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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.

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.

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.

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.

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.

One of the major concerns in the vehicle trim part design is the acoustic targets, which are generally defined by absorption area or coefficients, and sound transmission loss (STL) or sound insertion loss (SIL). The breaking down of acoustic targets in vehicle design, which is generally referred to as cascading, is the process of determining the trim part acoustic targets so as to satisfy full vehicle acoustic performance. In many cases, these targets are determined by experience or by subjective evaluation. Simulation based transfer path analysis (TPA), which traces the energy flow from source, through a set of paths to a given receiver, provides a systematic solution of this problem. Guided by TPA, this paper proposes a component level target setting approach that is based on the statistical energy analysis (SEA), an efficient method for vehicle NVH analysis in mid and high frequencies.

The present contribution will present how local micromechanical properties can be used in an industrial way to assess the crash performance of parts made of short fiber reinforced polymers. To this end, local information about the material structure, predicted by a Manufacturing Process Simulation (MPS), is transferred and mapped automatically on the performance composite part model. The homogenization and mapping techniques will be presented for elastic and nonlinear application fields. Short fiber reinforced injected thermoplastics are widely used in the automotive industry in mass production. Reliable prediction of the performance of short fiber reinforced thermoplastics by simulation for statics and crash simulation can be achieved only by accounting for the full manufacturing process coming from process simulation software.

Electric vehicle makers have largely relied on aluminum to make their cars lighter in hopes of offsetting the weight of the battery pack and reducing overall weight. Distortion of Aluminum welding is a big issue due to Aluminum’s high coefficient of expansion ratios. This paper presents an effective numerical approach to minimize weld-induced distortion in Electrical Vehicle Aluminum assembly structures using welding sequence optimization. A numerical optimization framework based on genetic algorithms and Finite Element Analysis (FEA) is developed and implemented. The shrinkage method calibrated using transient approach, is used for the weld sequence optimization to reduce the computation time. The optimization results show that the proposed calibration approach can contribute substantially to reduce distortion by optimizing weld sequences. It enhances final aluminum assembly quality while facilitating and accelerating design and development.

Model Order Reduction (MOR) methods such as Component Mode Synthesis (CMS) have been used in order to simulate large linear dynamic systems for many years and have reached a considerable level of saturation. These reduction methods have many advantages such as minimizing computational costs but also have restrictions. One of their disadvantages is that material damping characteristics can only be defined in form of Rayleigh damping. Another disadvantage is that the reduced order model can only represent one state of the structure determined in the generation process of the reduced matrices. In this paper we present a way to consider material damping in reduced matrices that contain one or more materials having different damping characteristics without the disadvantages of using Rayleigh damping.

To develop future electrical and autonomous cars, it is important to virtually test the car in real driving circumstances, including on wet road or under heavy rain conditions. It is especially critical to check that no water prevents the sensors of the driving assistance systems or autonomous cars from working properly, that water intrusion does not disturb electrical equipment, and that the driver’s visibility remains good under rain condition. ESI Group has introduced the Finite Point Method (FPM) in Virtual Performance Solution (VPS) as a CFD mesh free module in order to simulate the interaction of water with the car structure. It was initially specialized for tank sloshing and water drain applications for car closures and is now extended to other application fields. The objective is to enable a holistic prediction of the car behavior under realistic driving conditions, using a virtual car prototype.

The Deep Orange program immerses automotive engineering students into the world of an OEM as part of their 2-year graduate education. In support of developing the program’s seventh vehicle concept, the students studied the sponsoring brand essence, conducted market research, and made a heuristic assessment of competitor vehicles. The upfront research lead to the definition of target customers and setting vehicle level targets that were broken down into requirements to develop various vehicle sub-systems. The powertrain team was challenged to develop a scalable propulsion concept enabled by a common vehicle architecture that allowed future customers to select (at the point of purchase) among various levels of electrification best suiting their needs and personal desires. Four different configurations were identified and developed: all-electric, two plug-in hybrid electric configurations, and an internal combustion engine only.

The quiet nature of hybrid and electric vehicles has triggered developments in research, vehicle manufacturing and legal requirements. Currently, three countries require fitting an Approaching Vehicle Alerting System (AVAS) to every new car capable of driving without a combustion engine. Various other geographical areas and groups are in the process of specifying new legal requirements. In this paper, the design challenges in the on-going process of designing the sound for quiet cars are discussed. A proposal is issued on how to achieve the optimum combination of safety, environmental noise, subjective sound character and technical realisation in an iterative sound design process. The proposed sound consists of two layers: the first layer contains tonal components with their pitch rising along with vehicle speed in order to ensure recognisability and an indication of speed.

Recent developments in the prediction of the contribution of wind noise to the interior SPL have opened a realm of new possibilities. The main physical mechanisms related to noise generation within a turbulent flow and the vibro-acoustic transmission through the vehicle greenhouse is nowadays better understood. Several simulation methods such as CFD, FEM, BEM, FE/SEA Coupled and SEA can be coupled together to represent the physical phenomena involved. The main objective being to properly represent the convective and acoustic component within the turbulent flow to ensure proper computation of the wind noise contribution to the interior SPL of a vehicle.

The requirement of the start of the internal combustion engine (ICE) not only at vehicle standstill is new for full hybrid electric vehicles in comparison to conventional vehicles. However, the customer will not accept any deterioration with respect to dynamics and comfort. ICE-starting-systems and -strategies have to be designed to meet those demands. Within this research, a method was developed which allows a reproducible maneuver-based analysis of ICE-starts. In the first step, a maneuver catalogue including a customer-oriented maneuver program with appropriate analysis criteria was defined. Afterwards, the maneuvers were implemented and verified in a special test bench environment. Based on the method, two sample hybrid vehicles were benchmarked according to the maneuver catalogue. The benchmarking results demonstrate important dependencies between the criteria-based assessment of ICE-starts and the embedded ICE-starting-system and -strategy.

Modern exhaust systems contain not only a piping network to transport hot gas from the engine to the atmosphere, but also functional components such as the catalytic converter and turbocharger. The turbocharger is common place in the automotive industry due to their capability to increase the specific power output of reciprocating engines. As the exhaust system is a main heat source for the under body of the vehicle and the turbocharger is located within the engine bay, it is imperative that accurate surface temperatures are achieved. A study by K. Haehndel [1] implemented a 1D fluid stream as a replacement to solving 3D fluid dynamics of the internal exhaust flow. To incorporate the 3D effects of internal fluid flow, augmented Nusselt correlations were used to produce heat transfer coefficients. It was found that the developed correlations for the exhaust system did not adequately represent the heat transfer of the turbocharger.

Today, LRI is a proven manufacturing technology for both small and large scale structures (e.g. sailboats) where, in most cases, experience and limited prototype experimentation is sufficient to get a satisfactory design. However, large scale aerospace (and other) structures require reproducible, high quality, defect free parts, with excellent mechanical performance. This requires precise control and knowledge of the preforming (draping and manufacture of the composite fabric preforms), their assembly and the resin infusion. The INFUCOMP project is a multi-disciplinary research project to develop necessary Computer Aided Engineering (CAE) tools for all stages of the LRI manufacturing process. An ambitious set of developments have been undertaken that build on existing capabilities of leading drape and infusion simulation codes available today. Currently the codes are only accurate for simple drape problems and infusion analysis of RTM parts using matched metal molds.

Within the pre-development phase of a vehicle validation process, the role of computational simulation is becoming increasingly prominent in efforts to ensure thermal safety. This gain in popularity has resulted from the cost and time advantages that simulation has compared to experimental testing. Additionally many of these early concepts cannot be validated through experimental means due to the lack of hardware, and must be evaluated via numerical methods. The Race Track Simulation (RTS) can be considered as the final frontier for vehicle thermal management techniques, and to date no coherent method has been published which provides an efficient means of numerically modeling the temperature behavior of components without the dependency on statistical experimental data.

The thermal prediction of a vehicle under-body environment is of high importance in the design, optimization and management of vehicle power systems. Within the pre-development phase of a vehicle's production process, it is important to understand and determine regions of high thermally induced stress within critical under-body components. Therefore allowing engineers to modify the design or alter component material characteristics before the manufacture of hardware. As the exhaust system is one of the primary heat sources in a vehicle's under-body environment, it is vital to predict the thermal fluctuation of surface temperatures along corresponding exhaust components in order to achieve the correct thermal representation of the overall under-body heat transfer. This paper explores a new method for achieving higher accuracy exhaust surface temperature predictions.

For diesel engines to meet current and future emissions levels, the amount of EGR required to reach these levels has increased dramatically. This increased EGR has posed big challenges for conventional turbocharger technology to meet the higher emissions requirements while maintaining or improving other vehicle attributes, to the extent that some OEMs resort to multiple turbocharger configurations. These configurations can include parallel, series sequential, or parallel - series turbocharger systems, which would inevitably run into other issues, such as cost, packaging, and thermal loss, etc. This study, as part of a U.S. Department of Energy (USDoE) sponsored research program, is focused on the experimental evaluation of the emission and performance of a modern diesel engine with an advanced single stage turbocharger.

Despite increasingly stringent crash requirements, the body structures of future mainstream production cars need to get lighter. Carbon fiber reinforced polymer (CFRP) composites with a density 1/5th of steel and very high specific energy absorption represent a material technology where substantial mass can be saved when compared to traditional steel applications. BMW have addressed the demanding challenges of producing several hundred composite Body-in-White (BIW) assemblies a day and are committed to significant adoption of composites in future vehicle platforms, as demonstrated in the upcoming i3 and i8 models. A next step to further integrate composites into passenger cars is for primary structural members, which also perform critical roles in passive safety by absorbing large amounts of energy during a crash event.