EFI controllers approximate complex, non-linear relationships between fuelling parameters, engine states and ambient conditions using linked tables or 'maps'. Determination of a single fuelling value generally requires interrogation of a number of maps and linear interpolation to determine intermediate values. Some types of Artificial Neural Network (NN) can model multi-dimensional arbitrary functions to any desired degree of accuracy, and interpolate smoothly. This paper demonstrates how Multi-Layer Perceptrons can approximate fuelling maps and trim tables, to produce smooth surfaces that model the data with good interpolation performance.


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    Titel :

    Neural networks - potential for enhanced control of automotive electronic fuel injection systems


    Weitere Titelangaben:

    Neuronale Netze bieten Potential für eine verbesserte Regelung elektronischer Kraftstoffeinspritzsysteme


    Beteiligte:
    Osman, K.A. (Autor:in) / Cole, A.C. (Autor:in) / Higginson, A.M. (Autor:in)


    Erscheinungsdatum :

    1999


    Format / Umfang :

    14 Seiten, 16 Bilder, 16 Quellen



    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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    Osman,K.A. / Cole,A.C. / Higginson,A.M. et al. | Kraftfahrwesen | 1999


    Neural Network Control of Automotive Fuel-Injection Systems

    Majors, M. / Stori, J. / Cho, D.-I. | British Library Online Contents | 1994


    Neural network control of automotive fuel-injection systems

    Majors, M. / Stori, J. / Cho, Dong-il | Tema Archiv | 1994



    Progress in electronic fuel injection control systems for automotive diesel engines

    Inoue,T. / Aoki,K. / Ikeda,S. et al. | Kraftfahrwesen | 1986