Efficient modelling of complex multi-phase fluid-flows is one of todays most common engineering challenges. The vast majority of commercial CFD solvers are based on Eulerian grid-based approaches. In general, these methods are efficient but their have many drawbacks, e.g. it is necessary to additionaly handle the location of the interface or free-surface within computational cells. Very promising alternatives to the Eulerian methods are Lagrangian approaches which, generally speaking, discretize the fluid instead of the whole domain. One of the most common methods of this kind is the Smoothed Particle Hydrodynamics (SPH) method. This is a fully Lagrangian, particle-based approach for fluid-flow simulations. One of its main advantages over Eulerian techniques is that there is no need for numerical grids. Consequently, there is no need to handle the interface shape (contrary to Volume-Of-Fluid, Level-Set, or Front-Tracking methods), because it is directly obtained from the set of computational particles. Due to this, there is no additional numerical diffusion related to the interface handling. Thus, the SPH method is increasingly used for hydro-engineering and geophysical applications involving free-surfaces and multi-phase flows. One disadvantage of the SPH method compared to the grid-based approaches is in the numerical efficiency of the solver. However, in most cases involving complex geometries, the human time needed to create computational grids can be so large, that it becomes more time- and cost-efficient to perform calculations using SPH. Furthermore, in recent years new techniques allowing numerical simulations to be performed using Graphics Processing Units (GPU) have been developed. The massive parallelization capabilities of modern GPUs allow simulations of large systems to be performed using low cost desktop computers. Since the SPH method is easy to write in a parallel manner, we decided to create our SPH simulation framework using Nvidia CUDA technology. During this presentation, we will discuss the potential advantages and disadvantages of using the SPH method for solving typical problems that may arise in the automotive industry. Some of the very promising applications that will be discussed include: fluid flow through a pipe (fuel tank filling), gearbox modelling and water management on a car body (rain model). The major part of this presentation will be devoted to discussing the advantages and disadvantages of SPH modelling using low cost desktop GPU devices.