André L. Boehman’s research while affiliated with University of Michigan and other places

The U.S. Department of Energy Supertruck 2 program placed emphasis on development of heavy-duty trucks with high freight efficiency using commercially realizable technology suites. This paper describes the research and development process used to pursue a high thermal efficiency heavy-duty engine under Supertruck 2 . The team focused on over-expanded engine cycles and advanced piston designs. This paper describes how single-cylinder engine studies using thermal barrier coated pistons, high compression pistons, and over-expanded cycles informed the development process of a multi-cylinder demonstration engine that achieved 49.9% peak thermal efficiency. While tailoring the injection strategy and other control parameters optimized the demonstration engine, more than half of the efficiency improvement came from the over-expanded cycle.

div>Dimethyl ether (DME) is an alternative fuel that, blended with propane, could be an excellent alternative for exploring the use of fuels from renewable sources. DME–propane blends are feasible for their comparable physicochemical properties; these fuels may be pressured as liquids using moderate pressure at ambient temperature. Adding a proportion of DME with a low octane number to a less reactive fuel like propane can improve the combustion process. However, the increased reactivity of the mixture induced by the DME could lead to the early appearance of knocking, and this tendency may even be pronounced in boosted SI engines. Hence, this study experimentally analyzes the effect of E10 gasoline (baseline) and DME–propane blends, with varying proportions of DME in propane ranging from 0% to 30% by weight, in increments of 5% on knocking tendency, combustion characteristics, gaseous emissions, and particle number concentration, under different intake pressure conditions (0.8, 0.9, 1.0, and 1.1 bar) in an SI engine. The results show that as the proportion of DME in the propane blend rises, the knocking tendency becomes more pronounced. That behavior intensifies with increasing intake pressure, but with 20% DME in the propane blend, reaching the maximum brake torque (MBT) without knocking in the four boosted conditions is feasible. The presence of knock limited the advance of combustion phasing and decreased the gross indicated thermal efficiency (ITEg) with E10 gasoline and 25% and 30% DME in propane blends under 1.0 and 1.1 bar boosted conditions. In these knock-limited circumstances, the NOx emissions decreased due to the retarded phasing, and THC and PN emissions increased due to the lower combustion stability, considerably raising the concentration of accumulation mode particles in the particle size distribution (PSD) compared to the other fuel blends tested.</div

The prohect goal is to develop and demonstrate a microalgae bio-blendstock with greater than 60% greenhouse gas reduction potential relative to petroleum diesel, that can reduce sooting propensity, increase cetane number and improve engine thermal efficiency relative to a baseline diesel engine operating on conventional fuel.

Aquatic microalgae are a highly promising feedstock for the production of biocrude and tailored biofuels, with distinct advantages over traditional terrestrial crops, such as reduced land use and avoidance of food production competition. However, unlocking their full potential requires the development of biofuels with low life cycle greenhouse emissions biofuels, such as algae biofuels, which can significantly reduce the environmental impact of the transportation systems without requiring a complete overhaul of existing engine technology. In this study, we employ cutting-edge data-based AI modeling techniques to optimize the performance of heavy-duty engines, with a focus on transitioning towards biofuels with low life cycle greenhouse emissions biofuels. Our methodology offers significant advantages over traditional sweep testing, enabling efficient and accurate optimization of engine performance with minimal time and resources consumption. Our findings demonstrate the potential of utilizing this approach, with up to 55% NOx emissions reductions and up to 2% reduction in fuel consumption compared to the baseline optimized point. Moving forward, we plan to utilize a 30% blend of algae biofuels with diesel fuel, with the ultimate goal of achieving up to 60% lifecycle GHG emissions. Lastly, we plan to compare the results with 100% renewable biodiesel to add an additional dimension of investigating the impact of fuel chemistry on engine optimization. Overall, this study underscores the vital importance of biofuels for reducing the carbon footprint of the transportation sector and supporting a sustainable future. By harnessing the power of data-based AI modeling with low life cycle greenhouse emissions biofuels, we can accelerate the adoption of more environmentally friendly transportation systems and reduce their impact on the planet. Our findings contribute to this transition and offer insights for developing efficient and effective strategies for addressing global climate change.