Fuzzy PID Based Optimization of Starting Control for AMT Clutch of Heavy-duty Trucks

Starting control has become a troublesome issue in the developing field of the control system for heavy-duty trucks, due to the complexity of vehicle driving and the variability of driver's intention. The too fast clutch engagement may result in serious impact, influence on the comfort and fatigue life, and even the engine flameout, while the too slow clutch engagement may lead to long time of friction, the increased temperature, and accelerated wear of friction pair, as well as influence on the power performance and fatigue life[1]. Therefore, the key technique of starting control is clutch engagement control, for which the fuzzy PID based optimization of starting control for AMT clutch is proposed, with the pneumatic AMT clutch of heavy-duty trucks as the research object. Firstly, the structure and working principle of the clutch control system is introduced, and the working characteristics of the clutch is analyzed; Secondly, the clutch engagement process is analyzed, and the dynamic analysis is carried out for the starting process, to establish the theoretical model; Then, the common PID algorithm is improved to optimize its parameters by the fuzzy inference method of the error change rate and error rate of clutch position, and the fuzzy PID based starting controller is designed. Finally, the vehicle dynamics model and clutch control model are established for simulation by using MATLAB/SIMULINK, and the real vehicle test is also carried out to verify the designed optimal PID control algorithm. The simulation and test results show that the fuzzy PID based starting controller results in better target tracing performance of the clutch engagement displacement, compared to normal PID control, and the starting performance has been improved with the smoother starting process.


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  • Accession Number: 01730840
  • Record Type: Publication
  • Source Agency: SAE International
  • Report/Paper Numbers: 2018-01-1166
  • Files: TRIS, SAE
  • Created Date: Oct 8 2018 1:00PM