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In the electro-pneumatic automated mechanical transmission (AMT) system, the manufacturing, assembly, wear, replacement and other issues often lead to gear position change and some differences in various gears of transmission, which reduces the success rate and even results in abnormally working. To solve these problems, based on the intelligent control theories of fuzzy PI control, this research developed an intelligent self-learning system for the AMT gear position. This system contains the position initialization module after assembling (offline module) and the position correction module in use (online module). The system can automatically recognize gear position deviation and actively correct it, which improves the robustness of shift actuator. The precise control of shift actuator is the key of this self-learning system.

According to the structural features and working characteristics of the dry clutch, this study focuses on the factors that affect the performance and life of the dry clutch. The temperature rise caused by the clutch slipping was proved as the key factor. Dynamics model of the powertrain for the dry clutch in launching process was established, and friction work generated during the launching process was simulated and calculated. Based on the basic theory of heat transfer, this paper defined the boundary conditions of the temperature field and the finite element model for the dry clutch was built. The transient temperature field of the friction disk, temperature field changes under the frequent starting conditions and the effects of friction material on temperature rise were analyzed, and measures were proposed to reduce the temperature of dry clutch from its design, use and control.