Diesel engines have been the major power source for medium- to heavy-duty ground vehicles due to superior fuel efficiency and durability over gasoline engines. However, Diesel engines are the main contributors for non-renewable Diesel fuel consumption and NOx and particulate matter (PM) emissions. Biodiesel fuel has been considered as a promising alternative fuel and can be directly fed into Diesel engines without major modifications. In addition, biodiesel has demonstrated lower hydrocarbon (HC), carbon monoxide (CO), and PM emissions than Diesel fuel. Nevertheless, the NOx emissions of biodiesel are generally higher. To meet stringent NOx emission regulation, urea-based selective catalytic reduction (SCR) systems have been widely utilized in Diesel-powered vehicles. The application of biodiesel fuel to Diesel engines can significantly change the exhaust condition and thus increase the complexity of SCR design and controls. This paper presents a fuel-adaptive nonlinear model predictive control (NMPC) method for selective catalytic reduction (SCR) system with biodiesel applications. A proper urea dosing strategy is derived as the solution of a NMPC problem such that both NOx and ammonia emission requirements can be met simultaneously. Experimental and simulation studies suggest the need to increase SCR size for biodiesel applications. Simulation results demonstrate the effectiveness of proposed NMPC-based controller for biodiesel applications. Such a SCR control strategy can be instrumental for reducing tailpipe emissions for flexible-fuel ground vehicles in the future.


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    Title :

    Model Predictive NOx Emission Control for a Biodiesel Engine Coupled with a Urea-based Selective Catalytic Reduction System


    Additional title:

    Sae Technical Papers


    Contributors:
    Chen, Pingen (author) / Ma, Yao (author)

    Conference:

    WCX SAE World Congress Experience ; 2019



    Publication date :

    2019-04-02




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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