This article presents a novel method to simulate artificial driving cycles that have the same significant characteristics as measured driving cycles. The driving cycles are based on only two different easily accessible parameters namely mean velocity and mean positive acceleration as well as their standard variations. Those parameters allow to adapt the driving cycles to different cycle types (urban, extra urban, highway), length and duration. Other than know drive cycle simulators, the approach is based on normal distribution of velocities and accelerations, thus needing to analyze only few cycles for the initialization.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Artificial driving cycles for the evaluation of energetic needs of electric vehicles


    Contributors:


    Publication date :

    2012-06-01


    Size :

    349504 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Development of real-world driving cycles for battery electric vehicles

    Pfriem, Matthias / Gauterin, Frank | DataCite | 2016


    Selection of driving cycles for electric vehicles of the 1990s

    Liles, A.W. / Fettermann, G.P. | Tema Archive | 1976


    Electric motor control for hybrid electric vehicles based on different driving cycles

    Yi Hou / Ravey, Alexandre / Bouquain, David et al. | IEEE | 2013


    LVQ Neural Network Based Driving Cycles Recognition for Hybrid Electric Vehicles

    Xu, S.J. | British Library Conference Proceedings | 2013