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A holistic concept for design and implementation of in-vehicle networks using the standardized CAN and LIN communication protocols has been developed, taking into account recent findings from real-time research. The Volcano concept relies on an integrated chain of high-level tools and carefully engineered software. The total chain provides requirement capture, model based design, automatic code generation and system level validation capabilities. Guaranteed “Design to correctness” capability in complex distributed architecture is a unique capability of Volcano helping to reduce unit cost, shorten design time and improve quality. The concept is successfully used in production since 1998.

For the computation of the flow around a car there is typically an overprediction of stagnation and base pressure coefficient by 0.02 and 0.07 respectively causing an underprediction of total drag by about 0.01 - 0.02. To determine the cause of the error in stagnation pressure several different effects have been investigated: length of inlet section, boundary conditions on the floor, mesh resolution, turbulence models and different flow solvers. One major effect was found to be a short inlet section in the computational model, which caused an overprediction of the stagnation pressure. The second major effect was insufficient resolution of the mesh along the stagnation line. More than 100 nodes along the stagnation line were necessary to avoid a significant pressure drop. Finally the k-ε turbulence model caused overprediction of total pressure very close to the stagnation point. The use of an explicit algebraic Reynolds stress model removed this error.

Computations of the flow around a basic car shape, the Volvo ECC, have been done using different turbulence models: two lowRe k-ε model, the standard k-ε model and the IP and Gibson-Launder version of the Reynolds Stress Model (RSM). Results from the different computations are compared to windtunnel measurements of drag, pressure and velocity. The effect of the turbulence model on the accuracy of predicted pressure and drag is studied. To provide a basis for this work grid refinement studies have been performed to study the effect of mesh resolution and mesh quality on the error in pressure and drag. It is shown that mesh quality is important to preserve the order of the difference schemes but that the grid related error may be virtually eliminated. Further the computations show that a lowRe k-e model yields the best prediction of experimental data.