The study introduces a surrogate model capable of reproducing complex computational fluid dynamics simulations with significantly lower computational effort. By relying on simulation data and advanced modelling techniques, the approach allows for faster evaluation of airflow patterns, temperature distribution, and thermal comfort conditions inside the cabin. This enables more efficient design iterations and supports the development of smarter HVAC strategies.

As HVAC systems represent a major share of auxiliary energy consumption in electric vehicles, improving their performance is essential to extending driving range. The proposed model allows engineers to explore a wide range of configurations and operating scenarios, helping identify solutions that balance comfort and efficiency without the need for time-intensive simulations.

This work reflects the broader objectives of the 2Zero project, which aims to accelerate the transition to climate-neutral mobility through innovation in vehicle technologies and digital tools. By enabling faster and more flexible design processes, data-driven models such as this one can play a key role in bringing more efficient electric vehicles to market.

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