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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.

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.

It is particularly easy to get tunnel vision as a domain expert, and focus only on the improvements one could provide in their area of expertise. To make matters worse, many Original Equipment Manufacturers (OEMs) are silo-ed by domain of expertise, unconsciously promoting this single mindedness in design. Unfortunately, the successful and profitable development of a vehicle is dependent on the delicate balance of performance across many domains, involving multiple physics and departments. Taking for instance the design of a Heating, Ventilation & Air Conditioning (HVAC) system, the device’s primary function is to control the climate system in vehicle cabins, and more importantly to make sure that critical areas on the windshield can be defrosted in cold weather conditions within regulation time. With the advent of electric and autonomous vehicles, further importance is now also placed on the energy efficiency of the HVAC, and its noise.

It is essential to include uncertainties in the simulation process in order to perform reliable vibroacoustic predictions in the early design phase. In this contribution, uncertainties are quantified using the generalized Polynomial Chaos (gPC) expansion in combination with a Finite Element (FE) model of a vehicle body in white. It is the objective to particularly investigate the applicability of the gPC method in the industrial context with a high number of uncertain parameters and computationally expensive models. A non-intrusive gPC expansion of first and second order is implemented and the approximation of a stochastic response process is compared to a Latin Hypercube sampling based reference solution with special regard to accuracy and computational efficiency. Furthermore, the method is examined for other input distributions and transferred to another FE model in order to verify the applicability of the gPC method in practical applications.

During the last decades, big steps have been taken towards a realistic simulation of NVH (Noise Vibration Harshness) behavior of vehicles using the Finite Element (FE) method. The quality of these computation models has been substantially increased and the accessible frequency range has been widened. Nevertheless, to perform a reliable prediction of the vehicle vibroacoustic behavior, the consideration of uncertainties is crucial. With this approach there are many challenges on the way to valid and useful simulation models and they can be divided into three areas: the input uncertainties, the propagation of uncertainties through the FE model and finally the statistical output quantities. Each of them must be investigated to choose sufficient methods for a valid and fast prediction of vehicle body vibroacoustics. It can be shown by rough estimation that dimensionality of the corresponding random space for different types of uncertainty is tremendously high.

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.

For highly automated driving, commercial vehicles require an Electric/Electronic (E/E) architecture, which - in addition to sensor fusion - ensures safety-critical processes such as steering and braking at all times. Among other things, a redundant 24 V supply with corresponding disconnection is required. The battery switch is a key component. Commercial, construction, and agricultural vehicles (CAV) need to operate at the highest possible availability and the lowest possible cost of ownership. This is why automated and autonomous driving has the potential to revolutionize the CAV sector. Driverless machines can be operated around the clock and almost non-stop. Platooning allows automated, interconnected trucks to drive in a convoy and very close to each other. Platooning saves fuel.

Sensing and acting elements to guarantee the locking functions of seat belt retractors can emit noise when the retractor is subjected to externally applied vibrations. For these elements to function correctly, stiffness, inertia and friction needs to be in tune, leading to a complex motion resistance behavior, which makes it delicate to test for vibration induced noise. Requirements for a noise test are simplicity, robustness, repeatability, and independence of laboratory and test equipment. This paper reports on joint development activities for an alternative test procedure, involving three test laboratories with different equipment. In vehicle observation on parcel shelf mounted retractors, commercially available test equipment, and recent results from multi-axial component tests [1], set the frame for this work. Robustness and reliability of test results is being analyzed by means of sensitivity studies on several test parameters.

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.

From an acoustical point of view, the integration of seatbelt retractors in a vehicle is a real challenge that has to be met early in the vehicle development process. The buzz and rattle noise of seat belt retractors is a weak yet disturbing interior noise. Street irregularities excite the wheels and this excitation is transferred via the car body to the mounting location of the retractor. Ultimately, the inertia sensor of the locking mechanism is also excited. This excitation can be amplified by structural resonances and generate a characteristic impact noise. The objective of this paper is to describe a simulation method for an early development phase that predicts the noise-relevant low frequency local modes and consequently the contact of the retractor with the mounting panel of the car body via the finite element method.

Over the past decades, interior noise from wind noise or engine noise have been significantly reduced by leveraging improvements of both the overall vehicle design and of sound package. Consequently, noise sources originating from HVAC systems (Heat Ventilation and Air Conditioning), fans or exhaust systems are becoming more relevant for perceived quality and passenger comfort. This study focuses on HVAC systems and discusses a Flow-Induced Noise Detection Contributions (FIND Contributions) numerical method enabling the identification of the flow-induced noise sources inside and around HVAC systems. This methodology is based on the post-processing of unsteady flow results obtained using Lattice Boltzmann based Method (LBM) Computational Fluid Dynamics (CFD) simulations combined with LBM-simulated Acoustic Transfer Functions (ATF) between the position of the sources inside the system and the passenger’s ears.

Highly automated driving (HAD) is under rapid development and will be available for customers within the next years. However the evidence that HAD is at least as safe as human driving has still not been produced. The challenge is to drive hundreds of millions of test kilometers without incidents to show that statistically HAD is significantly safer. One approach is to let a HAD function run in parallel with human drivers in customer cars to utilize a fraction of the billions of kilometers driven every year. To guarantee safety, the function under test (FUT) has access to sensors but its output is not executed, which results in an open loop problem. To overcome this shortcoming, the proposed method consists of four steps to close the loop for the FUT. First, sensor data from real driving scenarios is fused in a world model and enhanced by incorporating future time steps into original measurements.

Functional safe products conforming to the ISO 26262 standard are getting more important for automotive applications wherein electronic takes more and more response for safety relevant operations. Consequently safety mechanisms are needed and implemented in order to reach defined functional safety targets. To prove their effectiveness diagnostic coverage provides a measurable quantity. A straight forward safety mechanism for sensor systems can be established by redundant signal paths measuring the same physical quantity and subsequently performing an independent output difference-check that decides if the data can be transmitted or an error message shall be sent. This paper focuses on the diagnostic coverage figure calculation of such data correlation-checks for linear sensors which are also shown in ISO 26262 part5:2011 ANNEX D2.10.2.

The constant motivation for lower fuel consumption and emission levels has always been in the minds of most auto makers. Therefore, it is important to have precise control of the fuel being delivered into the engine. Gasoline Port fuel injection has been a matured system for many years and cars sold in emerging markets still favor such system due to its less system complexity and cost. This paper will explain injection control strategy of today during development, and especially the injector dead-time compensation strategy in detail and how further improvements could still be made. The injector current profile behavior will be discussed, and with the use of minimum hardware electronics, this paper will show the way for a new compensation strategy to be adopted.

In recent years, we see more and more ECUs integrating a huge number of application software components. This process mostly results from the increasing amount of so called in-house software in various fields like electric-drive, chassis and driver assistance systems. The software development for these systems is partially moved from the supplier to the car manufacturers. Another important trend is the introduction of new network architectures intending to meet the growing communication requirements. For such ECUs the software integration scenarios become more complicated, as more quality of service requirements with regards to timing, safety and security need to be considered [2]. Multi-core microcontrollers offer even more potential variants for integration scenarios. Understanding the interaction between the different software components, not only from a functional, but also from a timing view, is a key success factor for modern electronic systems [6,7,8,9].

The modern day power MOSFET is constructed using the latest technology in order to minimize the drain source resistance. The latest MOSFET technologies are capable of achieving the same drain to source resistance with a smaller MOSFET die than previous generations which will directly lead to increased thermal resistance and limited energy handling capability. This paper will discuss the Safe Operating Area of power MOSFETs and how to assess new MOSFET technology.

The German funded project ARAMiS included work on several demonstrators one of which was a multicore approach on large scale software integration (LSSI) for the automotive domain. Here BMW and Audi intentionally implemented two different integration platforms to gain both experience and real life data on a Hypervisor based concept on one side as well as using only native AUTOSAR-based methods on the other side for later comparison. The idea was to obtain figures on the added overhead both for multicore as well as safety, based on practical work and close-to-production implementations. During implementation and evaluation on one hand there were a lot of valuable lessons learned about multicore in conjunction with safety. On the other hand valuable information was gathered to make it finally possible to set up a cost model for estimation of potential overhead generated by different integration approaches for safety related software functions.

This paper presents a reliability study of a directly cooled IGBT module after a test drive of 85,000 Km in a fuel cell electric vehicle, as well as of an indirectly cooled IGBT module after a test drive of 200,000km in a hybrid car on public roads. At the end of the test drive, the inverter units were disassembled and analyzed with regard to the lifetime consumption. First, electrical measurements were carried out and the results were compared with the ones obtained directly after module production (End of Line test). After that, ultrasonic microscopy was performed in order to investigate any delamination in the solder layers. As a third step, an optical inspection was performed to monitor damages in the housing, formation of cracks or degradation of wire bonds. The results show none of the depicted failure modes could be found on the tested power modules after the field test. Obviously, no significant life time consumption could be observed.

This paper introduces an innovative approach, named synergetic 1D-3D-Coupling, by using synergy effects of 1D and 3D simulation in order to bring down modeling and simulation efforts. At the same time the methodology sustains the spatial resolution of a 3D model. This goal is reached by reducing the 3D fluid side with its time consuming continuity, momentum, energy and turbulence equations to a simple but precise 1D model. Because of the solid structure staying three dimensional, heat flux direction and spatial resolution have 3D accuracy but short calculation times due to the simple heat diffusion equation to be solved. The 1D model is represented by an automatically generated equation system which is capable of considering transient effects. The energy transfer between 1D fluid model and 3D structure model is realized through a neutral 1D-3D-coupling program and the application of the fluid element specific Nusselt correlations.