technology

Research output: Contribution to journal › Article › peer-review

14 Citations (Scopus)

Abstract

To realize suspension semi-active adaptive control and the compromise between ride comfort and control stability, an algorithm based on multi-objective optimization and road recognition was proposed. Firstly, we built an equivalent quarter vehicle model with skyhook control, and established analytical descriptions, based on the system dynamics, for vehicle sprung mass acceleration and tire force. Then, a genetic-based multi-objective optimization method was used to calculate the Pareto optimal solutions. Different weights were assigned for different road level to obtain the corresponding control gains. Simulation results show that the as-proposed adaptive control strategy can achieve the balance between ride comfort and control stability for varying road levels.

Original language	English
Pages (from-to)	1138-1143
Number of pages	6
Journal	Dongbei Daxue Xuebao/Journal of Northeastern University
Volume	37
Issue number	8
DOIs	https://doi.org/10.3969/j.issn.1005-3026.2016.08.016
Publication status	Published - 1 Aug 2016

Keywords

Control stability
Multi-objective optimization
Ride comfort
Road classification
Suspension semi-active control

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10.3969/j.issn.1005-3026.2016.08.016

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title = "Suspension semi-active control of vehicles based on road profile classification",

abstract = "To realize suspension semi-active adaptive control and the compromise between ride comfort and control stability, an algorithm based on multi-objective optimization and road recognition was proposed. Firstly, we built an equivalent quarter vehicle model with skyhook control, and established analytical descriptions, based on the system dynamics, for vehicle sprung mass acceleration and tire force. Then, a genetic-based multi-objective optimization method was used to calculate the Pareto optimal solutions. Different weights were assigned for different road level to obtain the corresponding control gains. Simulation results show that the as-proposed adaptive control strategy can achieve the balance between ride comfort and control stability for varying road levels.",

keywords = "Control stability, Multi-objective optimization, Ride comfort, Road classification, Suspension semi-active control",

author = "Qin, {Ye Chen} and Dong, {Ming Ming} and Feng Zhao and Liang Gu",

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T1 - Suspension semi-active control of vehicles based on road profile classification

AU - Qin, Ye Chen

AU - Dong, Ming Ming

AU - Zhao, Feng

AU - Gu, Liang

PY - 2016/8/1

Y1 - 2016/8/1

N2 - To realize suspension semi-active adaptive control and the compromise between ride comfort and control stability, an algorithm based on multi-objective optimization and road recognition was proposed. Firstly, we built an equivalent quarter vehicle model with skyhook control, and established analytical descriptions, based on the system dynamics, for vehicle sprung mass acceleration and tire force. Then, a genetic-based multi-objective optimization method was used to calculate the Pareto optimal solutions. Different weights were assigned for different road level to obtain the corresponding control gains. Simulation results show that the as-proposed adaptive control strategy can achieve the balance between ride comfort and control stability for varying road levels.

AB - To realize suspension semi-active adaptive control and the compromise between ride comfort and control stability, an algorithm based on multi-objective optimization and road recognition was proposed. Firstly, we built an equivalent quarter vehicle model with skyhook control, and established analytical descriptions, based on the system dynamics, for vehicle sprung mass acceleration and tire force. Then, a genetic-based multi-objective optimization method was used to calculate the Pareto optimal solutions. Different weights were assigned for different road level to obtain the corresponding control gains. Simulation results show that the as-proposed adaptive control strategy can achieve the balance between ride comfort and control stability for varying road levels.

KW - Control stability

KW - Multi-objective optimization

KW - Ride comfort

KW - Road classification

KW - Suspension semi-active control

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JF - Dongbei Daxue Xuebao/Journal of Northeastern University

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Suspension semi-active control of vehicles based on road profile classification

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Keywords

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