An electric vehicle model has been developed with four direct-drive in-wheel motors. A high-level vehicle stability controller is proposed, which uses the principles of fuzzy logic to determine the corrective yaw moment required to minimize the vehicle sideslip and yaw rate errors. A genetic algorithm has been used to optimize the parameters of the fuzzy controller. The performance of the controller is evaluated as the vehicle is driven through a double-lane-change maneuver. Preliminary results indicate that the proposed control system has the ability to improve the performance of the vehicle considerably.


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    Titel :

    Integrated Stability Control System for Electric Vehicles with In-wheel Motors using Soft Computing Techniques


    Weitere Titelangaben:

    Sae International Journal of Passenger Cars- Electronic and Electrical Systems
    Sae Int. J. Passeng. Cars – Electron. Electr. Syst


    Beteiligte:
    McPhee, John (Autor:in) / Jalali, Kiumars (Autor:in) / Lambert, Steve (Autor:in) / Uchida, Thomas (Autor:in)

    Kongress:

    SAE World Congress & Exhibition ; 2009



    Erscheinungsdatum :

    2009-04-20


    Format / Umfang :

    11 pages




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch





    2009-01-0435 Integrated Stability Control System for Electric Vehicles with In-Wheel Motors using Soft Computing Techniques

    Jalali, K. / Uchida, T. / McPhee, J. et al. | British Library Conference Proceedings | 2009



    Control of electric vehicles using two in-wheel motors

    Wu, Feng-Kuang / Yeh, T.J. | Tema Archiv | 2010


    Development of an Advanced Torque Vectoring Control System for an Electric Vehicle with In-Wheel Motors using Soft Computing Techniques

    Jalali, K. / Uchida, T. / Lambert, S. et al. | British Library Conference Proceedings | 2013