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When developing a new engine control strategy, some of the important issues are cost, resource minimization, and quality improvement. This paper outlines how a model based approach was used to develop an engine control strategy for an Extended Range Electric Vehicle (EREV). The outlined approach allowed the development team to minimize the required number of experiments and to complete much of the control development and calibration before implementing the control strategy in the vehicle. It will be shown how models of different fidelity, from map-based models, to mean value models, to 1-D gas dynamics models were generated and used to develop the engine control system. The application of real time capable models for Hardware-in-the-Loop testing will also be shown.

The effects of using a B30 blend of ultra-low sulfur diesel and two different Fatty Acid Methyl Esters (FAME) obtained from both Rapeseed Methyl Ester (RME) and Jatropha Methyl Ester (JME) in a Euro 5 small displacement passenger car diesel engine on both full load performance and part load emissions have been evaluated in this paper. In particular the effects on engine torque were firstly analyzed, for both a standard ECU calibration (i.e., without any special tuning for the different fuel characteristics) and for a specifically adjusted ECU calibration obtained by properly increasing the injected fuel quantities to compensate for the lower LHV of the B30: with the latter, the same torque levels measured under diesel operation could be observed with the B30 blend too, with lower smoke levels, thus highlighting the potential for maintaining the same level of performance while achieving substantial emissions benefits.

Experimental work was carried out on a small displacement Euro 5 automotive diesel engine alternatively fuelled with ultra low sulphur diesel (ULSD) and with two blends (30% vol.) of ULSD and of two different fatty acid methyl esters (FAME) obtained from both rapeseed methyl ester (RME) and jatropha methyl ester (JME) in order to evaluate the effects of different fuel compositions on particle number (PN) emissions. Particulate matter (PM) emissions for each fuel were characterized in terms of number and mass size distributions by means of two stage dilutions system coupled with a scanning mobility particle sizer (SMPS). Measurements were performed at three different sampling points along the exhaust system: at engine-out, downstream of the diesel oxidation catalyst (DOC) and downstream of the diesel particulate filter (DPF). Thus, it was possible to evaluate both the effects of combustion and after-treatment efficiencies on each of the tested fuels.