System Identification of Diesel EGR Based on UEGO
Liu Ruixiang1 Gao Xiyan2(1. College of Traffic and Vehicle Engineering, Shandong University of Technology, 255049, China;2. The Institute of Internal Combustion Engine, Dalian University of Technology, 116023, China)
The main issue is system identification with pseudo random binary signal of the EGR system with nonlinearities, time delays, and the effects of complex intake and exhaust gas dynamics. After extensive measurements two ARX models corresponding to two principal conditions are identified. The two order transfer functions with the time delays corresponding to two identified models are obtained. The model's properties are evaluated with validation data sets. The results show that the models are good approximation of the system dynamics.