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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.

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.

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.

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).

The new BMW Aerodynamisches Versuchszentrum (AVZ) wind tunnel center includes a full-scale wind tunnel, "The BMW Windkanal" and an aerodynamic laboratory "The BMW AEROLAB." The AVZ facility incorporates numerous new technology features that provide design engineers with new tools for aerodynamic optimization of vehicles. The AVZ features a single-belt rolling road in the AEROLAB and a five-belt rolling road in the Windkanal for underbody aerodynamic simulation. Each of these rolling road types has distinct advantages, and BMW will leverage the advantages of each system. The AEROLAB features two overhead traverses that can be configured to study vehicle drafting, and both static and dynamic passing maneuvers. To accurately simulate "on-road" aerodynamic forces, a novel collector/flow stabilizer was developed that produces a very flat axial static pressure distribution. The flat static pressure distribution represents a significant improvement relative to other open jet wind tunnels.

The improvement of low-speed MUX-systems in car-body areas gets important in a scenario where on one hand, the possible number of integrated local control units (LCU's) gets larger and on the other hand, the possible versions of a car range from basic to top-of-the-line. Cost and developement time can be reduced if the same MUX-System is used throughout this whole range. A possibility to realize this is the use of data-compression (DC) for data-transmission. Basic configurations integrating only a small number of LCU's of a car-MUX can communicate without using data-compression, whereas for the top-of-the-line versions, the performance can be enhanced using DC only for communication processes between additional control units causing critical peak load situations. Specifically, the use of adaptive algorithms in automotive multiplex systems is a promising way to improve the MUX's capacity performance by minimizing redundant symbols/information in peak-load situations.

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.