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The new DI diesel engine combustion system named Double-Layer Diverging Combustion System (DLDCS) results in a better Brake Specific Fuel Consumption (BSFC) and lower exhaust emissions. The previous results of numerical simulation and bench test of a single cylinder DI diesel engine showed that more homogeneous fuel distribution, better BSFC and lower emission level were obtained by employing this combustion system. In this research, further numerical simulation are employed to seek the best injection advance angle and investigate the influence of different volume fraction and type lines of upper layer with AVL Fire.

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.