The study on the driving cycle and powertrain of electric vehicle presents the conclusion that there is a regular working area on efficiency map where electric motor works for the most time. Thus, two motivations are proposed: first, to evaluate the efficiency map of electric motor analytically, second, to design an electric motor whose maximum efficiency area on efficiency map covers its regular working area. To evaluate motor efficiency map, three tasks have to be completed: calculating torque-speed characteristic, calculating losses, studying on motor control strategy. For in-wheel application, surface-mounted permanent magnet motor with fractional-slot concentrated-windings is adopted. Its torque-speed profile of flux-weakening control is calculated. Different methods of losses calculation are compared and the results are presented. Motor control strategy is studied to obtain the input electric parameters of other operating points within the torque-speed profile. To design the motor, driving cycle and powertrain of electric vehicle are analyzed. Multi-objective optimization is utilized to obtain the optimal motor design. Different factors impacting motor efficiency map are discussed. The motor designs are compared to illustrate the loss balance of electric motor. Motor design and analytic results are validated in powertrain calculation and finite element calculation. Flux-weakening control is implemented. The co-simulation model is built up for further study to calculate the dynamic efficiency of driving cycle. A prototype with similar typology and winding layout is manufactured. Some preliminary experiment results are presented and compared with analytic results.


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    Titel :

    FRACTIONAL-SLOT CONCENTRATED-WINDING SURFACE-MOUNTED PERMANENT MAGNET MOTOR DESIGN AND ANALYSIS FOR IN-WHEEL APPLICATION


    Beteiligte:
    Li, Zijian (Autor:in)

    Erscheinungsdatum :

    2012-01-01


    Anmerkungen:

    doi:10.6092/polito/porto/2497418



    Medientyp :

    Hochschulschrift


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    600 / 629



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