Crash, Noise Vibration Harshness (NVH) and Computational Fluid Dynamics (CFD) are three pillars in Automotive Computer Aided Engineering (CAE). What these areas have in common is that they use numerical simulations to improve an initial design until it meets the specified requirements, and thus justifies the production of a physical prototype. These simulations require, depending on the application area, between a few hours on a multi-core system for NVH simulations, to several days on an HPC in CFD. Assuming a mid single-digit cent amount per core hour, this results in a price of a few euros up to several thousand euros per simulation, without considering the costs for the simulation code. Thus, archiving the simulation result is preferable to re-simulating also in terms of environmental protection. Depending on the field of application, the size of a simulation result varies between a few hundred MB and already reaches the terabyte range, especially in CFD. A proven approach to deal with large amounts of data is compression. Without data compression, for example, today's communication and work from a remote place with video calls and online presentations would be impossible. Lossy compression methods that have been specially developed for audio and video streams, exploit their properties for efficient compression depending on the available bandwidth and the quality required by the user. The outstanding compression rates, while maintaining good quality, can only be achieved by addressing and taking into account the specific characteristics of the data in question. In the present work, we compare different approaches for the compression of simulation results. For this purpose, we model dependencies of data points based on the simulation grid, simulation time and between simulation results. It is shown that the more dependencies are considered, the more effective compression can be implemented. In addition, we specifically address the properties that simulated data contain numerical and modelling errors and therefore the used precision of 32bit or 64bit for simulated post values is window dressing. Hence lossy compression is applicable. Justified by rate-distortion theory, it is possible to achieve higher compression factors by relaxing the requirements on the required precision for reconstruction. As particle-based solvers using SPH and FPM, respectively, become more and more important in CFD, we discuss compression techniques for mesh-free simulation results, next to modelling grid dependencies for NVH results, dependencies between time steps for CFD results, and dependencies between simulations for Crash results.