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HMCVT段内无级跟踪调速控制研究

卢震 鲁植雄 程准

卢震,鲁植雄,程准. HMCVT段内无级跟踪调速控制研究[J]. 机械科学与技术,2021,40(4):518-526 doi: 10.13433/j.cnki.1003-8728.20200101
引用本文: 卢震,鲁植雄,程准. HMCVT段内无级跟踪调速控制研究[J]. 机械科学与技术,2021,40(4):518-526 doi: 10.13433/j.cnki.1003-8728.20200101
LU Zhen, LU Zhixiong, CHENG Zhun. Research on Tracking Speed Control of HMCVT Stepless Segment[J]. Mechanical Science and Technology for Aerospace Engineering, 2021, 40(4): 518-526. doi: 10.13433/j.cnki.1003-8728.20200101
Citation: LU Zhen, LU Zhixiong, CHENG Zhun. Research on Tracking Speed Control of HMCVT Stepless Segment[J]. Mechanical Science and Technology for Aerospace Engineering, 2021, 40(4): 518-526. doi: 10.13433/j.cnki.1003-8728.20200101

HMCVT段内无级跟踪调速控制研究

doi: 10.13433/j.cnki.1003-8728.20200101
基金项目: 国家重点研发专项(2016YFD0701103)与江苏省研究生科研创新计划(KYCX17_0647)
详细信息
    作者简介:

    卢震(1993−),硕士研究生,研究方向为汽车电子控制技术,15855512367@163.com

    通讯作者:

    鲁植雄,教授,博士生导师,博士,luzx@njau.edu.cn

  • 中图分类号: S219.032.1; TP273.2

Research on Tracking Speed Control of HMCVT Stepless Segment

  • 摘要: 为了解决拖拉机在实际行驶过程中,由于马达转速的变化存在响应的滞后,造成各工况下拖拉机的车速并非最优值。设计了HMCVT泵控马达系统转速跟踪控制器,实现马达转速的实时跟踪。建立了HMCVT泵控马达系统的数学模型,采用模糊PID控制器对马达转速进行实时控制。提出了一种改进粒子群算法寻优的方法,对模糊PID控制器的参数进行寻优。根据寻优的最优系数,在MATLAB/Simulink中搭建HMCVT泵控马达系统的仿真模型并进行相关仿真。仿真结果表明:采用改进粒子群算法优化的模糊PID控制器能够很好地实现马达转速的跟踪控制,跟踪误差以及超调量很小,同时在系统受到外负载扰动时表现出良好的跟随特性。研究结果为制定拖拉机HMCVT的最佳燃油经济性和最佳动力性的段内控制策略提供了理论参考。
  • 图  1  传动方案原理图

    图  2  HMCVT泵马达系统马达转速跟踪控制原理图

    图  3  HMCVT理想传动比MAP图

    图  4  马达输出轴转速传感器示意图

    图  5  模糊PID控制器原理图

    图  6  隶属度函数编辑器

    图  7  $\Delta {K_p}$$\Delta {K_i}$$\Delta {K_d}$在论域上的输出曲面图

    图  8  算法收敛曲线

    图  9  泵控马达系统模糊PID仿真模型

    图  10  适应度值变化曲线

    图  11  阶跃信号马达转速跟踪结果

    图  12  正弦信号马达转速跟踪结果

    图  13  负载扰动下阶跃信号马达转速跟踪结果

    图  14  负载扰动下正弦信号马达转速跟踪结果

    表  1  HMCVT泵控马达系统目标马达转速

    区段HMCVT泵控马达系统目标马达转速
    HM1${n_{m1}} = \dfrac{{{k_3}\left( {1 + {k_1}} \right)\left( {1 + {k_4}} \right){i_1}{i_3}{i_4}{i_4}{n_{out}} + \left( {1 + {k_1}} \right)\left( {1 + {k_2}} \right){i_1}{i_2}{n_0}}}{{\left( {1 + {k_2} + {k_3}} \right)}} - {k_1}{i_1}{i_2}{n_0}$
    HM2${n_{m2}} = \dfrac{{\left( {1 + {k_1}} \right)\left( {1 + {k_2}} \right){i_1}{i_2}{n_0} - \left( {1 + {k_1}} \right)\left( {1 + {k_4}} \right){i_2}{i_3}{i_4}{i_4}{n_{out}}}}{{{k_2}}} - {k_1}{i_1}{i_2}{n_0}$
    HM3${n_{m3}} = \left( {1 + {k_1}} \right){i_1}{i_2}{i_3}{i_4}{n_{{\rm{out }}}} - {k_1}{i_1}{i_2}{n_0}$
    HM4${n_{m4}} = \dfrac{{\left( {1 + {k_1}} \right)\left( {1 + {k_2}} \right){i_1}{i_2}{n_0} - \left( {1 + {k_1}} \right){i_1}{i_2}{i_3}{i_4}{n_{out}}}}{{{k_2}}} - {k_1}{i_1}{i_2}{n_0}$
    下载: 导出CSV

    表  2  各项参数优化结果

    ${k_1}$${k_2}$${k_3}$${k_4}$${i_1}$${i_2}$${i_3}$${i_4}$
    2.95981.96622.99872.99961.00131.00811.12741.3615
    下载: 导出CSV

    表  3  试验数据记录

    励磁电压U/V输入转速/
    (r·min−1
    输出转速/
    (r·min−1
    排量比负载/
    (N·m)
    11050195.250.2881150
    2194.250.2866
    3143.250.2114
    477.750.1147
    516.250.0239
    下载: 导出CSV

    表  4  优化变量的上下限取值

    取值${K_e}$${K_{ec}}$$\Delta {K_p}$$\Delta {K_i}$$\Delta {K_d}$
    下限0.50.51050.01
    上限1.51.530151
    下载: 导出CSV

    表  5  改进PSO算法最优整定结果

    ${K_e}$${K_{ec}}$$\Delta {K_p}$$\Delta {K_i}$$\Delta {K_d}$
    1.44841.008412.883913.33430.5434
    下载: 导出CSV
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出版历程
  • 收稿日期:  2019-11-03
  • 网络出版日期:  2021-04-16
  • 刊出日期:  2021-04-16

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