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基于变压充电方法的直线电机式馈能型半主动悬架控制

陈士安 孙文强 王健 蔡宇萌 王骏骋

陈士安, 孙文强, 王健, 蔡宇萌, 王骏骋. 基于变压充电方法的直线电机式馈能型半主动悬架控制[J]. 交通运输工程学报, 2018, 18(2): 90-100. doi: 10.19818/j.cnki.1671-1637.2018.02.010
引用本文: 陈士安, 孙文强, 王健, 蔡宇萌, 王骏骋. 基于变压充电方法的直线电机式馈能型半主动悬架控制[J]. 交通运输工程学报, 2018, 18(2): 90-100. doi: 10.19818/j.cnki.1671-1637.2018.02.010
CHEN Shi-an, SUN Wen-qiang, WANG Jian, CAI Yu-meng, WANG Jun-cheng. Control of energy-reclaiming semi-active suspension with linear motor based on varying charge voltage method[J]. Journal of Traffic and Transportation Engineering, 2018, 18(2): 90-100. doi: 10.19818/j.cnki.1671-1637.2018.02.010
Citation: CHEN Shi-an, SUN Wen-qiang, WANG Jian, CAI Yu-meng, WANG Jun-cheng. Control of energy-reclaiming semi-active suspension with linear motor based on varying charge voltage method[J]. Journal of Traffic and Transportation Engineering, 2018, 18(2): 90-100. doi: 10.19818/j.cnki.1671-1637.2018.02.010

基于变压充电方法的直线电机式馈能型半主动悬架控制

doi: 10.19818/j.cnki.1671-1637.2018.02.010
基金项目: 

国家自然科学基金项目 51575239

详细信息
    作者简介:

    陈士安(1973-), 男, 湖北荆州人, 江苏大学教授, 工学博士, 从事汽车悬架控制研究

  • 中图分类号: U463.33

Control of energy-reclaiming semi-active suspension with linear motor based on varying charge voltage method

More Information
  • 摘要: 针对以直线电机作为执行器的馈能型半主动悬架控制方法复杂与效果差等问题, 结合变压充电控制原理与方法, 提出一种利用单相等效模型求解充电电压的方法, 设计了馈能型半主动悬架控制系统, 用于控制直线电机式馈能执行器; 建立了1/2车4自由度动力学模型和变压充电控制直线电机模型, 采用LQG控制策略求解理想馈能阻尼力; 将联接有整流桥的直线电机理论模型等效为单相电机模型, 计算了电机单相等效模型反电动势、电磁推力系数、电阻与电感参数; 采用充电电压求解控制器, 以悬架相对速度和理想馈能阻尼力作为输入求解实际充电电压, 进而实现执行器馈能控制; 以被动悬架和理想半主动悬架作为比较对象, 分析了馈能型半主动悬架性能与馈能效果。分析结果表明: 与被动悬架相比, 馈能型半主动悬架与理想半主动悬架的综合性能指标分别减小38.97%和45.42%, 前后悬架实际馈能阻尼力与理想馈能阻尼力的相关系数分别为0.967 4和0.976 8, 并且前后悬架振动能量的56.7%和62.1%被回收进蓄电池中, 因此, 采用基于单相等效模型与变压充电方法控制的馈能型半主动悬架能够回收大部分悬架振动能量和改善汽车的行驶平顺性。

     

  • 图  1  变压充电控制原理

    Figure  1.  Control principle of varying charge voltage

    图  2  直线电机阻尼特性曲线

    Figure  2.  Damping characteristic curves of linear motor

    图  3  车辆模型

    Figure  3.  Vehicle model

    图  4  馈能型半主动悬架控制系统

    Figure  4.  Control system of energy-reclaiming semi-active suspension

    图  5  直线电机单相等效模型

    Figure  5.  Single phase equivalent model of linear motor

    图  6  反电动势与速度曲线

    Figure  6.  Curves of back electromotive force and velocity

    图  7  电磁推力与电流曲线

    Figure  7.  Curves of Electromagnetic thrust and current

    图  8  实际和拟合电磁推力对比

    Figure  8.  Comparison of actual and fitting electromagnetic thrusts

    图  9  前悬架馈能阻尼力曲线

    Figure  9.  Curves of energy-reclaiming damping force of front suspension

    图  10  后悬架馈能阻尼力曲线

    Figure  10.  Curves of energy-reclaiming damping force of rear suspension

    图  11  车身加速度曲线

    Figure  11.  Curves of body acceleration

    图  12  俯仰角加速度曲线

    Figure  12.  Curves of pitch angle acceleration

    图  13  前轮动变形曲线

    Figure  13.  Curves of front wheel dynamic deformation

    图  14  前悬架动挠度曲线

    Figure  14.  Curves of front suspension dynamic deflection

    图  15  悬架综合性能指标曲线

    Figure  15.  Curves of suspension comprehensive performance index

    图  16  车身加速度功率谱密度曲线

    Figure  16.  Curves of power spectral density of body acceleration

    图  17  俯仰角加速度功率谱密度曲线

    Figure  17.  Curves of power spectral density of pitch angle acceleration

    图  18  前轮动变形功率谱密度曲线

    Figure  18.  Curves of power spectral density of front wheel dynamic deformation

    图  19  前悬架动挠度功率谱密度曲线

    Figure  19.  Curves of power spectral density of front suspension dynamic deflection

    图  20  前悬架功率曲线

    Figure  20.  Power curves of front suspension

    图  21  前悬架能量曲线

    Figure  21.  Energy curves of front suspension

    表  1  电机仿真主要参数

    Table  1.   Main parameters in motor simulation

    下载: 导出CSV

    表  2  电磁推力拟合精度

    Table  2.   Fitting precision of electromagnetic thrust

    下载: 导出CSV

    表  3  仿真参数

    Table  3.   Simulation parameters

    下载: 导出CSV

    表  4  理想与实际馈能阻尼力相关性

    Table  4.   Correlation between ideal and actual energy-reclaiming damping forces

    下载: 导出CSV

    表  5  悬架性能指标对比

    Table  5.   Comparison of performance indexes of suspensions

    下载: 导出CSV

    表  6  馈能型半主动悬架的能量回收数据

    Table  6.   Energy recovery data of ERSAS

    下载: 导出CSV
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  • 收稿日期:  2017-12-05
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