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Squeak and rattle (SAR) noise audible inside a passenger car causes the product quality perceived by the customer to deteriorate. The consequences are high warranty costs and a loss in brand reputation for the vehicle manufacturer in the long run. Therefore, SAR noise must be prevented. This research shows the application and experimental validation of a novel method to predict SAR noise on an actual vehicle interior component. The novel method is based on non-linear theories in the frequency domain. It uses the harmonic balance method in combination with the alternating frequency/time domain method to solve the governing dynamic equations. The simulation approach is part of a process for SAR noise prediction in vehicle interior development presented herein. In the first step, a state-of-the-art linear frequency-domain simulation estimates an empirical risk index for SAR noise emission. Critical spots prone to SAR noise generation are located and ranked.

Finite element simulation (FE) makes it possible to analyze the structural dynamic behavior of vehicle seat structures in early design phases to meet Noise-Vibration-Harshness (NVH) requirements. For this purpose, linear simulations are usually used, which neglect many nonlinear mechanical properties of the real structure. These models are trimmed to fit global vibration behavior based on the complex description of contact or jointed definitions. Targeted design is therefore only possible to a limited extent. The aim of this work is to characterize the entire seat structure and its sub-components in order to identify the main contributors using experimental and simulative data. The Lagrange Multiplier Frequency Based Substructuring (LM-FBS) method is used for this purpose. Therefore, the individual subsystems of seat frame, seat backrest and headrest are characterized under different conditions.

Trim materials are often used for vibroacoustic energy absorption purposes within vehicles. To estimate the sound impact at a driver’s ear, the substructuring approach can be applied. Thus, transfer functions are calculated starting from the acoustic source to the car body, from the car body to the trim and, finally, from the trim to the inner cavity where the driver is located. One of the most challenging parts is the calculation of the transfer functions from the car body inner surface to the bottom trim surface. Commonly, freely laying mass-spring systems (trims) are simulated with a fixed boundary and interface phenomena such as friction, stick-slip or discontinuities are not taken into consideration. Such an approach allows for faster simulations but results in simulations strongly overestimating the energy transfer, particularly in the frequency range where the mass-spring system’s resonances take place.

The thermal operational safety (TOS) of a vehicle ensures that no component exceeds its critical temperature during vehicle operation. To enhance the current TOS validation process, a data-driven approach is proposed to predict maximum component temperatures of a new vehicle project by leveraging the historical thermal wind tunnel data from previous vehicle projects. The approach intends to support engineers with temperature predictions in the early phase and reduce the number of wind tunnel tests in the late phase of the TOS validation process. In the early phase, all measurements of the new vehicle project are predicted. In the late phase, a percentage of measurements with the test vehicle used for the model training and the remaining tests are predicted with the trained ML model. In a first step, data from all wind tunnel tests is extracted into a joint dataset together with metadata about the vehicle and the executed load case.

The US American government introduced a law to mandatorily equip passenger vehicles with rear view cameras. Furthermore, US NCAP presented a test for passenger vehicles to brake on pedestrians while back up. These two circumstances lead to main motivation of the development of the Comfort Backup Assist (CBUA). Nevertheless, more and more passenger cars in general are being equipped with rear view cameras. Rear view system (RVS) allows to deliver a rear-view camera system including a braking functionality which is intended to make the driving mission safer and reduce the number of accidents in parking driving situations. RVS also focus on vehicle safety by reducing accidents while taking reversing/parking scenarios and to provides slow de-acceleration of the vehicle gradually to avoid jerk and increase the ride comfort.

Riveting is a process used to fasten printed circuit board to housing that offers several advantages compared to screws. This involves a cylindrical pin that protrudes from the housing being compressed with a concave tool to produce a rivet head that fills the PCB hole and holds it in place over service life of the component. The process as performed currently in-house uses parameters that have not been optimized. Testing has revealed that the process is subjecting the PCB to surface strains higher than 1000μɛ which is the limit as recommended by standards. Exceeding this limit reduces the reliability of electrical components and increases risk of field failures. This risk can be mitigated by improving the riveting process parameters to prevent high strain from reaching components. Having a finite element model for high deformation problems is an essential prerequisite to explore riveting process improvement.

The NVH-development cycle of vehicle components often requires a source characterization separated from the vehicle itself, which leads to the implementation of test bench setups. In the context of frequency based substructuring and transfer path analysis, a component can be characterized using Blocked Forces. The following paper provides a comparison of methods between an acceleration-based in-situ and a new hybrid in-situ Blocked Force determination, using measurements of an artificially excited electric power steering (EPS). Under real-life conditions on a test rig, the acceleration-based in-situ approach often shows limitations in the lower frequency range, due to relatively bad signal-to-noise ratio at the indicator sensors, while delivering accurate results in the higher spectrum. Due to considerable loads on components in operation, the stiffness of the test-rig cannot be decreased arbitrarily.

In order to predict reality as accurately as possible leads to the fact that numerical models in automotive vibroacoustic problems become increasingly high dimensional. This makes applications with a large number of model evaluations, e.g. optimization tasks or uncertainty quantification hard to solve, as they become computationally very expensive. Engineers are thus faced with the challenge of making decisions based on a limited number of model evaluations, which increases the need for data-efficient methods and reduced order models. In this contribution, variational autoencoders (VAEs) are used to reduce the dimensionality of the vibroacoustic model of a vehicle body and to find a low-dimensional latent representation of the system.

Transfer path analyses of vehicle bodies are widely considered as an important tool in the noise, vibration and harshness design process, as they enable the identification of the dominating transfer paths in vibration problems. It is highly beneficial to model uncertain parameters in early development stages in order to account for possible variations on the final component design. Therefore, parameter studies are conducted in order to account for the sensitivities of the transfer paths with respect to the varying input parameters of the chassis components. To date, these studies are mainly conducted by performing sampling-based finite element simulations. In the scope of a sensitivity analysis or parameter studies, however, a large amount of large-scale finite element simulations is required, which leads to extremely high computational costs and time expenses. This contribution presents a method to drastically reduce the computational burden of typical sampling-based simulations.

Uncertainties play a major role in vibroacoustics - especially in car body design in the preliminary development because of the overall spread in the production that should be covered with one simulation model. Therefore, we use uncertain input parameters to determine the stochastically distributed admittance of the car body before each part of the car is fully designed. To gain a stochastic result - the stochastically distributed admittance curve - we calculate a deterministic finite element simulation several times with sets of stochastically distributed input parameter values. To reduce simulation time and cost of the car model with many million degrees of freedom we focus on the uncertain parameters that show a significant influence on the admittance curve. It is therefore necessary to be able to accurately estimate for each parameter if its influence on the admittance of the car body plays a major role for the noise vibration harshness simulation.

Raising demands towards lightweight design paired with a loss of originally predominant engine noise pose significant challenges for NVH engineers in the automotive industry. From an aeroacoustic point of view, low frequency buffeting ranks among the most frequently encountered issues. The phenomenon typically arises due to structural transmission of aerodynamic wall pressure fluctuations and/or, as indicated in this work, through rear vent excitation. A possible workflow to simulate structure-excited buffeting contains a strongly coupled vibro-acoustic model for structure and interior cavity excited by a spatial pressure distribution obtained from a CFD simulation. In the case of rear vent buffeting no validated workflow has been published yet. While approaches have been made to simulate the problem for a real-car geometry such attempts suffer from tremendous computation costs, meshing effort and lack of flexibility.

Substructuring approaches are helpful methods to solve and understand vibro-acoustic problems involving systems as complex as a vehicle. In that case, the whole system is split into smaller, simpler to solve, subsystems. Substructuring approaches allow mixing different modeling “solvers” (closed form solutions, numerical simulations or experiments). This permits to reach higher frequencies or to solve bigger systems. Finally, one of the most interesting features of substructuring approaches is the possibility to combine numerical and experimental descriptions of subsystems. The latter point is particularly interesting when dealing with subdomains that remain difficult to model with numerical tools (assembly, trim, sandwich panels, porous materials, etc.). The Patch Transfer Functions (PTF) method is one of these substructuring approaches. It condenses information (impedance matrix) of subsystems on their coupling surfaces.

The Noise Vibration and Harshness (NVH) characteristics and requirements of vehicles are changing as the automotive manufacturers turn their focus from developing and producing cars propelled by internal combustion engines (ICE) to electrified vehicles. This new strategic orientation enables them to offer products that are more efficient and environmentally friendly. Although electric powertrains have many advantages compared to their established predecessors they also bring new challenges that increase the difficulty of matching the high quality requirements of premium car producers especially regarding NVH. Electric motors are one of the most important sources of vibrations in electric vehicles.

The advancing electrification of the powertrain is giving rise to new challenges in the field of acoustics. Film capacitors used in power electronics are a potential source of high-frequency interfering noise since they are exposed to voltage harmonics. These voltage harmonics are caused by semiconductor switching operations that are necessary to convert the DC voltage of the battery into three-phase alternating current for an electrical machine. In order to predict the acoustic characteristics of the DC-link capacitor at an early stage of development, a multiphysical chain of effects has to be addressed to consider electrical and mechanical influences. In this paper, a new method to evaluate the excitation amplitude of film capacitor windings is presented. The corresponding amplitudes are calculated via an analytical strain based on electromechanical couplings of the dielectric within film capacitors.

Driving cycles are valuable tools for emissions calibration at engine and powertrain test beds. While generic velocity profiles were sufficient in the past, legislative changes and increasing complexity of powertrain and exhaust aftertreatment systems require a new approach: Realistically transient cycles - which include critical driving maneuvers and can be tailored to a specific powertrain configuration - are needed to optimize the emission behavior of the said powertrain. For the generation of realistic velocity profiles, the Markov chain approach has been widely used and described in literature. However, this approach, so far, has only been used to generate cycles that are statistically representative of a large database of real driving trips, which is typically not available during the early stages of development of a new powertrain.

Service-oriented architectures (SOAs) are well-established solutions in the IT industry. Their use in the automotive domain is still on the way. Up to now, the automotive domain has taken advantage of service-oriented architectures only in the area of infotainment and not for systems with hard real-time requirements. However, applying SOA to such systems has just started but is missing suitable design and verification methodologies. In this context, we target to include the notion of model-based design to address fail-operational systems. As a result, a model-based approach for the development of fail-operational systems based on dynamic reconfiguration using a service-oriented architecture is illustrated. For the evaluation, we consider an example function of an automatically controlled braking system and analyze the reconfiguration time when the function fails.

Classical decentralized architectures based on large networks of microprocessor-based Electronic Control Units (ECU), namely those used in self-driving cars and other highly-automated applications used in the automotive industry, are becoming more and more complex. These new, high computational power demand applications are constrained by limits on energy consumption, weight, and size of the embedded components. The adoption of new embedded centralized electrical/electronic (E/E) architectures based on dynamically reconfigurable hardware represents a new possibility to tackle these challenges. However, they also raise concerns and questions about their safety. Hence, an appropriate evaluation must be performed to guarantee that safety requirements resulting from an Automotive Safety Integrity Level (ASIL) according to the standard ISO 26262 are met. In this paper, a methodology for the evaluation of dynamically reconfigurable systems based on centralized architectures is presented.

Global automotive fuel economy and emissions pressures mean that 48 V hybridisation will become a significant presence in the passenger car market. The complexity of powertrain solutions is increasing in order to further improve fuel economy for hybrid vehicles and maintain robust emissions performance. However, this results in complex interactions between technologies which are difficult to identify through traditional development approaches, resulting in sub-optimal solutions for either vehicle attributes or cost. The results presented in this paper are from a simulation programme focussed on the optimisation of various advanced powertrain technologies on 48 V hybrid vehicle platforms. The technologies assessed include an electrically heated catalyst, an insulated turbocharger, an electric water pump and a thermal management module.

The introduction of new light-duty vehicle emission limits to comply under real driving conditions (RDE) is pushing the diesel engine manufacturers to identify and improve the technologies and strategies for further emission reduction. The latest technology advancements on the after-treatment systems have permitted to achieve very low emission conformity factors over the RDE, and therefore, the biggest challenge of the diesel engine development is maintaining its competitiveness in the trade-off “CO2-system cost” in comparison to other propulsion systems. In this regard, diesel engines can continue to play an important role, in the short-medium term, to enable cost-effective compliance of CO2-fleet emission targets, either in conventional or hybrid propulsion systems configuration. This is especially true for large-size cars, SUVs and light commercial vehicles.

Since several decades, passenger cars and light duty vehicles (LDV) with spark-ignited engines reach full pollutant conversion during warm up conditions; the major challenge has been represented by the cold start and warming up strategies. The focus on technology developments of exhaust after treatment systems have been done in the thermal management in order to reach the warm up conditions as soon as possible. A new challenge is now represented by the Real Driving Emission (RDE) Regulation as this bring more various, and not any longer cycle defined, cold start conditions. On the other hand, once the full conversion has been reached, it would be beneficial for many Exhaust After Treatment System (EATS) components, e.g. for overall durability if the exhaust gas temperature could be lowered. To take significant further emission steps, approaching e.g. zero emission concepts, we investigate the use of Electrical Heating Catalyst (EHC) also including pre-heating.