Piovano, A., Lorefice, L., and Scantamburlo, G., "Modelling of Car Cabin Thermal Behaviour during Cool Down, Using an Advanced CFD/Thermal Approach," SAE Technical Paper 2016-01-0213, 2016, doi:10.4271/2016-01-0213.
The aim of this work has been to develop an advanced methodology to model the car cabin cool down test. It has been decided to focus the attention on the fluid dynamics and thermal dynamics aspects of the phenomenon, trying to catch the correct heat transfer between the outside environment and the internal cabin with a thermal tool, together with an internal flows CFD simulation.To start with, an experimental cool down test was conducted in the FCA Italy climatic wind tunnel on a L0 segment vehicle, to get the correlation data and the boundary conditions required for the simulation: panel ducts air transient temperatures, wind tunnel air temperature and velocity, solar array load.The simulation was divided into two steps: steady state soak with a finite difference based thermal solver and transient cool down, coupling the thermal solver with a CFD one. In particular an advanced CFD/thermal coupled approach has been applied, using STAR-CCM+® and TAITherm® tools.For the thermal simulation, the vehicle surface mesh model used includes the internal cabin surfaces and the complete external body, while for the CFD steps the focus has been on the internal flows. An external aerodynamics CFD simulation has been run to get the external HTC values. FCA simplified manikins have been inserted in both test and simulation, in order to compare the air temperatures on the stickmen air thermocouples with the experimental data.The work on the CFD/Thermal coupling parameters, cabin thermal model, environmental conditions, CFD mesh and boundary conditions, has been performed to obtain even better results on cabin air temperatures and on all the internal points near to the panel outlets, including the stickmen high parts. Moreover the influence of critical boundary conditions and parts modelling has been investigated to evaluate a possible reduction of simulation complexity.