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• W4386890504 abstract "The ultra-low NO x emission limits for heavy and mid-duty vehicles, which are expected to be imposed in both Europe and the USA by 2027, together with the enforcement of continuous decrease in CO 2 emission levels, make the need for adoption of newer technologies in the automotive industry imperative. To achieve low tailpipe NO x emissions, the accelerated warm-up of the exhaust aftertreatment system is of great importance. On the other hand, the thermal management strategies applied for this purpose result in fuel consumption penalty and consequently higher CO 2 as it can be widely found in the literature. Thus, the use and optimization of advanced thermal management technologies is critical to decrease the NO x – fuel penalty trade-off on the basis of complete driving cycles. In the present work an integrated modeled-based approach is implemented by coupling advanced, predictive 1D engine, and aftertreatment simulation models which are extensively validated via dedicated experimental data. The main goal of this approach is to define and investigate multiple engine or aftertreatment-based thermal management technologies, as well as a combination of them, creating a more efficient warm-up mode for the engine. Thermal measures such as cylinder deactivation, retarded start of the main injection, late intake valve closing (Miller cycle), intake throttling, elevated idle speed, and secondary fuel injection upstream the DOC are evaluated for their effect on the exhaust system heat-up time, the fuel consumption penalty and more importantly, for their impact on the tailpipe NO x emissions calculated by this holistic simulation approach." @default.
• W4386890504 created "2023-09-21" @default.
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• W4386890504 date "2023-09-20" @default.
• W4386890504 modified "2023-09-27" @default.
• W4386890504 title "Evaluation of thermal management technologies for fuel efficient cold-start emissions reduction in diesel engines" @default.
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• W4386890504 doi "https://doi.org/10.1177/14680874231196969" @default.
• W4386890504 hasPublicationYear "2023" @default.
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