Abstract In controlling the longitudinal motion of electrified vehicles such as hybrid vehicles and PHEV (Plug-in Hybrid Electric Vehicles), the variation of the driving resistance loads (or driving loads) such as road grade and actual vehicle mass, is the most influential factor which limits the control performance. Measuring the driving load is not impossible, but it is costly since additional sensors have to be mounted on the vehicle. In this study, methods for estimating vehicle mass and road grade are designed to compensate for the driving loads. The proposed methods are verified using simulation tools and then evaluated experimentally.


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    Titel :

    Development of estimation algorithms for vehicle’s mass and road grade


    Beteiligte:
    Kim, I. (Autor:in) / Kim, H. (Autor:in) / Bang, J. (Autor:in) / Huh, K. (Autor:in)


    Erscheinungsdatum :

    2013




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch


    Klassifikation :

    BKL:    55.20$jStraßenfahrzeugtechnik / 55.20 Straßenfahrzeugtechnik



    Development of estimation algorithms for vehicle’s mass and road grade

    Kim, I. / Kim, H. / Bang, J. et al. | Springer Verlag | 2013


    Development of estimation algorithms for vehicle’s mass and road grade

    Kim, I. / Kim, H. / Bang, J. et al. | British Library Online Contents | 2013


    Development of algorithms for commercial vehicle mass and road grade estimation

    Kim, Seungki / Shin, Kyungsik / Yoo, Changhee et al. | Springer Verlag | 2017


    Development of algorithms for commercial vehicle mass and road grade estimation

    Kim, Seungki / Shin, Kyungsik / Yoo, Changhee et al. | Online Contents | 2017


    Development of algorithms for commercial vehicle mass and road grade estimation

    Kim, S. / Shin, K. / Yoo, C. et al. | British Library Online Contents | 2017