Impact of density in simulation model for extreme cold ambient conditions

Battery Electric Vehicles (BEVs) necessitate highly efficient thermal management strategies, as cabin heating directly consumes energy from the finite traction battery, potentially reducing driving range significantly. Early-stage design evaluations of warmup performance commonly rely on one-dimensional (1D) simulations due to their computational speed and efficiency. The accuracy and predictive capability of these models are critically dependent on how well they represent blower operation and account for temperature-induced variations in air density. This fidelity is essential because engineers depend on warmup simulations to set HVAC targets that will deliver real‑world comfort and defrost performance within stringent range constraints. Earlier, warmup simulations employed a Constant Mass Flow (CMF) approach, which simplifies computations by assuming a fixed air density at a standard reference temperature. However, this approach contrasts with real-world blower behavior, where volumetric airflow remains relatively stable and air density changes dynamically with temperature. This study examines and compares four distinct modeling scenarios using a unified 1D simulation methodology. Case 1 utilizes the earlier CMF approach, maintaining constant density at standard reference temperature. In contrast, Cases 2–4 adopt a Constant Volume Flow (CVF) strategy, allowing density to vary with temperature to more accurately emulate real blower performance. Density calculations are based respectively on: (a) heater-inlet temperature, (b) the arithmetic mean of heater-inlet and heater-outlet temperatures, and (c) heater-outlet temperature. To isolate the effects of these modeling paradigms, all other boundary conditions, heat-source profiles, and control logics remain identical across scenarios. Simulation outputs are systematically compared against vehicle test data, with the delta difference (ΔT) in heater-out air temperature continuously monitored and summarized through graphs and error metrics. This comprehensive validation underscores the robustness and applicability of the presented 1D simulation framework for BEV cabin warmup analysis.