Abstract The paper presents an innovative method combining artificial neural networks (ANNs) with Fuzzy PID to demonstrate the advantages of this control approach for meeting both NOx emission requirements and NH3 slip targets. An ANN model was utilized to simulate the formation of NOx emissions under various engine operating conditions. Next, an effective closed-loop control strategy with a type of feedback known as fuzzy PID is adopted for on-line, real-time control of 32.5% aqueous urea dosing in the exhaust stream. The new strategy explores the benefits by simulation and testing in the environments of Matlab/Simulink and ESC/ETC, respectively. The notable achievement of considerable NOx reduction and an acceptably small NH3 slip is obtained based on this new, feasible and effective strategy.


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    Titel :

    SCR control strategy based on ANNs and Fuzzy PID in a heavy-duty diesel engine


    Beteiligte:
    Zhang, S. M. (Autor:in) / Tian, F. (Autor:in) / Ren, G. F. (Autor:in) / Yang, L. (Autor:in)


    Erscheinungsdatum :

    2012




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch


    Klassifikation :

    BKL:    55.20$jStraßenfahrzeugtechnik / 55.20 Straßenfahrzeugtechnik



    SCR control strategy based on ANNs and Fuzzy PID in a heavy-duty diesel engine

    Zhang, S. M. / Tian, F. / Ren, G. F. et al. | British Library Online Contents | 2012


    SCR control strategy based on ANNs and Fuzzy PID in a heavy-duty diesel engine

    Zhang, S. M. / Tian, F. / Ren, G. F. et al. | Springer Verlag | 2012


    Heavy duty Diesel engine oil filterability

    Overton,R. / Rogers,W.N. / Esso Petroleum Canada,CA | Kraftfahrwesen | 1984


    Heavy Duty Diesel Engine Oil Filterability

    Overton, R. / Rogers, W.N. | SAE Technical Papers | 1984