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The Diesel engine has now become a vital component of the transport sector, in view of its performance in terms of efficiency and therefore CO2 emissions some 25 % less than a traditional gasoline engine, its main competitor. However, the introduction of more and more stringent regulations on engine emissions (NOx, PM) requires complex after-treatment systems and combustion strategies to decrease pollutant emissions (regeneration strategies, injection strategies, …) with some penalty in fuel consumption. It becomes necessary to find new ways to improve the Diesel efficiency in order to maintain its inherent advantage. In the present work, we are looking for strategies and technologies to reduce Diesel engine fuel consumption. Based on the observation that large Diesel engines have a better efficiency than the smaller ones, a detailed thermodynamic combustion analysis of one Heavy Duty (HD) engine and two Passenger car (PC) engines is performed to understand these differences.

In a Diesel engine with a Diesel particulate filter (DPF) system, high-sulfur fuel causes white smoke containing odorous and harmful pollutants during DPF regeneration. This study investigates the conditions and mechanisms of sulfur-related white smoke generation. Engine and vehicle tests found that sulfur compounds emitted from the engine accumulated on the catalysts in the DPF system and were emitted as white smoke during DPF regeneration. The white smoke was observed when the catalyst temperature was more than 450°C, under conditions such as the early stage of DPF regeneration. Model gas tests were conducted to clarify the mechanism of the white smoke. It was found that SO2 emitted from the engine was oxidized to SO3 on the catalyst, which was then mainly absorbed on the oxidation catalyst support (Al2O3). Then, the absorbed SO3 was desorbed and converted into white smoke.

With the increase of heavy-duty transportation, more fuel efficient technologies and services have become of great importance due to their environmental and economical impacts for the fleet managers. In this paper, we first develop a new analytical model of the heavy-truck for its dynamics and its fuel consumption, and valid the model with experimental measurements. Then, we propose a bi-level optimization approach to reduce the fuel consumption, thus the CO2 emissions, while ensuring several safety constraints in real-time. Numerical results show that important reduction of the fuel consumption can be achieved, while satisfying imposed safety constraints.