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磁流变半主动座椅悬架建模及振动特性分析

史文库 张曙光 陈志勇 张友坤

史文库, 张曙光, 陈志勇, 张友坤. 磁流变半主动座椅悬架建模及振动特性分析[J]. 西南交通大学学报, 2023, 58(2): 253-260. doi: 10.3969/j.issn.0258-2724.20210882
引用本文: 史文库, 张曙光, 陈志勇, 张友坤. 磁流变半主动座椅悬架建模及振动特性分析[J]. 西南交通大学学报, 2023, 58(2): 253-260. doi: 10.3969/j.issn.0258-2724.20210882
SHI Wenku, ZHANG Shuguang, CHEN Zhiyong, ZHANG Youkun. Modeling and Vibration Analysis of Semi-active Seat Suspension with Magnetorheological Damper[J]. Journal of Southwest Jiaotong University, 2023, 58(2): 253-260. doi: 10.3969/j.issn.0258-2724.20210882
Citation: SHI Wenku, ZHANG Shuguang, CHEN Zhiyong, ZHANG Youkun. Modeling and Vibration Analysis of Semi-active Seat Suspension with Magnetorheological Damper[J]. Journal of Southwest Jiaotong University, 2023, 58(2): 253-260. doi: 10.3969/j.issn.0258-2724.20210882

磁流变半主动座椅悬架建模及振动特性分析

doi: 10.3969/j.issn.0258-2724.20210882
基金项目: 国家重点研发计划(2018YFB0106200)
详细信息
    作者简介:

    史文库(1960—),男,教授,博士生导师,研究方向为汽车振动噪声分析与控制,E-mail:shiwk@jlu.edu.cn

  • 中图分类号: U461.4

Modeling and Vibration Analysis of Semi-active Seat Suspension with Magnetorheological Damper

  • 摘要:

    磁流变阻尼器力学模型及控制电流逆模型对半主动控制系统的控制精度具有重要影响. 采用正弦及余弦型魔术公式,基于骨架曲线与滞回分离的建模方法,建立改进的磁流变阻尼器动态阻尼力模型;采用基于Sobol序列的差分-禁忌混合优化算法对阻尼力模型进行参数识别,构建包含激励特性及控制电流参数的通用数学模型;在试验测试及正向模型基础上,利用自适应神经模糊系统建立阻尼器控制电流逆模型. 研究结果表明:本文建立的正逆模型均能够有效表征磁流变阻尼器的非线性行为及滞回特性;改进魔术公式模型在不同激励特性及电流工况下的平均百分比误差在3.4%附近变化;逆向动力学模型计算的控制电流误差均方根值为0.0869~0.1171 A;经过控制电流逆模型与阻尼器正向模型串联模型计算的预测阻尼力误差均方根值为阻尼器最大阻尼力的5.6%;通过试验测试与仿真结果对比,验证了本文提出的阻尼器数学模型具有较好的精度和适用性,能够改善座椅悬架系统振动传递特性.

     

  • 图 1  基于骨架曲线与滞回分离的阻尼力模型

    Figure 1.  Model of MR damper with hysteresis division

    图 2  磁流变阻尼器力学特性试验装置

    Figure 2.  Experimental setup of MR damper

    图 3  不同工况下滞回环速度中心

    Figure 3.  Comparison of velocity centers of hysteretic loop

    图 4  不同工况下最大阻尼力

    Figure 4.  Comparison of maximum damping forces

    图 5  SS-DTHA算法流程

    Figure 5.  Flow chart of SS-DTHA

    图 6  不同模型计算值与试验数据对比

    Figure 6.  Comparison of damping forces calculated by different models

    图 7  不同工况下模型计算值与试验数据对比

    Figure 7.  Comparison of damping forces calculated by the model under different working conditions

    图 8  参数BpBhc随激励及电流的变化规律

    Figure 8.  Variation of parameter BpBhc with excitation and current conditions

    图 9  通用模型辨识结果与试验数据对比

    Figure 9.  Comparison of damping forces between generalized model and test data

    图 10  控制电流逆模型预测结果

    Figure 10.  Prediction results of inverse model

    图 11  控制电流逆模型验证流程

    Figure 11.  Inverse model validation steps

    图 12  阻尼力预测结果

    Figure 12.  Prediction results of damper force

    图 13  半主动座椅悬架控制系统示意

    Figure 13.  Semi-active seat suspension control system

    图 14  半主动与被动座椅悬架位移传递率对比

    Figure 14.  Comparison of transmissibility between semi-active and passive seat suspension

    图 15  包含时滞特性的半主动座椅悬架系统框图

    Figure 15.  Application of time delay of the whole semi-active control system

    图 16  不同时间延迟对座椅悬架位移传递率影响对比

    Figure 16.  Comparison of the time delay effect to seat transmissibility

    表  1  不同工况模型平均百分比误差

    Table  1.   Comparison of average percentage error of models under different working conditions

    电流/A幅值 5 mm 幅值 15 mm
    3 Hz4 Hz3 Hz4 Hz
    0 0.0447 0.0355 0.0457 0.0452
    0.2 0.0474 0.0355 0.0289 0.0396
    0.4 0.0316 0.0321 0.0302 0.0319
    0.6 0.0310 0.0322 0.0269 0.0284
    0.8 0.0344 0.0349 0.0305 0.0315
    1.0 0.0308 0.0359 0.0282 0.0273
    下载: 导出CSV

    表  2  滞回模型参数辨识结果

    Table  2.   Parameter identification of hysteretic model

    变量辨识结果
    ${F}_{{\rm{max}}}$$\left(-9.36{I}^{2} + 123.97I + 23.05\right)\left(4.29{ {v}^{0.19}_{{\rm{m}}} }\right)$
    ${\dot{x} }_{{\rm{center}}}$$\left(-3.47I + 1.91\right)(-2.35{\rm{ln} }\;{v}_{ {\rm{m} } } + 9.21)$
    ${B}_{{\rm{p}}}$$1.97{v}^{-1.09}_{{\rm{m}}}$
    ${B}_{{\rm{h}}}$$1.01{v}_{{\rm{m}}}^{-0.86}$
    $ c $$0.32{ {v}_{ {\rm{m} } } ^{-1.01}}$
    Cp1.32
    Dp0.70
    Ep−7.64
    Ch1.10
    Dh0.42
    Eh−11.50
    f0−80.34
    下载: 导出CSV
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出版历程
  • 收稿日期:  2021-11-16
  • 修回日期:  2022-02-17
  • 网络出版日期:  2023-03-28
  • 刊出日期:  2022-03-05

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