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This paper presents a numerical study on the impact of washcoat diffusion on the overall conversion performance of catalytic converters. A comprehensive transient 1D pore diffusion reaction model is embedded in state-of-the-art 1D and 3D catalytic converter models. The pore diffusion model is discussed with its model equations and the applied diffusive transport approaches are summarized. The diffusion reaction model is validated with the help of two available analytical solutions. The impact of basic washcoat characteristics such as pore diameters or thickness on overall conversion performance is investigated by selected 1D+1D calculations. This model is also used to highlight the impact of boundary layer transfer, pore diffusion and reaction on the overall converter conversion performance. The interaction of pore diffusion and flow non-uniformities is demonstrated by 3D+1D CFD simulations.

The trend towards renewable energy sources will continue under the pre-amble of greenhouse gas (GHG) emission reduction targets. The main question is how to harvest and store renewable energy properly. The challenge of intermittency of the renewable energy resources make the supply less predictable compared to the traditional energy sources. Chemical energy carriers like hydrogen and synthetic fuels (e-Fuels) seem to be at least a part of the solution for storing renewable energy. The usage of e-Fuels in the existing ICE-powered vehicle fleet has a big lever arm to reduce the GHG emissions of the transport sector in the short- and medium term. The paper covers the whole well-to-wheel (WtW) pathway by discussing the e-Fuel production from renewable sources, the storage and the usage in the vehicle. It will be summarized by scenarios on the impact of e-Fuel to the WtW CO2 fleet emissions.

Wet clutches drag loss simulation is essentially linked to the clutch friction surface patterns in addition to the main geometry and conditions of the interface (relative speed, separation, inner and outer radius, viscosity and boundary pressures). The clutch patterns promote cooling flow and micro-hydrodynamic effects to aid clutch separation but greatly complicate the simulation of drag loss during separation. These drag losses are important in understanding the system losses as well as finding the most effective clutch cooling strategy. Typical clutch models either only consider simple patterns, such as radial grooves, or require significant simulation efforts to evaluate. Additionally, many simple models require calibration to measurement of the actual clutch they try to model before they provide a useful model.

E-mobility is a game changer for the automotive domain. It promises significant reduction in terms of complexity and in terms of local emissions. With falling prices and recent technological advances, the second generation of electric vehicles (EVs) that is now in production makes electromobility an affordable and viable option for more and more transport mission (people, freight). Still, major challenges for large scale deployment remain. They include higher maturity with respect to performance (e.g., range, interaction with the grid), development efficiency (e.g., time-to-market), or production costs. Additionally, an important market transformation currently occurs with the co-development of automated driving functions, connectivity, mobility-as-a-service. New opportunities arise to customize road transportation systems toward application-driven, user-centric smart mobility solutions.

Minimizing the lubricant volume in a transmission system reduces the churning losses and overall unit costs. However, lubricant volume reduction is also detrimental to the thermal stability of the system. Transmission overheating can result in significant issues in the region of loaded contacts, risking severe surface/sub-surface damage in bearings and gears, as well as reduction in the lubricant quality through advanced oxidation and shear degradation. The increasing trend of electrified transmission input speeds raises the importance of understanding the thermal limits of the system at the envelope of the performance to ensure quality and reliability can be maintained, as well as being a key factor in the development, effecting internal housing features for the promotion of lubrication. A nodal bearing thermal model will be shown which utilizes thermal resistances and smooth particle based CFD for determining bearing lubricant feed rates during operation.

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.

Increasingly stringent greenhouse gas and emission limits demand for powertrain electrification throughout all vehicle applications. Beside fully electric powertrains different configurations of hybrid powertrains will have an important role in upcoming and future vehicle generations. As already discussed in previous papers, the requirements on the combustion engine in hybrid powertrains are different to those in a conventional powertrain solution, heading for brake thermal efficiency targets of 45% and above within the product lifecycle for conventional fuels. Focus on product cost and production and assembly facility investment drives reuse of technology packages within modular powertrain technology platforms, with different combinations of internal combustion engines (ICE), transmissions, and e-drive-layouts. The goal of zero carbon operation requires compatibility of ICE for sustainable fuels.

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.

In order to achieve future CO2 targets - in particular under real driving conditions - different powertrain technologies will have to be introduced. Beside the increasing electrification of the powertrain, it will be essential to utilize the full potential of the internal combustion engine. In addition to further optimization of the combustion processes and the reduction of mechanical losses in the thermal- and energetic systems, the introduction of Variable Compression Ratio (VCR) is probably the measure with the highest potential for fuel economy improvement. VCR systems are expected to be introduced to a considerable number of next generation turbocharged Spark Ignited (SI) engines in certain vehicle classes. The basic principle of the AVL VCR system described in this paper is a 2-stage variation of the conrod length and thus the Compression Ratio (CR).

Traditionally, Electric Machine design has primarily focused on factors like efficiency, packaging, and cost, often neglecting the critical aspects of Noise, Vibration, and Harshness (NVH) in the early decision-making stages. This disconnect between E-Machine design teams and NVH teams has consistently posed a challenge. This paper introduces an innovative workflow that unifies these previously separate domains, facilitating comprehensive optimization by seamlessly integrating NVH considerations with other E-Machine objectives, such as electromagnetic compatibility (EMC). This paper highlights AVL's approach in achieving this transformation and demonstrates how this integrated approach sets a new standard for E-Machine design. The presented approach relies on AI-driven algorithms and computational tools.

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).

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.

This paper presents calculations of external car aerodynamics by using the finite volume (FV) immersed-boundary method. The FV numerical codes primarily employ Reynolds-Averaged Navier-Stokes (RANS) models. In recent years, and due to possibility to run very large computational meshes, these models are usually used in conjunction with the advanced near-wall models. Moreover, it has been often demonstrated that the accuracy of RANS near-wall models relies on the mesh quality near the wall so by the rule, larger number of wall body-fitted cell-layers are employed. An immersed boundary (IB) method becomes an attractive alternative to the ‘standard’ FV approaches especially when applied to low quality CAD data. In general, the IB method is less investigated and validated for the car aerodynamics, particularly in conjunction with advanced near-wall turbulence models and an adaptive mesh refinement (AMR).

The paper addresses aspects of modeling cavitating flows within high pressure injection equipment while considering the effects of liquid compressibility. The presented numerical study, performed using the commercial CFD code AVL FIRE®, mimics common rail conditions, where the variation in liquid density as a function of pressure may be relevant owing to very high pressure injection scenarios. The flow through the injector has been calculated and the conditions at the outlet of the nozzle orifice have been applied as inlet condition for subsequent Euler-Lagrangian spray calculations to investigate the effects of liquid compressibility treatment on spray propagation. Flows of such nature are of interest within automotive and other internal combustion (IC) related industries to obtain good spray and emissions characteristics.

Fully flexible dual fuel (DF) internal combustion (IC) engines, that can burn diesel and gas simultaneously, have become established among heavy-duty engines as they contribute significantly to lower the environmental impact of the transport sector. In order to gain better understanding of the DF combustion process and establish an effective design methodology for DFIC engines, high fidelity computational fluid dynamics (CFD) simulation tools are needed. The DF strategy poses new challenges for numerical modelling of the combustion process since all combustion regimes have to be modelled simultaneously. Furthermore, DF engines exhibit higher cycle-to-cycle variations (CCV) compared to the pure diesel engines. This issue can be addressed by employing large eddy simulation coupled with appropriate DF detailed chemistry mechanism. However, such an approach is computationally too expensive for today’s industry-related engine calculations.

With the introduction of new regulations on emissions, fuel efficiency, driving cycles, etc. challenges for the powertrains are significantly increasing. In order to fulfil these regulations, hybrid-electric powertrains are an unquestioned option for short and long-term solutions. Hybridization however, is not only fulfilling these challenging efficiency or emission targets, but also allows numerous new possibilities on control strategies of different powertrain elements as well as new approaches of designing them. A good example is transmissions where, hybridization allows a new transmission type called Dedicated Hybrid Transmission (DHT), which enables to use novel control strategies bringing improved performance, driveability, durability and NVH behavior. This paper focuses on the novel shift strategy where friction clutches do not have to slip.

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.

Commonly, the spray process in Direct Injection (DI) diesel engines is modeled with the Euler Lagrangian discrete droplet approach which has limited validity in the dense spray region, close to the injector nozzle hole exit. In the presented research, a new reactive spray modelling method has been developed and used within the 3D RANS CFD framework. The spray process was modelled with the Euler Eulerian multiphase approach, extended to the size-of-classes approach which ensures reliable interphase momentum transfer description. In this approach, both the gas and the discrete phase are considered as continuum, and divided into classes according to the ascending droplet diameter. The combustion process was modelled by taking into account chemical kinetics and by solving general gas phase reaction equations.

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.