Intelligent Cabins – Energy Efficiency and Passenger Comfort in BEVs

Abstract

This technical report investigates strategies for enhancing energy efficiency and occupant thermal comfort in Battery Electric Vehicle (BEV) cabins during cold climate operations. Using high-fidelity Computational Fluid Dynamics (CFD) in STAR-CCM+, the study characterizes the complex relationship between HVAC parameters, specifically inlet temperature and mass flow rates, and human physiological responses. The research integrates advanced thermo-physiological models, including the Fiala and Berkeley models, to provide a detailed analysis of local thermal sensation and comfort across diverse occupant demographics. Key findings from the parametric study indicate that a vane inlet temperature of 32 °C, resulting in an average cabin temperature of approximately 24.6 °C, provides the highest thermal comfort for both male and female occupants, achieving a Predicted Percentage of Dissatisfied (PPD) of nearly 5 %. The study demonstrates that while adjustments to the ventilation mass flow rate have a negligible impact on occupant comfort, reducing the flow from 0.2 kg/s to 0.1 kg/s can yield measurable energy savings, potentially extending vehicle range by 3–5 km during winter driving. Additionally, the results highlight the significant influence of solar loads on thermal perception, noting that occupants feel “chilly” at 24 °C when radiative heating is absent. This work serves as a foundation for designing intelligent, occupancy-aware climate control systems that balance passenger well-being with vehicle performance.