Version 1
: Received: 20 April 2024 / Approved: 23 April 2024 / Online: 23 April 2024 (10:07:13 CEST)
How to cite:
Li, Y.; Zhu, Z.; Li, X. Reinforcement Learning Based Speed Control with Creep Rate Constraints for Autonomous Driving of Mining Electric Locomotives. Preprints2024, 2024041512. https://doi.org/10.20944/preprints202404.1512.v1
Li, Y.; Zhu, Z.; Li, X. Reinforcement Learning Based Speed Control with Creep Rate Constraints for Autonomous Driving of Mining Electric Locomotives. Preprints 2024, 2024041512. https://doi.org/10.20944/preprints202404.1512.v1
Li, Y.; Zhu, Z.; Li, X. Reinforcement Learning Based Speed Control with Creep Rate Constraints for Autonomous Driving of Mining Electric Locomotives. Preprints2024, 2024041512. https://doi.org/10.20944/preprints202404.1512.v1
APA Style
Li, Y., Zhu, Z., & Li, X. (2024). Reinforcement Learning Based Speed Control with Creep Rate Constraints for Autonomous Driving of Mining Electric Locomotives. Preprints. https://doi.org/10.20944/preprints202404.1512.v1
Chicago/Turabian Style
Li, Y., Zhencai Zhu and Xiaoqiang Li. 2024 "Reinforcement Learning Based Speed Control with Creep Rate Constraints for Autonomous Driving of Mining Electric Locomotives" Preprints. https://doi.org/10.20944/preprints202404.1512.v1
Abstract
The working environment of mining electric locomotives is wet and muddy coal mine 1 roadway. There may be idling or slipping between the wheels and rails of mining electric locomotives 2 due to low friction between the wheel and rail and insufficient utilization of creep rate. Therefore, it 3 is necessary to control the creep rate within a reasonable range. In this paper, the autonomous control 4 algorithm for mining electric locomotives based on improved ε-greedy is theoretically proven to be 5 convergent and effective firstly. Secondly, after analyzing the contact state between the wheel and rail 6 under wet and slippery road conditions, it was concluded that the value of creep rate is an important 7 factor affecting the autonomous driving of mining electric locomotives. Therefore, the autonomous 8 control method for mining electric locomotives based on creep control is proposed in this paper. 9 Finally, the effectiveness of the proposed method was verified through simulation. The problem of 10 wheel slipping and idling caused by insufficient friction of mining electric locomotives in coal mining 11 environments is effectively suppressed. Autonomous operation of vehicles with optimal driving 12 efficiency can be achieved through quantitative control and utilization of the creep rate between 13 wheels and rails
Keywords
autonomous driving; creep rate; mining electric locomotive; reinforcement learning; 15 speed control
Subject
Engineering, Mining and Mineral Processing
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
