The automotive fan is a critical component of the cooling module, providing the majority of the cooling airflow over the heat exchangers and to underbody components at low speed, idle, and key-off conditions. Accurately predicting the performance of the automotive cooling fan is critical for sizing heat exchangers and ensuring that underhood and underbody components remain below target temperatures. This is normally done with computational fluid dynamics, but in a full-vehicle simulation it is impractical to model the rotation of the fan blades using a sliding mesh approach. Thus, simplified models which capture the fan behavior are employed. In this paper, a body force-type fan modeling approach is adopted and assessed. Many industrial fan models are calibrated based on experiments or higher-fidelity simulations. This can slow the design process. The approach employed eliminates this step, requiring only fan geometry information and no a-priori performance data. An existing body force modeling approach is used. It has been shown to be suitable for fans of the type typically used in automotive cooling systems. The model is analyzed and validated against computations including the blades. The model is then applied to simulations of the flow around and through an entire vehicle at a variety of speeds. The model predicts the flow rate through the radiator to within 8% of the experimentally-measured value at idle. At high vehicle speed, the accuracy improves to 1%. The accuracy of the uncalibrated model in predicting the radiator flow rate is comparable to the current best-practice calibrated fan modeling techniques used in the industry. The impact of the findings is a reduction in the overall effort involved in simulating under-hood and underbody flows.


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    Title :

    Suitability Assessment of an Uncalibrated Body Force Based Fan Modeling Approach to Predict Automotive Underhood Airflows


    Additional title:

    Sae Int. J. Adv. and Curr. Prac. in Mobility


    Contributors:

    Conference:

    SAE WCX Digital Summit ; 2021



    Publication date :

    2021-04-06


    Size :

    15 pages




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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