Automatic Transmissions managements are often based on throttle position and vehicle speed and mainly aim to reduce fuel consumption and carbon dioxide (CO2) emissions, in vehicles equipped with Internal Combustion Engines (ICE). This is an important goal from two viewpoints: fuel economy and greenhouse gases (GHG) containment, with benefits in terms of global warming and climate change. At the same time, traffic stops are due to the detection of other pollutants, as nitrogen oxides (NOx) and particulate matter (PMx), which are harmful for human health. This is particularly true in urban areas, especially during traffic jams. Moreover, localized high levels of the pollutants produced may not be detected by conventional and relatively far air quality detection stations.In this paper, a solution to efficiently detect air quality parameters near the vehicles is proposed, with the development of on-board low-cost monitoring air quality systems and a Vehicle to Vehicle (V2V) communication. Based on such data, an estimation of the pollutant to be contained is made and communicated to surrounding vehicles. Hence, their behaviors are modulated thanks to the Map-Driven Automatic Transmission (AT) Management, with a gear selection strategy that enforces the engine to operate in the lower part of a given map. From this viewpoint, a detailed Matlab/Simulink model of the vehicle was developed and validated against experimental data. Then, the AT strategy was tested in order to demonstrate its effectiveness, both on terms of fuel economy and GHG emissions or containment of a particular pollution, if required.


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    Titel :

    A Map-Driven Automatic Transmission for Selective Emissions Reduction in ICE Vehicles


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:

    Kongress:

    Conference on Sustainable Mobility ; 2022



    Erscheinungsdatum :

    2022-09-16




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch





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