Abstract Estimation algorithms for road slope angle and vehicle mass are presented for commercial vehicles. It is well known that vehicle weight and road grade significantly affect the longitudinal motion of a commercial vehicle. However, it is very difficult to measure the weight and road slope angle in real time because of lack of sensor technology. In addition, the total weight of a commercial vehicles varies depending on the freight. In this study, the road grade and vehicle mass estimation algorithms are proposed using the RLS (Recursive Least Square) method and only the in-vehicle sensors. The proposed algorithms are verified in experiments using a commercial vehicle under various conditions.


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    Titel :

    Development of algorithms for commercial vehicle mass and road grade estimation


    Beteiligte:
    Kim, Seungki (Autor:in) / Shin, Kyungsik (Autor:in) / Yoo, Changhee (Autor:in) / Huh, Kunsoo (Autor:in)


    Erscheinungsdatum :

    2017




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch


    Klassifikation :

    BKL:    55.20$jStraßenfahrzeugtechnik / 55.20 Straßenfahrzeugtechnik



    Development of algorithms for commercial vehicle mass and road grade estimation

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


    Development of algorithms for commercial vehicle mass and road grade estimation

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


    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 estimation algorithms for vehicle’s mass and road grade

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