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With the increasing importance of electrified powertrains, electric motors and gear boxes become an important NVH source especially regarding whining noises in the high frequency range. Engine encapsulation noise treatments become often necessary and present some implementation, modeling as well as optimization issues due to complex environments with contact uncertainties, pass-throughs and critical uncovered areas. Relying purely on mass spring systems is often a too massive and relatively unefficient solution whenever the uncovered areas are dominant. Coverage is key and often a combination of hybrid backfoamed porous stiff shells with integral foams for highly complex shapes offer an optimized trade-off between acoustic performance, weight and costs.

With the electrification of powertrains, the noise level inside vehicles reach high levels of silence. The dominant engine noise found in traditional vehicles is now replaced by other sources of noise such as rolling noise and aeroacoustic noise. These noises are encountered during driving on roads and highways and can cause significant fatigue during long journeys. Regarding aeroacoustic phenomena, the noise transmitted into the cabin is the result of both turbulent pressure and acoustic pressure created by the airflow. Even though it is lower in level, the acoustic pressure induces most of the noise perceived by the occupants. Its wavelength is closer to the characteristic vibration wavelengths of the glass, making its propagation more efficient through the vehicle's windows. The accurate modeling of these phenomena requires the coupling of high-frequency computational fluid dynamics (CFD) simulations and vibro-acoustic simulations.

This paper delves into the intricate realm of Formula 1 race car aerodynamics, focusing on the pivotal role played by floor flow structures in contemporary racing. The aerodynamic design of the floor of a Formula 1 car is a fundamental component that connects the flow structures from the front wing to the rear end of the car through the diffuser, thus significantly influencing the generation of lift and drag. In this work, CFD was used to predict the structure of the vortices and flow pattern underneath a Formula 1 car using a CAD model that mimicked the modern Red Bull Racing Team’s car in recent years. Through comprehensive analysis and simulation, a detailed understanding of the complex flow patterns and aerodynamic phenomena occurring beneath the floor of the car and its vicinity is presented.

The proposed Euro 7 regulation aims to substantially reduce the NOx emissions to 0.03 g/km, a trend also seen in upcoming China 6b and US EPA regulations. Meeting these stringent requirements necessitates advancements in Urea/Selective Catalytic Reduction (SCR) aftertreatment systems, with the urea deposit formation being a key challenge to its design. It’s proven that Computational Fluid Dynamics (CFD) can be an effective tool to predict Urea deposits. Transient wall temperature prediction is crucial in Urea deposit modeling. Additionally, fully understanding the kinetics of urea decomposition and by-products solidification are also critical in predicting the deposit amount and its location. In this study, we introduce (i) a novel film boiling model (IFPEN-BRT model) and (ii) a new urea by-product solidification model in the CONVERGE CFD commercial solver, and validate the results against the recent experiments.

The internal combustion engine (ICE) has long dominated the heavy-duty sector by using liquid fossil fuels such as diesel but global commitments by countries and OEMs to reduce lifecycle carbon dioxide (CO2) emissions has garnered interest in alternative fuels like hydrogen. Hydrogen is a unique gaseous fuel that contains zero carbon atoms and has desired thermodynamic properties of high energy density per unit mass and high flame speeds. However, there are challenges related to its adoption to the heavy-duty sector as a drop-in fuel replacement for compression ignition (CI) diesel combustion given its high autoignition resistance. To overcome this fundamental barrier, engine manufacturers are exploring dual fuel combustion engines by substituting a fraction of the diesel fuel with hydrogen which enables fuel flexibility when there is no infrastructure and retrofittability to existing platforms.

Urea-water solution (UWS) injection combined with Selective Catalytic Reduction (SCR) has developed as an effective method of meeting EPA and EURO NOx emissions regulations for diesel engines. Urea/SCR systems encompass a wide range of engine sizes, from light duty vehicles to large ship or power generation engines. One key challenge faced by modern urea/SCR systems is the formation of solid deposits of urea decomposition by-products that are difficult to remove. These deposits are proven to be detrimental to urea/SCR systems by decreasing ammonia uniformity, clogging injector nozzles and increasing pressure drop of the whole system. Urea deposits only form in a narrow range of wall temperatures and take many minutes to hours to form. The decomposition of urea into deposits begins with the formation of biuret and then progresses into the crystalline species cyanuric acid (CYA), ammelide, and ammeline.

Combustion in any engine starts with the injection of fuel into the combustion chamber. Atomization of fuel and its mixing plays a vital role in determining the suitable air-fuel (A/F) ratio. Appropriate A/F ratio determines the amount of energy release and pollutant formation for standard engines. Thus an accurate prediction of these processes is required to perform reliable combustion and pollutant formation simulations. In this study, the Eulerian-Lagrangian Spray Atomization (ELSA) model is implemented as a Computational Fluid Dynamics (CFD) tool for the prediction of spray behavior. Past studies performed on diesel fuel suggest good agreement between experiment and simulation indicating the model’s capability. The study aims to validate the ELSA model for gasoline fuel against the test results obtained from Renault and against the pure Lagrangian spray model. The simulations have been performed using CONVERGE CFD v2.4.18.

Automotive suppliers provide multi-layer trims mainly made of porous materials. They have a real expertise on the characterization and the modeling of poro-elastic materials. A dozen parameters are used to characterize the acoustical and elastical behavior of such materials. The recent vibro-acoustic simulation tools enable to take into account this type of material but require the Biot parameters as input. Several characterization methods exist and the question of reproducibility and confidence in the parameters arises. A Round Robin test was conducted on three poro-elastic material with four laboratories. Compared to other Round Robin test on the characterization of acoustical and elastical parameters of porous material, this one is more specific since the four laboratories are familiar with automotive applications. Methods and results are compared and discussed in this work.

One of the most important safety issues for automotive engineering is to avoid any fire due to the ignition of flammable liquids, which may result from leaks. Fire risk is a combination of hot temperature, fast vaporisation and accumulation of vapor in a cavity. In IC engines, potentially flammable liquids are fuel and oil. To guarantee safety, flammable liquids must not come into contact with hot parts of the engine. Consequently, shields are designed to guide the flow path of possible leakages and to take any flammable liquid out of the hot areas. Simulation is a great help to optimize the shape of the shield by investigating a large number of possible leakages rapidly. Recent breakthroughs in numerical methods make it possible to apply simulations to industrial design concepts. The employed approach is based on the Lagrangian Smoothed Particle Hydrodynamics (SPH) method.

This paper touches on the mass transport phenomenon in the exhaust gas recirculation (EGR) of a gasoline engine air path. It presents the control-oriented model and control design of the burned gas ratio (BGR) transport phenomenon, witnessed in the intake path of an internal combustion engine (ICE), due to the redirection of burned gases to the intake path by the low-pressure EGR (LP-EGR). Based on a nonlinear AMESim® model of the engine, the BGR in the intake manifold is modeled as a state-space (SS) output time-delay model, or alternatively as an ODE-PDE coupled system, that take into account the time delay between the moment at which the combusted gases leave the exhaust manifold and that at which they are readmitted in the intake manifold. In addition to their mass transport delay, the BGRs in the intake path are also subject to state and input inequality constraints.

The Reynolds stress turbulence model (RSM) has been developed to go beyond the Boussinesq hypothesis and to improve turbulence modeling of flows with significant mean streamline curvature and secondary flow. In this paper the RSM in commercial CFD software CONVERGE is tested for its performance and robustness when applying to complex flows. Several validation cases including flow over flat plate, vortex combustor, diesel engine spray and combustion were selected to test the RSM. The swirling flow in vortex combustor, non-reacting but vaporizing ECN Spray A (free jet) and Sandia small bore diesel engine case are used to demonstrate the benefits of the RSM over the widely used RNG k-epsilon model without model tuning. The vortex combustor case shows the RSM can provide good prediction for strong swirling flow. ECN spray A case was used to demonstrate that the RSM can accurately predict the liquid and vapor penetration lengths of a free jet under diesel engine conditions.

As we are heading towards autonomous vehicles, additional driver assistance systems are being added. The vehicle motion is automated step by step to ensure passengers’ safety and comfort, while still preserving vehicle performance. However, simultaneous activations of concurrent systems may conflict, and non-suitable behavior may emerge. Our research work consists in proving that with the right coordination approach, simultaneous operation of different systems improve the vehicle’s performance and avoid the emergence of unwanted conflicts. To prove this, we gathered different control architectures implemented in commercial passenger cars, and we compared them with our control architecture using a unified reference vehicle model. The high-fidelity vehicle model is developed in Simcenter Amesim in a modular and extensible manner. This enables adding systems in a plug-and-play way.

The Computational Chemistry Consortium (C3) is dedicated to leading the advancement of combustion and emissions modeling. The C3 cluster combines the expertise of different groups involved in combustion research aiming to refine existing chemistry models and to develop more efficient tools for the generation of surrogate and multi-fuel mechanisms, and suitable mechanisms for CFD applications. In addition to the development of more accurate kinetic models for different components of interest in real fuel surrogates and for pollutants formation (NOx, PAH, soot), the core activity of C3 is to develop a tool capable of merging high-fidelity kinetics from different partners, resulting in a high-fidelity model for a specific application. A core mechanism forms the basis of a gasoline surrogate model containing larger components including n-heptane, iso-octane, n-dodecane, toluene and other larger hydrocarbons.

Wind noise in automobile is becoming more and more important as the customer expectations increase. On the other hand, great progress has been made on engine and road noises, especially for electric and hybrid vehicles. Thus, the wind noise is now by far the major acoustic source during road and motorway driving. As for other noises, automobile manufacturers must be able, for a new car project, to specify, calculate and measure each step of the acoustic cascading: Source Transfers, both solid and air borne In the case of the automotive wind noise, the excitation source is the dynamic pressure on the vehicle’s panels. This part of the cascading is the one influenced by the exterior design. Even if many others components (panels, seals, cabin trims) have a big influence, the exterior design is a major issue for the wind noise. The wind noise level in the cabin may change significantly with only a small modification of the exterior design.

Reduced-order models typically assume that the flow through the injector orifice is quasi-steady. The current study investigates to what extent this assumption is true and what factors may induce large-scale variations. Experimental data were collected from a single-hole metal injector with a smoothly converging hole and from a transparent facsimile. Gas, likely indicating cavitation, was observed in the nozzles. Surface roughness was a potential cause for the cavitation. Computations were employed using two engineering-level Computational Fluid Dynamics (CFD) codes that considered the possibility of cavitation. Neither computational model included these small surface features, and so did not predict internal cavitation. At steady state, it was found that initial conditions were of little consequence, even if they included bubbles within the sac. They however did modify the initial rate of injection by a few microseconds.

Urea water solution-based Selective Catalytic Reduction (SCR) of NOx emissions from vehicular diesel engines is now widely used world-wide to meet strict health and environmental protection regulations. While urea-based SCR is proven effective, urea-derived deposits often form near injectors, on mixers and pipes, and on the SCR catalyst face. Further understanding of these deposit-formation processes is needed to design aftertreatment system hardware and control systems capable of avoiding severe urea-derived deposits. Computational Fluid Dynamics (CFD) is widely used in SCR aftertreatment design. Film formation, movement, solid wall cooling and deposit initiation/growth time-scales are in the range of minutes to hours, but traditional CFD simulations take too long to reach these time-scales. Here, we propose and demonstrate the frozen flow approach for pulsed sprays and conjugate heat transfer to reduce computation time while maintaining accuracy of key physics.

The Extended Coherent Flamelet Model (ECFM) is limited to lower order upwinding schemes to minimize the numerical discrepancy between species and tracers, which can lead to inaccurate estimates of the progress variable and consequently negative conditional mass fractions in the burned gases after ignition. The recently developed Species-Based ECFM (SB-ECFM) removes the species tracers from the definition of the progress variable, and allows the use of higher order schemes. In this study, SB-ECFM is coupled with the Imposed Stretch Spark Ignition Model (ISSIM) to simulate a spark-ignition engine, the transparent combustion chamber (TCC) engine. To examine the spatial discretization effect and demonstrate the improvement due to using higher order schemes, Reynolds-Averaged-Navier-Stokes (RANS) simulations performed with a first-order upwinding scheme and a second-order central differencing scheme are compared.

Fluid-Structure Interaction (FSI) simulation approach can be used to simulate a turbocharger. However, this predictive 3D simulation encounters the challenge of a long computational time. The impeller speed can be above 100,000 rpm, and generally a CFD solver limits the maximum movement of the impeller surface per time step. The maximum movement must be a fraction (~0.3) of the cell length, thus the time step will be very small. A Multiple Reference Frame (MRF) approach can reduce computational time by eliminating the need to regenerate the mesh at each time-step to accommodate the moving geometry. A static local reference zone encompassing the impeller is created and the impact of the impeller movement is modeled via a momentum source. However, the MRF approach is not a predictive simulation because the impeller speed must be given by the User. A new simulation approach was introduced that coupled the FSI and MRF approach.

A computational fluid dynamics (CFD) guided combustion system optimization was conducted for a heavy-duty diesel engine running with a gasoline fuel that has a research octane number (RON) of 80. The goal was to optimize the gasoline compression ignition (GCI) combustion recipe (piston bowl geometry, injector spray pattern, in-cylinder swirl motion, and thermal boundary conditions) for improved fuel efficiency while maintaining engine-out NOx within a 1-1.5 g/kW-hr window. The numerical model was developed using the multi-dimensional CFD software CONVERGE. A two-stage design of experiments (DoE) approach was employed with the first stage focusing on the piston bowl shape optimization and the second addressing refinement of the combustion recipe. For optimizing the piston bowl geometry, a software tool, CAESES, was utilized to automatically perturb key bowl design parameters. This led to the generation of 256 combustion chamber designs evaluated at several engine operating conditions.

In order to design vehicles with diminished gCO2/km emissions level, car manufacturers aim at reducing the weight of their vehicles. One of the solutions advocated by the automotive industry consists in the replacement of metallic parts by lighter systems made of polymer reinforced composites. Unfortunately, the numerical simulations set to evaluate the vibratory and acoustic performances of systems made of this kind of materials are often not sufficiently effective and robust so that convincing test/simulation correlations are rarely met. Indeed, for polymer-based materials, numerous parameters affect the vibroacoustic behavior. On the one hand, it is well known that the viscoelastic properties (Storage -Young- and dissipative moduli) of polymers depend on the temperature, loading frequency and sometimes the humidity content.