Control Oriented Nitrogen Oxide and Soot Emission Estimation for Diesel Engine
Abstract
Comparing to conventional Electric Vehicles (EVs) and Hybrid Electric Vehicles (HEV), Plug-in Hybrid Electric Vehicles (PHEVs) have gained more attraction from researchers due to their advantages of extended all-electric range, decreased emission and being less dependent on recharging infrastructure. In order to develop power control and management for diesel engine-generator set in a series PHEV system, an estimation mechanism based on the NOx and soot emission with the impact of Exhaust Gas Recirculation (EGR) is developed in this thesis. In particular, the single zone combustion thermodynamic engine sub-model, NOx estimation sub-model (based on extended Zeldovich mechanism), soot estimation sub-model (based on Hiroyasu's two-step empirical model) and EGR sub-model are incorporated together. In order to illustrate the impact of EGR on the NOx and soot emission, the EGR sweep experiment has been carried out under certain working conditions. And, the simulation results have been validated with the empirical data. Finally, based on the validation of the emission estimation mechanism and the selected eight operating points working condition, the results EGR sweep results have been generated for the series PHEV engine-generator control design. In general, the present work targets on estimating real-time NOx and soot emission based on the inputs information, such as intake boost, fuel injection, injection timing etc, and the purpose of this thesis is to aid development of engine emission management with study about the effect of EGR on the reduction and the soot trade-off.