The roll angle of automotive vehicles is an important indicator for vehicle safety-related systems as well as vehicle dynamics assessment. However, its in-vehicle measurement is costly and therefore omitted for standard production vehicles. There exist several estimation methods that rely on simple linear roll models. Practically, these estimation techniques require exact knowledge of the plant parameters of the roll model. This work has presented two different methods that aim to identify a linear roll model using the measurement signals of lateral acceleration and roll rate. Once the identification is performed, the roll angle can be calculated e.g. by a trivial observer. The presented methods have been evaluated in simulation. They show high accuracy and can therefore be used instead of a roll angle sensor for vehicle dynamics assessment work. Aside from estimation of the roll angle the methods also provide parameters of a simple roll dynamics model that can be further used for offline simulation work. It is intended to implement them on a vehicle rapid prototyping system and determine their robustness to measurement noise on both input and output signals. As the algorithms are efficient in terms of required computational power their online implementation is straightforward.


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    Title :

    Robust vehicle roll dynamics identification based on roll rate measurements


    Contributors:


    Publication date :

    2012


    Size :

    7 Seiten, 8 Bilder, 29 Quellen



    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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