Fuzzy Neural Network PID-Based Constant Deceleration Control for Automated Mine Electric Vehicles Using EMB System

• Published in: Sensors (Basel, Switzerland) Vol. 24; no. 7; p. 2129
• Main Authors: Li, Jian, Ma, Chi, Jiang, Yuqiang
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 01.04.2024
• Subjects: Automation; Automobiles, Electric; autonomous driving; Braking systems; constant deceleration control; Control algorithms; Design; Electric vehicles; electro-mechanical brake system; Friction; Fuzzy logic; fuzzy neural network PID algorithm; Genetic algorithms; Heuristic; Hydraulics; intelligent chassis control; Microelectromechanical systems; Mineral industry; Mining industry; Neural networks; Parameter estimation; Railroad accidents & safety; Simulation; underground electric trackless rubber-tired vehicle; electro-mechanical brake system; underground electric trackless rubber-tired vehicle; constant deceleration control; fuzzy neural network PID algorithm; intelligent chassis control; autonomous driving
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s24072129

It is urgent for automated electric transportation vehicles in coal mines to have the ability of self-adaptive tracking target constant deceleration to ensure stable and safe braking effects in long underground roadways. However, the current braking control system of underground electric trackless rubber-tired vehicles (UETRVs) still adopts multi-level constant braking torque control, which cannot achieve target deceleration closed-loop control. To overcome the disadvantages of lower safety and comfort, and the non-precise stopping distance, this article describes the architecture and working principle of constant deceleration braking systems with an electro-mechanical braking actuator. Then, a deceleration closed-loop control algorithm based on fuzzy neural network PID is proposed and simulated in Matlab/Simulink. Finally, an actual brake control unit (BCU) is built and tested in a real industrial field setting. The test illustrates the feasibility of this constant deceleration control algorithm, which can achieve constant decelerations within a very short time and maintain a constant value of −2.5 m/s2 within a deviation of ±0.1 m/s2, compared with the deviation of 0.11 m/s2 of fuzzy PID and the deviation of 0.13 m/s2 of classic PID. This BCU can provide electric and automated mine vehicles with active and smooth deceleration performance, which improves the level of electrification and automation for mine transport machinery.