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矿用双轨底盘自主行走性能及机电特性研究

Research on autonomous walking performance and electromechanical characteristics of mining double-track chassis.

作者信息

Chen Zeren, Wang Yongpeng, Yang Fei, Li Ruibin, Han Peng, Xue Duomei

机构信息

College of Mechanical Engineering, Taiyuan University of Technology, Taiyuan, Shanxi, China.

Taiyuan Heavy Machinery Group Co., Ltd, Taiyuan, Shanxi, China.

出版信息

PLoS One. 2024 Dec 3;19(12):e0312096. doi: 10.1371/journal.pone.0312096. eCollection 2024.

DOI:10.1371/journal.pone.0312096
PMID:39625968
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11614219/
Abstract

To study the autonomous walking performance and corresponding electromechanical characteristics of unmanned mining equipment under different slopes, turning radii, and ground conditions. Firstly, the autonomous walking systems based on PID, fuzzy PID, and BP PID, in this paper, are constructed, and then the electromechanical coupling simulation is carried out to analyse autonomous walking performance and electromechanical characteristics of mining double-track chassis under different working conditions. Finally, the feasibility of the autonomous walking system based on fuzzy PID is verified by the path-tracking experiment. The results show that the autonomous walking performance of the autonomous walking system based on the fuzzy PID is the best. Under the soft ground, the current, voltage, and load torque are all increased to varying degrees due to the sinking phenomenon of the crawler, but the driving speed is reduced, and when mining double-track chassis makes large-radius turns, the autonomous walking system based on the BP PID can also be given priority with a path deviation within 0.1 m.

摘要

为研究无人采矿设备在不同坡度、转弯半径和地面条件下的自主行走性能及相应的机电特性。首先，构建了本文基于PID、模糊PID和BP-PID的自主行走系统，然后进行机电耦合仿真，分析不同工况下采矿双轨底盘的自主行走性能和机电特性。最后，通过路径跟踪实验验证了基于模糊PID的自主行走系统的可行性。结果表明，基于模糊PID的自主行走系统的自主行走性能最佳。在软土地面上，由于履带的下沉现象，电流、电压和负载转矩均有不同程度的增加，但行驶速度降低，且当采矿双轨底盘进行大半径转弯时，基于BP-PID的自主行走系统也能优先保证路径偏差在0.1m以内。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b0/11614219/ee61dfae975c/pone.0312096.g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b0/11614219/b8b7bc1cbb2f/pone.0312096.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b0/11614219/b34a94d7a5ec/pone.0312096.g002.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b0/11614219/a9f434500c34/pone.0312096.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b0/11614219/455cdaff4050/pone.0312096.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b0/11614219/aa92ced30334/pone.0312096.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b0/11614219/e71ae42567c7/pone.0312096.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b0/11614219/242bb091d61b/pone.0312096.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b0/11614219/ee61dfae975c/pone.0312096.g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b0/11614219/b8b7bc1cbb2f/pone.0312096.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b0/11614219/b34a94d7a5ec/pone.0312096.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b0/11614219/d30a492e3969/pone.0312096.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b0/11614219/94c0a5030fb4/pone.0312096.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b0/11614219/a9f434500c34/pone.0312096.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b0/11614219/455cdaff4050/pone.0312096.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b0/11614219/aa92ced30334/pone.0312096.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b0/11614219/e71ae42567c7/pone.0312096.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b0/11614219/242bb091d61b/pone.0312096.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b0/11614219/ee61dfae975c/pone.0312096.g010.jpg

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本文引用的文献

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A Two-Layer Controller for Lateral Path Tracking Control of Autonomous Vehicles.一种用于自动驾驶车辆横向路径跟踪控制的双层控制器。
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A Path Tracking Strategy for Car Like Robots with Sensor Unpredictability and Measurement Errors.具有传感器不确定性和测量误差的类汽车机器人路径跟踪策略。
Sensors (Basel). 2020 May 29;20(11):3077. doi: 10.3390/s20113077.
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