Study on the Eddy Current Retarder Loading Control System of Loading Vehicles

李忠利

doi:10.7652/xjtuxb201803017

您当前的位置：

首页 >

文章列表页 >

Study on the Eddy Current Retarder Loading Control System of Loading Vehicles

更新时间：2025-11-17

- Study on the Eddy Current Retarder Loading Control System of Loading Vehicles
- Vol. 52, Issue 3, Pages: 126-131(2018)
- 作者机构：
  
  河南科技大学车辆与交通工程学院,河南,洛阳,471003
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb201803017
  CLC： U270.7
- Published：2018
- 稿件说明：
移动端阅览
李忠利. Study on the Eddy Current Retarder Loading Control System of Loading Vehicles[J]. 2018, 52(3): 126-131.
DOI：

李忠利. Study on the Eddy Current Retarder Loading Control System of Loading Vehicles[J]. 2018, 52(3): 126-131. DOI： 10.7652/xjtuxb201803017.

摘要

为能更真实反映被试拖拉机牵引特性

对负荷车加载系统进行了改进

建立了负荷车加载系统传递函数模型。以牵引力载荷谱随机信号为输入

采用BP神经网络算法对加载系统进行动态加载控制

以输出不同类型的作业载荷。对系统响应特性进行了动态分析

在此基础上进行了道路试验验证

证明加载系统的有效性。在该控制模式下系统仿真载荷输出延迟0.12 s

最大超调量为3.1%; 路试载荷输出延迟0.22 s

最大超调量为4.2%。试验结果表明

BP神经网络PID控制的系统输出载荷对输入载荷具有更好的跟随效果

比传统PID控制响应性好

开发的负荷车加载系统输出载荷能够较好再现拖拉机实际牵引载荷。

Abstract

A loading control system of loading vehicle is improved to be able to effectively reflect the traction performance of a tractor in field work. A mathematical model of the loading vehicle's loading system is established. The input signal of the loading system is the stochastic signal of a field load spectrum. The backpropagation neural network is applied to control the loading system. The output signal of the loading system can simulate different kinds of working loads. The loading system response is analyzed dynamically. On the basis of the above study

the road test of the tractor's traction performance was conducted. In this control mode

the simulation results showed that the system delay time is 0.12 s and maximum overshoot is 3.1%. The road test results showed that the system delay time is 0.22 s and maximum overshoot is 4.2%. Experimental results showed that the system output traction has a good following effect in comparison with the input load. The BP neural net PID algorithm can improve the system's dynamical performance and its control response is better than the traditional PID control. So the output load of the developed loading system can better reproduce the tractive performance for the tested tractor.

关键词

Keywords

references

张硕, 杜岳峰, 朱忠祥, 等. 后轮驱动大功率拖拉机牵引力-滑转率联合自动控制方法 [J]. 农业工程学报, 2016, 32(12): 47-53.

ZHANG Shuo, DU Yuefeng, ZHU Zhongxiang, et al. Integrated control method of traction & slip ratio for rear-driving high-power tractors [J]. Transactions of the Chinese Society of Agricultural Engineering, 2016, 32(12): 47-53.

杨启超, 李连生, 赵远扬, 等. 旋涡压缩机轴向动态间隙的实验测量 [J]. 西安交通大学学报, 2008, 42(7): 795-798.

YANG Qichao, LI Liansheng, ZHAO Yuanyang, et al. Measurement of axial dynamic clearance in scroll compressor [J]. Journal of Xi'an Jiaotong University, 2008, 42(7): 795-798.

BABU G S, SURESH S. Meta-cognitive RBF network and its projection based learning algorithm for classification problems [J]. Applied Soft Computing, 2013, 13(1): 654-666.

HAYATI M, LOTFI A, KAZIMIERCZUK M K, et al. Generalized design considerations and analysis of class-E amplifier for sinusoidal and square input voltage waveforms [J]. IEEE Trans Ind Electron, 2015, 62(1): 211-220.

HERNMÁNDEZ-ALVARADO R, GARCÍA-VALDOVINOS L G, SALGADO-JIMÉNEZ T. Neural network-based self-tuning PID control for underwater vehicles [J]. Sensors, 2016, 16(9): 1429.

ANWAR S. A parametric model of an eddy current electric machine for automotive braking applications [J]. IEEE Transactions on Control Systems Technology, 2004, 12(3): 422-427.

丁锋. 系统辨识: 1 辨识导引 [J]. 南京信息工程大学学报, 2011, 3(1): 1-22.

DING Feng. System identification: part A Introduction to the identification [J]. Journal of Nanjing University of Information Science Technology, 2011, 3(1): 1-22.

章军辉, 李庆, 陈大鹏. 基于BP神经网络的纵向避撞安全辅助算法 [J]. 西安交通大学学报, 2017, 51(7): 140-147.

ZHANG Junhui, LI Qing, CHEN Dapeng. Safety assistance algorithm for longitudinal collision avoidance based on BP neural network [J]. Journal of Xi'an Jiaotong University, 2017, 51(7): 140-147.

韩磊, 李锐, 朱会利, 等. 基于BP神经网络的土壤养分综合评价模型 [J]. 农业机械学报, 2011, 42(7): 109-115.

HAN Lei, LI Rui, ZHU Huili. Comprehensive evaluation model of soil nutrient based on BP neural network [J]. Transactions of the Chinese Society for Agricultural Machinery, 2011, 42(7): 109-115.

陈月霞, 陈龙, 徐兴, 等. 随机干扰下电控空气悬架整车车身高度控制研究 [J]. 农业机械学报, 2015, 46(12): 309-315.

CHEN Yuexia, CHEN Long, XU Xing, et al. Vehicle height control of electronic-controlled air suspension under random disturbance [J]. Transactions of the Chinese Society for Agricultural Machinery, 2015, 46(12): 309-315.

王洪乐, 王家序, 周青华, 等. 基于BP神经网络的数控机床综合误差补偿方法 [J]. 西安交通大学学报, 2017, 51(6): 138-146.

WANG Hongle, WANG Jiaxu, ZHOU Qinghua, et al. Comprehensive error compensation of machine tools based on BP-neural network algorithm [J]. Journal of Xi'an Jiaotong University, 2017, 51(6): 138-146.

汪少华, 窦辉, 孙晓强, 等. 电控空气悬架车高调节与整车姿态控制研究 [J]. 农业机械学报, 2015, 46(10): 335-342.

WANG Shaohua, DOU Hui, SUN Xiaoqiang, et al. Vehicle height adjustment and attitude control of electronically controlled air suspension electronically controlled air suspension [J]. Transactions of the Chinese Society for Agricultural Machinery, 2015, 46(10): 335-342.

WALLACE M I, WAGG D J, NEILD S A. An adaptive polynomial based forward prediction algorithm for multi-actuator real-time dynamic substructuring [J]. Proceedings of the Royal Society, 2005(461): 3807-3826.

谢进, 阎开印, 陈永. 基于BP神经网络的平面机构连杆运动综合 [J]. 机械工程学报, 2005, 41(2): 24-27.

XIE Jin, YAN Kaiyin, CHEN Yong. Synthesis of planar motion generation mechanisms using BP neural networks [J]. Chinese Journal of Mechanical Engineering, 2005, 41(2): 24-27.

方在华, 周志立, 杨铁皂, 等. 拖拉机随机载荷的功率谱函数 [J]. 洛阳工学院学报, 1999, 20(4): 1-4.

FANG Zaihua, ZHOU Zhili, YANG Tiezao, et al. The power spectral function of the random loads in tractor [J]. Journal of Luoyang Institute of Technology, 1999, 20(4): 1-4.

方在华, 周志立, 杨铁皂, 等. 正态随机载荷的计算机仿真 [J]. 洛阳工学院学报, 2000, 21(1): 1-3.

FANG Zaihua, ZHOU Zhili, YANG Tiezao, et al. Computer simulation for normal random load [J]. Journal of Luoyang Institute of Technology, 2000, 21(1): 1-3.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Effects of Expansion Angle Crater Film Hole on the Film Cooling Characteristics of a Double-Wall Structure

Review of the Application of EBSILON Software in Combined Heat and Power System Optimization

Electrothermal Coupling Research on the Evolutionary Law of Anti-Corona Performance for High-Altitude Air-Cooled Generators

Influence of Structural Parameters on the Summer Operational Characteristics of a Three-Tower-in-One Indirect Air-Cooling System

Sensitivity Analysis of Foil Geometrical Parameters for the Third-Generation CO2 Gas Foil Bearings Based on Design of Experiments Method

Related Author

No data

Related Institution

No data

⁰