The research carried out on this project developed experimentally validated Diesel Oxidation Catalyst (DOC), Diesel Particulate Filter (DPF), and Selective Catalytic Reduction (SCR) high‐
fidelity models that served as the basis for the reduced order models used for internal state estimation. The high‐
fidelity and reduced order/estimator codes were evaluated by the industrial partners with feedback to MTU that improved the codes. Ammonia, particulate matter (PM) mass retained, PM concentration, and NOX sensors were evaluated and used in conjunction with the estimator codes. The data collected from PM experiments were used to develop the PM kinetics using the high‐
fidelity DPF code for both NO2 assisted oxidation and thermal oxidation for Ultra Low Sulfur Fuel (ULSF), and B10 and B20 biodiesel fuels. Nine SAE papers were presented and this technology transfer process should provide the basis for industry to improve the OBD and control of urea injection and fuel injection for active regeneration of the PM in the DPF using the computational techniques developed. This knowledge will provide industry the ability to reduce the emissions and fuel consumption from vehicles in the field. Four MS and three PhD Mechanical Engineering students were supported on this project and their thesis research provided them with expertise in experimental, modeling, and controls in aftertreatment systems.