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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.

The reduction of vehicle exhaust particle emissions is a success story of European legislation. Various particle number (PN) counters and calibration procedures serve as tools to enforce PN emission limits during vehicle type approval (VTA) or periodical technical inspection (PTI) of in-use vehicles. Although all devices and procedures apply to the same PN-metric, they were developed for different purposes, by different stakeholder groups and for different target costs and technical scopes. Furthermore, their calibration procedures were independently defined by different stakeholder communities. This frequently leads to comparability and interpretation issues. Systematic differences of stationary and mobile PN counters (PN-PEMS) are well-documented. New, low-cost PTI PN counters will aggravate this problem. Today, tools to directly compare different instruments are scarce.

To meet LEV and EU Stage III emission requirements, it is necessary for new catalytic converters to be designed which exceed light-off temperature as quickly as possible. The technical solutions are secondary air injection, active heating systems such as the electrically heated catalytic converter, and the close coupled catalytic converter. Engine control functions are extensively used to heat the converter and will to play a significant role in the future. The concept of relocating the converter to a position close to the engine in an existing vehicle involves new conflicts. Examples include the space requirements, the thermal resistance of the catalytic coating and high temperature loads in the engine compartment.

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.

A joint study was conducted between BMW and Goodyear with the objective of analysing the cause and identifying methods to reduce the structure-borne interior noise in a vehicle driving on rough road surfaces. A vibro-acoustic characterization of the car was performed by measuring the car vibro-acoustic transfer functions and by using a transfer path analysis technique to identify the main suspension parts affecting the interior noise at target frequencies. The vibration transmissibility characteristics of the tire were measured and also simulated by Finite Element in [1-200Hz] frequency range. The vibro-acoustic interaction between the tire and car sub-systems was examined. A Finite Element sensitivity analysis was used to define and build new prototype tires. A 3dB(A) interior noise improvement was obtained with these new tires at target frequencies.

In this contribution functional safety is discussed from a car manufacturer's point of view. Typical elements of a safety standard concerning safety activities during the product development process are described as well as management and other supporting processes. Emphasis is laid on the aspect of risk assessment and the determination of safety classes. Experiences with methods for safety analysis like FTA or FMEA are discussed and pros and cons of quantitative safety assessment are argued.

In the early stages of conceptual design the available geometric data are very coarse and the lifespan of a design idea is very short. The structural evaluation and improvement of a design has to take both facts into account. Its focus is on the total vehicle and its performance. This can be estimated by a modeling technique, which is adequate for the lack of geometric details. Static and dynamic global stiffness as well as some aspects of crash and NVH have to be considered. Optimization will lead to the proper sizing and some indication of the potential of the structure. In order to maintain high quality standards this approach has to be supported by specialized CAE tools and extensive rules on modeling techniques and analysis procedures.

A new simulation tool was established and approved by TRW as part of the continuous improvement of the development process. This tool allows the OEM and the system supplier to keep high quality even with further reduced development times. The introduction of the tool in a side air-bag development program makes it possible to ensure high development confidence with a reduced number of vehicle crash tests and late availability of interior component parts.

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.

A local Gaussian process regression approach is presented, which allows to model nonlinearities of internal combustion engines more accurate than global Gaussian process regression. By building smaller models, the prediction of local system behavior improves significantly. In order to predict a value, the algorithm chooses the nearest training points. The number of chosen training points depends on the intensity of estimated nonlinearity. After determining the training points, a model is built, the prediction performed and the model discarded. The approach is demonstrated with a benchmark system and air charge test bed measurements. The measurements are taken from a turbocharged SI gasoline engine with both variable inlet valve lift and variable inlet and exhaust valve opening angle. The results show how local Gaussian process regression outmatches global Gaussian process regression concerning model quality and nonlinearities in particular.

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.

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.

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.

Handling characteristics, ride comfort and active safety are customer relevant attributes of modern premium vehicles. Electronic control units offer new possibilities to optimize vehicle performance with respect to these goals. The integration of multiple control systems, each with its own focus, leads to a high complexity. BMW and ITK Engineering have created a tool to tackle this challenge. A simulation environment to cover all development stages has been developed. Various levels of complexity are addressed by a scalable simulation model and functionality, which grows step-by-step with increasing requirements. The simulation environment ensures the coherence of the vehicle data and simulation method for development of the electronic systems. The article describes both the process of the electronic control unit (ECU) development and positive impact of an integrated tool on the entire vehicle development process.

This paper presents an object-oriented method customized for a tool-assisted development of car software components. Tough market conditions motivate smart software development. ASCET SD is a tool to generate target code from graphic specifications, avoiding costly programming in C. But ASCET lacks guidelines on what to do, how to do it, in what order, like a fully equipped kitchen without a cooking book. Plans to employ the tool for BMW vehicle software sparked off demand for an adequate, object-oriented real-time methodology. We show how to scan the methodology market in order to adopt an already existing method for this purpose. The result of the adaptation of a chosen method to ASCET SD is a pragmatic version of ROOM, which we call BROOM. We present a modeling guidebook that includes process recommendations not only for the automotive sector, but for real-time software development in general.

Apart from the reduction of engine-out emissions from the powerplant, the development of an efficient and reliable catalytic converter heating system is an important task of automotive engineering in the future to meet standards that will require reduction of cold start emissions. Carrying out a comprehensive study in this field, BMW has tested and evaluated possible solutions to this challenge. In additon to the electrically heated catalytic converter (E-cat) and the afterburner chamber, an incorporated burner system would meet the requirement for fast catalyst light-off in the future, particularly in the case of larger engines.

The production of the BMW ALPINA B12 5.7 with Switch-Tronic transmission provides the markets of Europe and Japan with an exclusive, luxury-orientated, high performance limited series limousine. This is the first vehicle worldwide to be fitted with the progressive exhaust gas aftertreatment technology known as the Electrically Heated Catalyst (EHC), in which the effectiveness of the power utilized is increased significantly by an alternating heating process for both catalytic converters. Only since this achievement has the implementation of the EHC been viable without extensive modification to the battery and alternator. With this exhaust gas aftertreatment concept, the emissions of this high performance vehicle will fall to less than half the maximum permissible for compliance with 1996 emission standards.

If a tail light bulb burns out, the failure will be detected by an electronic light check module. The missing tail light will be substituted by the stop light function. The luminous intensity of the stop light will be automatically reduced to the tail light level. If a car is equipped with rear fog lights, a faulty brake light can be substituted, similarly by a reduced rear fog light. Today the hazard warning signal has the same frequency as the turn signal indicator. If one side of a car is blocked by for example another car then it is not possible to differentiate between the aforementioned signal types. Therefore the hazard warning information is lost. The suggested new hazard warning signal consists of a double-flash with a short break, the time period is nearly unchanged.

Vehicle thermal management (VTM) simulations are becoming increasingly important in the development phase of a vehicle. These simulations help in predicting the thermal profiles of critical components over a drive cycle. They are usually done using two methodologies: (1) Solving every aspect of the heat transfer, i.e., convection, radiation, and conduction, in a single solver (Conjugate Heat Transfer) or (2) Simulating convection using a fluid solver and computing the other two mechanisms using a separate thermal solver (Co-simulation). The first method is usually computationally intensive, while the second one isn’t. This is because Co-simulation reduces the load of simulating all heat transfer mechanisms in a single code. This is one of the reasons why the Co-simulation method is widely used in the automotive industry. Traditionally, the methods developed for Co-simulation processes are load case specific.