This paper describes the design and verification of a sliding mode observer to estimate the state information of the angular velocity and load torque for a motorized seat belt (MSB) system. The MSB system is a type of active safety system which provides functions to protect passengers and improve passenger convenience. To realize the full range of operations of a MSB system, several types of state information such as the motor current, angular velocity and load torque of the DC motor, the seat belt winding velocity and the position and temperature of the DC motor are necessary. Measuring this state information with sensors leads to an increase in both the system cost and its complexity. Furthermore, it is difficult to measure the load torque of a DC motor, which must be done in order to realize the full range of MSB functions. In this paper, a sliding mode observer is designed and verified to estimate the angular velocity of a DC motor and the load torque, both of which are necessary state information to realize the basic operation of a MSB system without sensors. In addition, a MSB retraction control algorithm with estimated state information is proposed.


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    Titel :

    Retraction Control of Motorized Seat Belt System with Sliding Mode Observer


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:
    Lee, Kangseok (Autor:in) / Bae, Kyutae (Autor:in) / Lee, Wootaik (Autor:in)

    Kongress:

    SAE 2012 World Congress & Exhibition ; 2012



    Erscheinungsdatum :

    16.04.2012




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




    Retraction Control of Motorized Seat Belt System with Sliding Mode Observer

    Lee, K. / Bae, K. / Lee, W. et al. | British Library Conference Proceedings | 2012



    State estimation for motorized seat belt system using sliding-mode observer

    Lee, K. S. / Lee, W. T. | British Library Online Contents | 2015



    MOTORIZED SEAT BELT SYSTEM

    SON SANG OCK / LEE SOO CHUL | Europäisches Patentamt | 2017

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