Vehicle mass and road gradient are the important parameters for engine torque control, transmission shift scheduling and vehicle longitudinal control. It will add manufacturing cost to use more sensors to obtain these values. Therefore, there is increasing concern on the estimation methods of vehicle mass and road gradient based on the vehicle model. In this paper, on the premise of no additional sensors, the engine torque, engine speed, velocity, acceleration/brake/clutch pedal signals and gear from the CAN bus are used as the original data. The estimation methods of vehicle mass and road gradient are studied by applying vehicle dynamic, Luenberger state observer and Recursive Least Square with varying forgetting factors. Furthermore, the real time estimation arithmetic is validated through dSPACE/MicroAutoBox system on FAW J5 commercial vehicle.


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    Title :

    Study on State Parameters Estimation for Commercial Vehicle


    Contributors:
    Liu, Li (author) / Huang, Chaosheng (author) / Li, Yuanfang (author) / Shi, Shuming (author)


    Publication date :

    2012


    Size :

    13 Seiten





    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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