Multi-objective optimization design of magnetorheological damper and vehicle handling stability performance research

IF 2.4 3区材料科学 Q3 MATERIALS SCIENCE, MULTIDISCIPLINARY

Journal of Intelligent Material Systems and Structures Pub Date : 2023-09-20 DOI:10.1177/1045389x231195835

Xinxin Wei, Tianhong Yan, Shulin Liu

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引用次数: 0

Abstract

Due to the characteristics of smart material magnetorheological (MR) fluid, such as short response time and large controllable range, semi-active suspension based on MR fluid has been widely used. In order to improve the steering stability of vehicles, a semi-active suspension with tapered flow mode MR was proposed. The magnetic circuit of the proposed structure was designed, its dynamic model was established, and the finite element simulation analysis was carried out. By establishing the optimization objectives and constraints, the MR damper was optimized by NSGA-II and MOST algorithms. The vehicle dynamics model with MR damper was established, and the vehicle dynamics simulation was carried out under the control system based on the vehicle dynamics simulation software CarSim-Simulink before and after optimization. The results show that the NSGA-II optimized MR damper can reduce vehicle roll and significantly improve vehicle handling stability. This paper provides a new idea for improving vehicle handling stability by optimizing the MR damper.

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磁流变阻尼器多目标优化设计及车辆操纵稳定性研究

由于智能材料磁流变液具有响应时间短、可控范围大等特点，基于磁流变液的半主动悬架得到了广泛的应用。为了提高车辆转向稳定性，提出了一种锥流型MR半主动悬架。设计了该结构的磁路，建立了其动力学模型，并进行了有限元仿真分析。通过建立优化目标和约束条件，采用NSGA-II和MOST算法对磁流变阻尼器进行优化。建立了带有磁流变阻尼器的车辆动力学模型，并基于车辆动力学仿真软件CarSim-Simulink在优化前后的控制系统下进行了车辆动力学仿真。结果表明，优化后的NSGA-II磁流变阻尼器能有效降低车辆侧倾，显著提高车辆操纵稳定性。通过优化磁流变阻尼器，为提高车辆操纵稳定性提供了新的思路。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Intelligent Material Systems and Structures 工程技术-材料科学：综合

CiteScore

5.40

自引率

11.10%

发文量

126

审稿时长

4.7 months

期刊介绍： The Journal of Intelligent Materials Systems and Structures is an international peer-reviewed journal that publishes the highest quality original research reporting the results of experimental or theoretical work on any aspect of intelligent materials systems and/or structures research also called smart structure, smart materials, active materials, adaptive structures and adaptive materials.