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In vehicle NVH development, vibroacoustic simulations with Finite Element (FE) models are a common technique. The computational costs for these calculations are steadily rising due to more detailed modelling and higher frequency ranges. At the same time, the need for multiple evaluations of the same model with different input parameters, e.g., for uncertainty quantification, optimization, or robustness investigations, is also increasing. Therefore, it is crucial to reduce the computational costs in these cases. A common technique is to use surrogate models that replace the computationally intensive FE model to perform repeated evaluations. Several different methods in this area are well established, but with the continuous advancements in the field of machine learning, interesting new methods like the Gaussian Process (GP) regression arises as a promising approach.

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.

Vehicle thermal management (VTM) simulations are becoming increasingly important in the development phase of a vehicle. These simulations help in predicting the thermal profiles of critical components over a drive cycle. They are usually done using two methodologies: (1) Solving every aspect of the heat transfer, i.e., convection, radiation, and conduction, in a single solver (Conjugate Heat Transfer) or (2) Simulating convection using a fluid solver and computing the other two mechanisms using a separate thermal solver (Co-simulation). The first method is usually computationally intensive, while the second one isn’t. This is because Co-simulation reduces the load of simulating all heat transfer mechanisms in a single code. This is one of the reasons why the Co-simulation method is widely used in the automotive industry. Traditionally, the methods developed for Co-simulation processes are load case specific.

Air conditioning acoustics have become of paramount importance in electric vehicles, where noise from electromechanical components is no longer masked by the presence of the internal combustion engine. In a car HVAC systems, the coolant compressor is one of the most important sources in terms of vibration and noise generation. The paper, the generated structural noise is studied in detail on a prototype installation, and the noise transmission and propagation mechanisms are analyzed and discussed. Through ”in situ” measurements and virtual point transformation, the rotor unbalance forces and torque acting within the component are identified. The dynamic properties of the rubber mounts, installed between the compressor and its support, are identified thanks to matrix inversion methods. To assess the quality of the proposed procedure, the synthesized sound pressure level is compared with experimental SPL measurements in different operational conditions.

The continuous encouragement of lightweight design in modern vehicles demands a reliable and efficient method to predict and ameliorate the interior acoustic comfort for passengers. Due to considerable psychological effects on stress and concentration, the low frequency contribution plays a vital rule regarding interior noise perception. Apart other contributors, low frequency noise can be induced by transient aerodynamic excitation and the related structural vibrations. Assessing this disturbance requires the reliable simulation of the complex multi-physical mechanisms involved, such as transient aerodynamics, structural dynamics and acoustics. The domain of structural dynamics is particularly sensitive regarding the modelling of attachments restraining the vibrational behaviour of incorporated membrane-like structures. In a later development stage, when prototypes are available, it is therefore desirable to replace or update purely numerical models with experimental data.

Synthetic fuels for internal combustion engines offer CO2-neutral mobility if produced in a closed carbon cycle using renewable energies. C1-based synthetic fuels can offer high knock resistance as well as soot free combustion due to their molecular structure containing oxygen and no direct C-C bonds. Such fuels as, for example, dimethyl carbonate (DMC) and methyl formate (MeFo) have great potential to replace gasoline in spark-ignition (SI) engines. In this study, a mixture of 65% DMC and 35% MeFo (C65F35) was used in a single-cylinder research engine to determine friction losses in the piston group using the floating-liner method. The results were benchmarked against gasoline (G100). Compared to gasoline, the density of C65F35 is almost 40% higher, but its mass-based lower heating value (LHV) is 2.8 times lower. Hence, more fuel must be injected to reach the same engine load as in a conventional gasoline engine, leading to an increased cooling effect.

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.

Pilot injection gas engines are commonly used as large stationary engines. Often, the combustion is implemented as a dual-fuel strategy, which allows both mixed and diesel-only operation, based on a diesel engine architecture. The current research project focuses on the application of pilot injection in an engine based on gasoline components of the passenger car segment, which are more cost-effective than diesel components. The investigated strategy does not aim for a diesel-only combustion, hence only small liquid quantities are used for the main purpose of providing a strong, reliable ignition source for the natural gas charge. This approach is mainly driven to provide a reliable alternative to the high spark ignition energies required for high cylinder charge densities. When using such small liquid quantities, a standard common-rail diesel nozzle will apparently not be ideal regarding some general specifications.

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 describes a novel approach for modeling an automotive HVAC unit. The model consists of black-box models trained with experimental data from a self-developed measurement setup. It is capable of predicting the temperature and mass flow of the air entering the vehicle cabin at the various air vents. A combination of temperature and velocity sensors is the basis of the measurement setup. A measurement fault analysis is conducted to validate the accuracy of the measurement system. As the data collection is done under fluctuating ambient conditions, a review of the impact of various ambient conditions on the HVAC unit is performed. Correction models that account for the different ambient conditions incorporate these results. Numerous types of black-box models are compared to identify the best-suited type for this approach. Moreover, the accuracy of the model is validated using test drive data.

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.

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.

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.

Autonomous driving systems and connected mobility are the next big developments for the car manufacturers and their suppliers during the next decade. To achieve the high computing power needs and fulfill new upcoming requirements due to functional safety and security, heterogeneous processor architectures with a mixture of different core architectures and hardware accelerators are necessary. To tackle this new type of hardware complexity and nevertheless stay within monetary constraints, high performance computers, inspired by state of the art data center hardware, could be adapted in order to fulfill automotive quality requirements. The European Processor Initiative (EPI) research project tries to come along with that challenge for next generation semiconductors. To be as close as possible to series development needs for the next upcoming car generations, we present a hybrid semiconductor system-on-chip architecture for automotive.

In this paper a method for the identification of most significant vehicle parameters influencing the behavior of a lateral control system of autonomous car is presented. Requirements for the design stage of the controller need to consider many uncertainties in the plant. While most vehicle properties can be compensated by an appropriate tuning of the control parameters, other vehicle properties can change significantly during usage. The control system is evaluated based on performance measures. Analyzed parameters comprise functional tire characteristics, mass of the vehicle and position of its center of gravity. Since the parameters are correlated, but Sobol’ sensitivity analysis assumes decorrelated inputs, random variation yields no reasonable results. Furthermore, the variation of each parameter or set of parameters is not applicable since the numbers of required simulations is increased significantly according to input dimension.

Vehicle thermal management (VTM) simulations constitute an important step in the early development phase of a vehicle. They help in predicting the temperature profiles of critical components over a drive cycle and identify components which are exceeding temperature design limits. Parts with the highest temperatures in a vehicle with an internal combustion engine are concentrated in the engine bay area. As packaging constraints grow tighter, the components in the engine bay are packed closer together. This makes the thermal protection in the engine bay even more crucial. The fan influences the airflow into the engine bay and plays an important role in deciding flow distribution in this region. This makes modelling of the fan an important aspect of VTM simulations. The challenge associated with modelling the fan is the accurate simulation of the rotation imparted by the fan to the incoming flow. Currently, two modelling approaches are prevalent in the industry.

External Exhaust Gas Recirculation (EGR) provides an opportunity to increase the efficiency of turbocharged spark-ignition engines. Of the competing technologies and configurations, Low-Pressure EGR (LP-EGR) is the most challenging in terms of its dynamic behavior. Only some of the stationary feasible potential can be used during dynamic engine operation. To guarantee fuel consumption-optimized engine operation with no instabilities, a load point-dependent limitation of the EGR rate or alternatively an adaptation of the operating point to the actual EGR rate is crucial. For this purpose, a precise knowledge of efficiency and combustion variance is necessary. Since the operating state includes the actual EGR rate, it has an additional dimension, which usually results in an immense measuring effort.

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.

Seatbelt retractors as important part of modern safety systems are mounted in any automotive vehicle. Their internal locking mechanism is based on mechanically sensing elements. When the vehicle is run over rough road tracks, the retractor oscillates by spatial mode shapes and its interior components are subjected to vibrations in all 6 degrees of freedoms (DOF). Functional backlash of sensing elements cause impacts with neighbouring parts and leads to weak, but persistent rattle sound, being often rated acoustically annoying in the vehicle. Current acoustic retractor bench tests use exclusively uni-directional excitations. Therefore, a silent 2 DOF test bench is developed to investigate the effect of multi-dimensional excitation on retractor acoustics, combining two slip-tables, each driven independently by a shaker. Tests on this prototype test bench show, that cross coupling between the two perpendicular directions is less than 1%, allowing to control both directions independently.

This paper is a case study from the TESSA project (French funded research program “Transfert des Efforts des Sources Solidiennes Actives”). The general frame of the work was to assess a collaborative design process between a car manufacturer and a major supplier using FE modelling and condensation of structure borne noise sources as an alternative to classic specification method for structure borne sources. Super elements from different FE commercial softwares have been used to assess the reliability of the method, the compatibility of the softwares and, most important, the relevance of applying a blocked force tensor to the component super element to predict the interior contribution of a component which is the originality of this work. The case study is an internal combustion engine cooling module (fan + shroud + exchangers) from VALEO including all assembly details (clips, decoupling elements) modelled under ABAQUS and its integration in a RENAULT Espace under NASTRAN.