Search Results

This paper presents calculations of engine flows by using the Partially-Averaged Navier Stokes (PANS) method (Girimaji [1]; [2]). The PANS is a scale-resolving turbulence computational approach designed to resolve large scale fluctuations and model the remainder with appropriate closures. Depending upon the prescribed cut-off length (filter width) the method adjusts seamlessly from the Reynolds-Averaged Navier-Stokes (RANS) to the Direct Numerical Solution (DNS) of the Navier-Stokes equations. The PANS method was successfully used for many applications but mainly on static geometries, e.g. Basara et al. [3]; [4]. This is due to the calculation of the cut-off control parameter which requires that the resolved kinetic energy is known and this is usually obtained by suitably averaging of the resolved field. Such averaging process is expensive and impractical for engines as it would require averaging per cycles.

Reynolds-averaged Navier-Stokes (RANS) computations of heat transfer involving wall bounded flows at elevated Prandtl numbers typically suffer from a lack of accuracy and/or increased mesh dependency. This can be often attributed to an improper near-wall turbulence modeling and the deficiency of the wall heat transfer models (based on the so called P-functions) that do not properly account for the variation of the turbulent Prandtl number in the wall proximity (y+< 5). As the conductive sub-layer gets significantly thinner than the viscous velocity sub-layer (for Pr >1), treatment of the thermal buffer layer gains importance as well. Various hybrid strategies utilize blending functions dependent on the molecular Prandtl number, which do not necessarily provide a smooth transition from the viscous/conductive sub-layer to the logarithmic region.

The presented paper deals with a methodology to model cycle-to-cycle variations (CCV) in 0-D/1-D simulation tools. This is achieved by introducing perturbations of combustion model parameters. To enable that, crank angle resolved data of individual cycles (pressure traces) have to be available for a reasonable number of engine cycles. Either experimental data or 3-D CFD results can be applied. In the presented work, experimental data of a single-cylinder research engine were considered while predicted LES 3-D CFD results will be tested in the future. Different engine operating points were selected - both stable ones (low CCV) and unstable ones (high CCV). The proposed methodology consists of two major steps. First, individual cycle data have to be matched with the 0-D/1-D model, i.e., combustion model parameters are varied to achieve the best possible match of pressure traces - an automated optimization approach is applied to achieve that.

Future demands regarding emissions, fuel consumption and driveability lead to complex engine and power train control systems. The calibration of the increasing number of free parameters in the ECU's contradicts the demand for reduced time in the power train development cycle. This paper will focus on the automatic, unmanned closed loop optimization of driveability quality on a high dynamic engine test bed. The collaboration of three advanced methods will be presented: Objective real time driveability assessment, to predict the expected feelings of the buyers of the car Automatic computer assisted variation of ECU parameters on the basis of statistical methods like design of experiments (DoE). Thus data are measured in an automated process allowing an optimization based on models (e.g. neural networks).

The present paper deals with the application of the LES approach to in-cylinder flow modeling. The main target is to study cycle-to-cycle variability (CCV) using 3D-CFD simulation. The engine model is based on a spark-ignited single-cylinder research engine. The results presented in this paper cover the motored regime aiming at analysis of the cycle-resolved local flow properties at the spark plug close to firing top dead center. The results presented in this paper suggest that the LES approach adopted in the present study is working well and that it predicts CCV and that the qualitative trends are in-line with established knowledge of internal combustion engine (ICE) in-cylinder flow. The results are evaluated from a statistical point of view based on calculations of many consecutive cycles (at least 10).

Aerodynamic properties of a BMW car model taking over a truck model are studied computationally by applying the scale-resolving PANS (Partially-averaged Navier-Stokes) approach. Both vehicles represent down-scaled (1:2.5), geometrically-similar models of realistic vehicle configurations for which on-road measurements have been performed by Schrefl (2008). The operating conditions of the modelled ‘on-road’ overtaking maneuver are determined by applying the dynamic similarity concept in terms of Reynolds number consistency. The simulated vehicle configuration constitutes of a non-moving truck model and a car model moving against the air flow, the velocity of which corresponds to the car velocity.

Rattle noise produced in the vehicle interior due to broadband excitation by road irregularities is a major concern with respect to driving comfort, and therefore has become one of the most important topics of acoustic development in recent years. A quantification i.e. measurement of this rattle noise is of fundamental importance for systematic development work and production control. Common noise level measurements (dB, dBA, etc. ) do not represent the rattle character in the vehicle interior as revealed during initial investigations. To overcome this problem and to substitute the subjective assessment with a combination of measurable parameters, the psychoacoustic software AVL-EAR was applied to create an Interior Rattle Quality Index. Based on more than 40 different vehicles that have been subjectively assessed by approximately 70 test persons, the index was generated by means of multiple pair comparisons and statistics on measurement data.

The demand for high efficiency powertrains in automotive engineering is further increasing, with hybrid powertrains being a feasible option to cope with new legislations. So far hybridization has only played a minor role for L-category vehicles. Focusing on an exemplary high-power L-category on-road vehicle, this research aims to show a new development approach, which combines longitudinal dynamic simulation (LDS) with “Design of Experiments” (DoE) in course of hybrid electric powertrain development. Furthermore, addressing the technological aspect, this paper points out how such a vehicle can benefit from 48V-hybridization of its already existing internal combustion powertrain. A fully parametric LDS model is built in Matlab/Simulink, with exchangeable powertrain components and an adaptable hybrid operation strategy. Beforehand, characterizing decisions as to focus on 48V and on parallel hybrid architecture are made.

The combustion efficiency of large gas engines is limited by knocking combustion. Due to fact that the quality of the fuel gas has a high impact on the self-ignition of the mixture, it is the aim of this work to model the knocking combustion for fuel gases with different composition using detailed chemistry. A cycle-resolved knock simulation of the fast burning cycles was carried out in order to assume realistic temperatures and pressures in the unburned mixture Therefore, an empirical model that predicts the cyclic variations on the basis of turbulent and chemical time scales was derived from measured burn rates and implemented in a 1D simulation model. Based on the simulation of the fast burning engine cycles the self-ignition process of the unburned zone was calculated with a stochastic reactor model and correlated to measurements from the engines test bench. A good agreement of the knock onset could be achieved with this approach.

The aim of this paper is to present the adjoint equations for shape optimization derived from steady incompressible Navier-Stokes (N-S) equations and an objective functional. These adjoint Navier-Stokes equations have a similar form as the N-S equations, while the source terms and the boundary conditions depend on the chosen objective. Additionally, the gradient of the targeted objective with respect to the design variables is calculated. Based on this, a modification of the geometry is computed to arrive at an improved objective value. In order to find out, whether a more sophisticated approach is needed, the adjoint equations are derived by using two different approaches. The first approach is based on the frozen turbulence assumption and the second approach, which is advanced in this paper, is derived from the near wall k − ζ − f turbulence model.

This paper presents calculations of external car aerodynamics by using the Partial-Averaged Navier-Stokes (PANS) variable resolution model in conjunction with the finite volume (FV) immersed-boundary method. The work presented here is the continuation of the study reported in Basara et al. [1]. In that work, it was shown that the same accuracy of predicted aerodynamic forces can be achieved by using Reynolds-Averaged Navier-Stokes (RANS) k-ζ-f model on both types of meshes, the standard body-fitted (BF), and on the immersed boundary (IB) mesh. Due to all well-known shortcomings of the steady state approach, in this work we deal with the Partially Averaged Navier-Stokes (PANS), which belongs to the hybrid RANS-LES (scale resolving / high fidelity) methods. This approach was developed to resolve a part of the turbulence spectrum adjusting seamlessly from RANS to DNS (Direct Numerical Simulation).