This paper describes a novel approach for modeling an automotive HVAC unit. The model consists of black-box models trained with experimental data from a self-developed measurement setup. It is capable of predicting the temperature and mass flow of the air entering the vehicle cabin at the various air vents. A combination of temperature and velocity sensors is the basis of the measurement setup. A measurement fault analysis is conducted to validate the accuracy of the measurement system. As the data collection is done under fluctuating ambient conditions, a review of the impact of various ambient conditions on the HVAC unit is performed. Correction models that account for the different ambient conditions incorporate these results. Numerous types of black-box models are compared to identify the best-suited type for this approach. Moreover, the accuracy of the model is validated using test drive data. This validation demonstrates the accuracy of the model of 2 K for temperature predictions. Further studies are recommended to quantify the impact of the model inaccuracies on the model-based calibration process.


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    Titel :

    Model-Based Calibration of an Automotive Climate Control System


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:
    Lassahn, Gerrit (Autor:in) / Qiu, Kang (Autor:in) / Jahn, Patrick (Autor:in)

    Kongress:

    WCX SAE World Congress Experience ; 2020



    Erscheinungsdatum :

    2020-04-14




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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