Browse Publications Technical Papers 2019-01-0348
2019-04-02

Obtaining Precise Churning Loss for a Gearbox Using Advanced Smoothed Particle Hydrodynamics 2019-01-0348

Last decades of the car design was a continuous, slow process. However, recent years, due to the electrification of engines, the design requires a very fast adaptation/modification of old technologies to fit to the requirements. What is more, many times, the new technologies have to be developed from scratch. One of the most important elements, which radically changes last years are the drive transmission systems. In order to help in fast development of novel powertrains, the ability of making fast and accurate Computational Fluid Dynamics analysis is of high importance. The vast majority of the commonly used CFD solvers are based on Eulerian approaches (grid-based). These methods are, in general, efficient with some drawbacks, e.g. it is necessary to handle additionally the location of the interface or free-surface within computational cells. Very promising alternatives to the Eulerian methods are Lagrangian approaches which, roughly speaking, discretize fluid instead of domain. One of the most common methods of this kind is the Smoothed Particle Hydrodynamics (SPH) method, a fully Lagrangian, particle-based approach for fluid-flow simulations. One of its main advantages over the Eulerian techniques is no need for a numerical grid. Consequently, there is no necessity to handle the interface shape because it is directly obtained from the set of the computational particles. Due to this, there is no additional numerical diffusion related to the interface handling. Another advantage of the SPH method over grid-based method is the easiness to handle the moving objects. The biggest disadvantage of this approach – efficiency, can be easily overcame by accelerating via GPUs. In the present work, we deeply analyze the advantages and drawbacks of applying the SPH approach to model the power train systems. The presented results of analysis will supported by experiments.

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