Real-time and robust estimation of biodiesel blends

Biodiesel as a renewable alternative fuel produces lower exhaust emissions with the exception of nitrogen oxides (NO_x) when compared to the conventional diesel fuel. Reducing nitrogen oxides produced from engines running on biodiesel requires proper engine controller adaptations that are linked to the specifics of the fuel blend. Therefore, online estimation of fuel blend is a critical step in allowing diesel engines to maintain performance while simultaneously meeting emission requirements when operating on biodiesel blends. Presented in this paper are three different model-based biodiesel blend estimation strategies using: (i) crankshaft torsionals, (ii) NO_x emissions measurement from the exhaust stream, and (iii) oxygen content measurement of the exhaust stream using a wide-band UEGO sensor. Each approach is investigated in terms of the accuracy and robustness to sensor errors. A sensitivity analysis is conducted for each method to quantify robustness of the proposed fuel blend estimation methods.