The safety, performance, and operational life of power dense Lithium-ion batteries used in Hybrid and Electric Vehicles are dependent on the operating temperature. Modeling and simulation are essential tools used to accelerate the design process of optimal thermal management systems. However, high-fidelity 3D computational fluid dynamics (CFD) simulation of such systems is often difficult and computationally expensive. In this paper, we demonstrate a multi-part coupled system model for simulating the heating/cooling system of the traction battery at a module level. We have reduced computational time by employing reduced-order modeling (ROM) framework on separate 3D CFD models of the battery module and the cooling plate. The order of the thermal ROM has also been varied to study the trade-off between accuracy, fidelity, and complexity. The ROMs are bidirectionally coupled to an empirical battery model built from in-house test data. This makes sure that we capture the interdependence of different parameters and behaviors and closely resemble the real system behavior. The complete system model is built up in a commercial system simulation platform and has the capability of simulating the system response to drive-cycles, charge profiles or any system dependent test conditions, under the influence of various heating/cooling control algorithms.


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    Titel :

    Thermal Reduced Order Modeling for System Analysis of EV Battery


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:
    Majumdar, Abhigyan (Autor:in) / Wakale, Anil (Autor:in) / Ding, Peiran (Autor:in) / Pawar, Pranav (Autor:in) / Jiang, Weiran (Autor:in) / Hu, Xiao (Autor:in)

    Kongress:

    WCX SAE World Congress Experience ; 2023



    Erscheinungsdatum :

    11.04.2023




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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