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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.

Acoustic comfort of automotive cabins has progressively become one of the key attributes of passenger comfort within vehicle design. Wind noise and the heating, ventilation, and air conditioning (HVAC) system noise are two of the key contributors to noise levels heard inside the car. The increasing prevalence of hybrid technologies and electrification has an associated reduction in powertrain noise levels. As such, the industry has seen an increasing focus on understanding and minimizing HVAC noise, as it is a main source of noise in the cabin particularly when the vehicle is stationary. The complex turbulent flow path through the ducts, combined with acoustic resonances can potentially lead to significant noise generation, both broadband and tonal.

In use cars often drive through the wakes of other vehicles. It has long been appreciated that this imposes a fluctuating onset flow which can excite a structural response in vehicle panels, particularly the bonnet. This structure must be designed to be robust to such excitation to guarantee structural integrity and maintain customer expectations of quality. As we move towards autonomous vehicles and exploit platoons for drag reduction, this onset flow condition merits further attention. The work reported here comprises both measurements and simulation capturing the unsteady pressure distribution over the bonnet of an SUV following a similar vehicle at high speed and in relatively close proximity. Measurements were taken during track testing and include 48 static measurement locations distributed over the bonnet where the unsteady static pressures were recorded.

The aim of the project is to reliably identify the set of constructive features responsible for the highest noise levels in the interior of motor vehicles. A simulation environment based on artificial intelligence techniques such as neural networks and genetic algorithms has been implemented. We used a system identification approach in order to approximate the functional relationship between the target noise series and the sets of constructive parameters corresponding to the cars. The noise levels were measured with a microphone positioned on the driver''s chair, and corresponded to a variation of the engine rotation of 600-900 rot/min. The database includes 45 different cars, each described by vectors of 67 constructive features.

The Energy and Environment Test Centre (EVZ) is a complex comprising three large climatic wind tunnels, two smaller test chambers, nine soak rooms and support infrastructure. The capabilities of the wind tunnels and chambers are varied, and as a whole give BMW the ability to test at practically all conditions experienced by their vehicles, worldwide. The three wind tunnels have been designed for differing test capabilities, but share the same air circuit design, which has been optimized for energy consumption yet is compact for its large, 8.4 m₂, nozzle cross-section. The wind tunnel test section was designed to meet demanding aerodynamic specifications, including a limit on the axial static pressure gradient and low frequency static pressure fluctuations - design parameters previously reserved for larger aerodynamic or aero-acoustic wind tunnels. The aerodynamic design was achieved, in-part, by use of computational fluid dynamics and a purpose-built model wind tunnel.

Thermal management on aircraft has been an important discipline for several decades. However, with the recent generations of high performance aircraft, thermal management has evolved more and more into a critical performance and capability constraint on the whole aircraft level. Fuel continues to be the most important heat sink on high performance aircraft, and consequently the requirements on thermal models of fuel systems are expanding. As the scope of modeling and simulation is widened in general, it is not meaningful to introduce a new isolated modeling and simulation capability. Instead, thermal models must be derived from existing model assets and eventually enable integration across several physical domains. This paper describes such an integrated approach based on the Modelica Fuel System Library and the 3DExperience Platform.

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.

Air charge calibration of turbocharged SI gasoline engines with both variable inlet valve lift and variable inlet and exhaust valve opening angle has to be very accurate and needs a high number of measurements. In particular, the modeling of the transition area from unthrottled, inlet valve controlled resp. throttled mode to turbocharged mode, suffers from small number of measurements (e.g. when applying Design of Experiments (DoE)). This is due to the strong impact of residual gas respectively scavenging dominating locally in this area. In this article, a virtual residual gas sensor in order to enable black-box-modeling of the air charge is presented. The sensor is a multilayer perceptron artificial neural network. Amongst others, the physically calculated air mass is used as training data for the artificial neural network.

Nowadays, a continually growing system complexity due to the development of an increasing number of vehicle concepts in a steadily decreasing development time forces the engineering departments in the automotive industry to a deepened system understanding. The virtual design and validation of individual components from subsystems up to full vehicles becomes an even more significant role. As an answer to the challenge of reducing complete hardware prototypes, the virtual competence in NVH, among other methods, has been improved significantly in the last years. At first, the virtual design and validation of objectified phenomena in analogy to hardware tests via standardized test rigs, e.g. four poster test rig, have been conceived and validated with the so called MBS (Multi Body Systems).

Design of HVAC system plays an important role in acoustic comfort for passengers. With automotive world moving towards electrical vehicles where powertrain noise is low, designing low noise HVAC system is becoming more important. For an automobile manufacturer, ability to predict the production vehicle cabin noise at the early design stage is important as it allows more freedom for design changes, which can be incorporated in the vehicle at lower cost. Although HVAC prototype and system level testing at early design stage is possible for noise estimation but flow field is not visible in test that makes difficult to improve design. CFD simulation can provide detailed information on flow field, noise source strength and location. But in such a simulation, accurate prediction has been a challenge due to the inability of CFD tools to model acoustic absorptive characteristics of interior walls of cabin.

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.

Two models for the forecast of road traffic emissions, independently developed in parallel, are comparatively presented and assessed: EPROG developed by BMW and enlarged by VDA for a national application (Germany) and FOREMOVE, developed for application on European Community scale. The analysis of the methodological character of the two algorithms proves that the models are fundamentally similar with regard to the basic calculation schemes used for the emissions. The same holds true as far as the significant dependencies of the emission factors, and the recognition and incorporation of the fundamental framework referring to traffic important parameters (speeds, mileage and mileage distribution etc) are concerned.

Timing evaluation methods help to design a robust and extendible E/E architecture (electric/electronic). BMW has introduced the systematic application of such methods in the E/E design process within the last three years. Meanwhile, most of the architectural changes are now verified by a tool-based, automatic real-time analysis. This has increased the accuracy of the network planning and productivity of the BMW network department. In this paper, we give an overview of the actual status of timing evaluations in BMW's E/E architecture design. We discuss acceptance criteria, analysis metrics, and design rules, as far as these are related to timing. We look specifically at automation options, as these improve the productivity further. We will see that timing analysis has matured and should be mandatory for application in mass production E/E architecture development. At the same time, there is room for future improvements.

For fuel cell vehicles, it is essential that the hydrogen tank be both compact and have sufficient hydrogen to ensure reasonable driving range for which there is a need to pressurize the hydrogen in the tank at levels much higher than that of atmospheric pressure. Furthermore, fast filling is an important consideration in order to minimize time to refuel hydrogen in the tank. In this article, we investigate a Computational Fluid Dynamics (CFD) methodology to see whether we can simulate the fast filling of the hydrogen tank. We performed simulations on an existing validation case using coupled simulation approach between the PowerFLOW® flow solver and PowerTHERM® the thermal solver. For an accurate simulation at elevated pressure levels, we implemented a real gas behavior that is more accurate than the ideal gas equation of state for under these conditions. We observe good agreement with experimental data for both bulk and local variations in temperature.

Selective Catalytic Reduction (SCR) is a process where one injects an aqueous solution of urea into a diesel exhaust system in order to reduce NOx emissions. The urea solution known as AdBlue® or Diesel Exhaust Fluid (DEF) is stored in a DEF Tank that can under cold weather conditions freeze over. Since AdBlue® is unusable while frozen, we use heaters installed in the tanks to melt AdBlue® with government regulations mandating time required to melt AdBlue® in the tank. In this article, we investigate whether a CFD (Computational Fluid Dynamics) based methodology can accurately evaluate time required in melting AdBlue® for a given DEF Tank and heater coil design for a production vehicle as per standard testing procedure. Simulations used a coupled methodology with PowerFLOW® as the flow solver and PowerTHERM® as the thermal solver. The flow simulation did require an accurate modelling of phase change from solid to liquid for AdBlue®.

This paper presents an aerodynamic degradation study of an iced airfoil, using the Lattice Boltzmann approach with the commercial software PowerFLOW. Three-dimensional numerical simulations were performed with an extruded constant section of the GLC-305 airfoil with a leading-edge double-horn ice shape using periodic boundary conditions. The freestream Reynolds number, based on the chord, is 3.5 million and the Mach number is 0.12. An extensive comparison of the main flow features with experimental data is performed, including aerodynamic coefficients, pressure coefficient distributions, velocity and turbulence contours along with its profiles at several positions, and stagnation streamlines. The drag coefficient agrees well with experiments, in spite of a small shift. Two different wind tunnel measurements, using different measurement techniques, were compared to the CFD results, which mostly stayed in between the experimental data.

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.

The specification of automotive ventilation / defrosting systems has often utilized “trial-and-error” and “prior experience” techniques. But design development and production efficiency has generated a strong interest in using more sophisticated design tools such as computational fluid dynamics. For this purpose a joint experimental and numerical study was undertaken. This comprehensive investigation was divided into two parts. First, the three dimensional defroster flow field was measured using LDA in an actual automobile. Second, LDA and infrared thermography was used to map the flow and temperature fields for a two dimensional jet impinging upon a slanted plate -- a simplified representation of a car defroster geometry.