Vehicle Attitude Control of Magnetorheological Semi-Active Suspension Based on Multi-Objective Intelligent Optimization Algorithm

A multi-objective intelligent optimization algorithm-based attitude control strategy for magnetorheological semi-active suspension is proposed to address the vehicle attitude imbalance generated during steering and braking. Firstly, the mechanical properties of the magnetorheological damper (MRD) ar...

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Main Authors: Kailiang Han, Yiming Hu, Dequan Zeng, Yinquan Yu, Lei Xiao, Jinwen Yang, Weidong Liu, Letian Gao
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Actuators
Subjects:
Online Access:https://www.mdpi.com/2076-0825/13/12/466
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author Kailiang Han
Yiming Hu
Dequan Zeng
Yinquan Yu
Lei Xiao
Jinwen Yang
Weidong Liu
Letian Gao
author_facet Kailiang Han
Yiming Hu
Dequan Zeng
Yinquan Yu
Lei Xiao
Jinwen Yang
Weidong Liu
Letian Gao
author_sort Kailiang Han
collection DOAJ
description A multi-objective intelligent optimization algorithm-based attitude control strategy for magnetorheological semi-active suspension is proposed to address the vehicle attitude imbalance generated during steering and braking. Firstly, the mechanical properties of the magnetorheological damper (MRD) are tested, and the parameters in the hyperbolic tangent model of the magnetorheological damper are identified through experiments. Secondly, a simulation model of the whole vehicle multi-degree-of-freedom vehicle dynamics including magnetorheological damper is established, and the whole-vehicle Linear Quadratic Regulator (LQR) controller is designed. Then, the optimization design model of the joint vehicle controller and vehicle dynamics is established to design the optimization fitness function oriented to the body attitude control performance, and the attitude optimal controller is calculated with the help of multi-objective intelligent optimization algorithm. Simulation results show that the proposed control method is able to improve the body roll angle, body pitch angle, and suspension dynamic deflection well on the basis of ensuring no deterioration in other performance indexes, ensuring good attitude control capability of the vehicle and verifying the feasibility of the control strategy.
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issn 2076-0825
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publishDate 2024-11-01
publisher MDPI AG
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series Actuators
spelling doaj-art-c0fc5c5487a04c74bdda8407c7e4911a2025-08-20T02:53:38ZengMDPI AGActuators2076-08252024-11-01131246610.3390/act13120466Vehicle Attitude Control of Magnetorheological Semi-Active Suspension Based on Multi-Objective Intelligent Optimization AlgorithmKailiang Han0Yiming Hu1Dequan Zeng2Yinquan Yu3Lei Xiao4Jinwen Yang5Weidong Liu6Letian Gao7School of Mechatronics and Vehicle Engineering, East China Jiaotong University, Nanchang 330013, ChinaSchool of Mechatronics and Vehicle Engineering, East China Jiaotong University, Nanchang 330013, ChinaSchool of Mechatronics and Vehicle Engineering, East China Jiaotong University, Nanchang 330013, ChinaSchool of Mechatronics and Vehicle Engineering, East China Jiaotong University, Nanchang 330013, ChinaSchool of Mechatronics and Vehicle Engineering, East China Jiaotong University, Nanchang 330013, ChinaSchool of Mechatronics and Vehicle Engineering, East China Jiaotong University, Nanchang 330013, ChinaSchool of Automotive Studies, Tongji University, Shanghai 201804, ChinaDepartment of Civil and Environmental Engineering, UCLA, Los Angeles, CA 90095, USAA multi-objective intelligent optimization algorithm-based attitude control strategy for magnetorheological semi-active suspension is proposed to address the vehicle attitude imbalance generated during steering and braking. Firstly, the mechanical properties of the magnetorheological damper (MRD) are tested, and the parameters in the hyperbolic tangent model of the magnetorheological damper are identified through experiments. Secondly, a simulation model of the whole vehicle multi-degree-of-freedom vehicle dynamics including magnetorheological damper is established, and the whole-vehicle Linear Quadratic Regulator (LQR) controller is designed. Then, the optimization design model of the joint vehicle controller and vehicle dynamics is established to design the optimization fitness function oriented to the body attitude control performance, and the attitude optimal controller is calculated with the help of multi-objective intelligent optimization algorithm. Simulation results show that the proposed control method is able to improve the body roll angle, body pitch angle, and suspension dynamic deflection well on the basis of ensuring no deterioration in other performance indexes, ensuring good attitude control capability of the vehicle and verifying the feasibility of the control strategy.https://www.mdpi.com/2076-0825/13/12/466magnetorheological dampersemi-active suspensionbody attitude controlMOPSO-LQR control
spellingShingle Kailiang Han
Yiming Hu
Dequan Zeng
Yinquan Yu
Lei Xiao
Jinwen Yang
Weidong Liu
Letian Gao
Vehicle Attitude Control of Magnetorheological Semi-Active Suspension Based on Multi-Objective Intelligent Optimization Algorithm
Actuators
magnetorheological damper
semi-active suspension
body attitude control
MOPSO-LQR control
title Vehicle Attitude Control of Magnetorheological Semi-Active Suspension Based on Multi-Objective Intelligent Optimization Algorithm
title_full Vehicle Attitude Control of Magnetorheological Semi-Active Suspension Based on Multi-Objective Intelligent Optimization Algorithm
title_fullStr Vehicle Attitude Control of Magnetorheological Semi-Active Suspension Based on Multi-Objective Intelligent Optimization Algorithm
title_full_unstemmed Vehicle Attitude Control of Magnetorheological Semi-Active Suspension Based on Multi-Objective Intelligent Optimization Algorithm
title_short Vehicle Attitude Control of Magnetorheological Semi-Active Suspension Based on Multi-Objective Intelligent Optimization Algorithm
title_sort vehicle attitude control of magnetorheological semi active suspension based on multi objective intelligent optimization algorithm
topic magnetorheological damper
semi-active suspension
body attitude control
MOPSO-LQR control
url https://www.mdpi.com/2076-0825/13/12/466
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