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    Area of Science:

    • Thermodynamics and Heat Transfer
    • Computational Engineering
    • Artificial Intelligence in Engineering

    Background:

    • Cooling system optimization is critical for applications like electric vehicle cabin and battery thermal management.
    • Multi-objective optimization in complex, non-linear systems is challenging due to large parameter spaces and long simulation times.
    • Existing methods often require semi-automatic, iterative approaches to handle simulation constraints and unmodeled factors.

    Purpose of the Study:

    • To present an interactive visual optimization approach for complex cooling systems.
    • To integrate deep learning (DL) for parameter estimation and numerical simulation for system characteristic computation.
    • To enhance user comprehension and accelerate optimization convergence through novel visualization techniques.

    Main Methods:

    • An iterative, guided optimization process steered by the user via a p-h diagram.
    • Utilizing a deep learning model to estimate system parameters based on target characteristics.
    • Employing numerical simulations to compute system characteristics for parameter ensembles.
    • Integrating a dual, interactive visual representation alongside the standard p-h diagram.

    Main Results:

    • The interactive visual approach facilitates user comprehension of the cooling system.
    • The method leads to faster convergence in the optimization process.
    • The dual visual representation effectively complements the p-h diagram, transferring its semantic meaning.
    • Multiple sets of intermediate solutions are generated and visually related, aiding the iterative process.

    Conclusions:

    • The proposed interactive visual optimization approach enhances understanding and efficiency in cooling system design.
    • The integration of DL models and advanced visualizations offers a powerful tool for complex engineering optimization.
    • This method shows significant promise for applications in the automotive industry, particularly for electric vehicles.