Review Of Human Thermal Comfort In Passenger Car Cabins: A Synergistic Analysis Of CFD Simulations And Experimental Testing

Abstract

Thermal comfort significantly impacts passenger satisfaction and overall driving experience in modern vehicles. With the increasing emphasis on energy efficiency and sustainability, optimizing vehicle HVAC systems has become critical. Computational Fluid Dynamics (CFD) simulations, combined with experimental testing, offer a robust framework to analyze and enhance thermal comfort in passenger car cabins. This review explores advancements in human thermal comfort studies, focusing on CFD simulations and experimental methodologies. The paper discusses key metrics, such as Predicted Mean Vote (PMV) and Predicted Percentage of Dissatisfied (PPD), and examines how airflow, temperature gradients, and radiant heat affect passenger comfort.

Additionally, this review highlights the role of advanced simulation tools like ANSYS Fluent, OpenFOAM, and STAR-CCM+ in predicting airflow patterns, temperature distribution, and heat transfer dynamics. Case studies showcasing successful integration of CFD and real-world testing are presented, providing insights into their applications in optimizing vent placement, airflow directionality, and thermal zoning. Challenges, such as the computational complexity of multi-parameter simulations and discrepancies between model predictions and real-world outcomes, are also addressed.