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Powertrain electrification is becoming increasingly common in the transportation sector to address the challenges of global warming and deteriorating air quality. This paper introduces a novel “Build Your Hybrid” approach to experience and test various hybrid powertrain concepts. This approach is applied to the light commercial vehicles (LCV) segment due to the attractive combination of a Diesel engine and a partly electrified powertrain. For this purpose, a demonstrator vehicle has been set up with a flexible P02 hybrid topology and a prototype Hybrid Control Unit (HCU). Based on user input, the HCU software modifies the control functions and simulation models to emulate different sub-topologies and levels of hybridization in the demonstrator vehicle. Three powertrain concepts are considered for LCVs: HV P2, 48V P2 and 48V P0 hybrid. Dedicated hybrid control strategies are developed to take full advantage of the synergies of the electrical system and reduce CO2 and NOx emissions.

In order to deeply investigate and improve the complete path from biofuel production to combustion, the cluster of excellence “Tailor-Made Fuels from Biomass” was installed at RWTH Aachen University in 2007. Recently, new pathways have been discovered to synthesize octanol [1] and di-n-butylether (DNBE). These molecules are identical in the number of included hydrogen, oxygen and carbon atoms, but differ in the molecular structure: for octanol, the oxygen atom is at the end of the molecule, whereas for DNBE it is located in the middle. In this paper the utilization of octanol and DNBE in a state-of-the-art single cylinder diesel research engine will be discussed. The major interest has been on engine emissions (NOx, PM, HC, CO, noise) compared to conventional diesel fuel.

Fuel properties are always considered as one of the main factors to diesel engines concerning performance and emission discussions. There are still challenges for researchers to identify the most correlating and non-correlating fuel properties and their effects on engine behavior. Statistical analyses have been applied in this study to derive the most un-correlating properties. In parallel, sensitivity analysis was performed for the fuel properties as well as to the emission and performance of the engine. On one hand, two different analyses were implemented; one with consideration of both, non-aromatic and aromatic fuels, and the other were performed separately for each individual fuel group. The results offer a different influence on each type of analysis. Finally, by considering both methods, most common correlating and non-correlating properties have been derived.