3D fan modelling strategies for heavy duty vehicle cooling installations - CFD with experimental validation
Paper in proceedings, 2008
The need for low fuel consumption and lower emissions is for every automotive OEM a reality. With a cooling fan in today’s trucks that typically consumes of the order of magnitude 50bHp fully engaged – reducing this loss is very important. In addition a lot of the new after treatment systems requires a higher airflow through the engine bay, and new legislations requires quieter fans, i.e. today there is a need for fans with higher efficiency.
To reach these needs CFD offers great potential. However since computer power is still limited for resolving transient Navier-Stokes equations without any turbulence models and in a mesh-independent domain - one relies heavily on the performance of simplified assumptions and models. This is also what is addressed in this paper – an investigation of different fan modelling strategies and how these interfere with turbulence models and mesh-size.
Main focus is on modelling the fan with MRF (Multiple Reference Frames, stationary) and its behaviour compared to resolving the fan rotation in a rigid body rotation (transient). The turbulence models investigated is a number of the standard two equation models.
In the work comprised by this paper it was found that it is very difficult to get the fan MRF model to perform well in a complete vehicle installation, this due to a limited space for fitting a valid rotational domain for the fan – independent of choice of turbulence model and mesh size. Fully transient (URANS) sliding mesh approach performs well, even for small case sizes. It was found that a small transient case could outperform a well resolved stationary simulation, still consuming less CPU hours then the stationary.
Referring to the context of this work, the authors do not claim to deliver the final answer to fan modelling techniques. For the sliding mesh runs, a 2% discrepancy of measured pressure for a fixed air-flow was achieved in working points close to the fan’s design point. This would typically convert to a 1% error in mass flow in a case where the flow is not fixed by the boundary conditions, .i.e in a typical full vehicle under hood environment. In the fan stalling and fan transition regions, though, discrepancy was larger. However these areas are, to the authors’ knowledge and experience, hard to measure with good repetition, so a numerical issue in these regions is to be expected as well. More effort needs still to be made on producing more elaborate experimental data, not just measured for the system, but also component data such as radiator coefficients, larger meshes and more turbulence models should be evaluated in transient mode in order to predict these regions better. In conclusion, though, this paper gives a clear hint on what type of fan modelling strategy can be worth considering for UTM simulations in the upcoming future.
Underhood Thermal Management