Search Results

Automobile manufacturers and suppliers are under pressure to develop more efficient thermal management systems as fuel consumption and emission regulations become stricter and buyers demand greater comfort and safety. Additionally, engines must be very efficient and windows must deice and defog quickly. These requirements are often in conflict. Moreover, package styling and cost constraints severely limit the design of coolant and air conditioning systems. Simulation-based design and virtual prototyping can ensure greater product performance and quality at reduced development time and cost. The representation of the vehicle thermal management needs a scalable approach with 0-D, 1-D, and 3-D fluid dynamics, multi-body dynamics, 3-D structural analysis, and control unit simulation capabilities. Different combinations and complexities of the simulation tools are required for various phases of the product development process.

The de-icing process of the windscreen is a demanding problem in car climatization. In the first stages of the development procedure of air ducts, the numerical simulation plays an important role due to economy of time and money. Unfortunately, the available numerical methods for the generation of the computational grid and the simulation of the de-icing process are very time consuming and are complicated in handling. Therefore normally the quality of the de-icing process is evaluated with simplified simulation procedures or even with measurements late in the design process and necessary modifications are again time and cost consuming. The aim of this paper is to describe new methods for the de-icing simulation that will reduce meshing and calculation time by showing accurate results.

Wet Clutches are used in automotive powertrains to enable compact designs and efficient gear shifting. During the slip phase of engagement, significant flash temperatures arise at the friction disc to separator interface because of dissipative frictional losses. An important aspect of the design process is to ensure the interface temperature does not exceed the material temperature threshold at which accelerated wear behavior and/or thermal degradation occurs. During the early stages of a design process, it is advantageous to evaluate numerous system and component design iterations exposed to plethora of possible drive cycles. A simulation tool is needed which can determine the critical operational conditions the system must survive for performance and durability to be assured. This paper describes a time-efficient multiphysics model developed to predict clutch disc temperatures with a runtime in the order of minutes.

This paper summarizes the results of several investigations on in-cylinder heat transfer during high-pressure and gas exchange phases as well as heat transfer in the inlet and outlet ports for a number of different engine types (DI Diesel, SI and gaseous fueled engine). The paper contains a comparision of simulation results and experimental data derived from heat flux measurements. Numerical results were obtained from zero-, one- and three-dimensional simulation methods. Time and spatially resolved heat fluxes were measured applying the surface temperature method and special heat flux sensors. The paper also includes an assessment of different sensor types with respect to accuracy and applicability.

In contrast to the well-established “standard” log-law wall function, the analytical wall function (AWF) as an advanced modelling approach has not been extensively used in the industrial computational fluid dynamics (CFD) applications. As the model was originally developed aiming at computations on relatively coarse meshes, potential stability issues may arise due to the pressure-gradient sensitivity if employing locally inappropriate mesh layers, typically associated with the complex geometry details. This work evaluates performance of the thermal AWF, as proposed by Suga [4], in conjunction with the main flow field computed employing the k-ζ-f turbulence model and the hybrid wall treatment (denoted as AWF-e) within the Reynolds-averaged Navier-Stokes (RANS) framework.