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Current developments in automotive industry such as hybrid powertrains and the continuously increasing demands on emission control systems, are pushing complexity still further. Validation of such systems lead to a huge amount of test cases and hence extreme testing efforts on the road. At the same time the pressure to reduce costs and minimize development time is creating challenging boundaries on development teams. Therefore, it is of utmost importance to utilize testing and validation prototypes in the most efficient way. It is necessary to apply high levels of instrumentation and collect as much data as possible. And a streamlined data pipeline allows the fleet managers to get new insights from the raw data and control the validation vehicles as well as the development team in the most efficient way. In this paper we will demonstrate a data-driven approach for validation testing.

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.

The OBD II and EOBD legislation have significantly increased the number of system components that have to be monitored in order to avoid emissions degradation. Consequently, the algorithm design and the related calibration effort is becoming more and more challenging. Because of decreasing OBD thresholds, the monitoring strategy accuracy, which is tightly related with the components tolerances and the calibration quality, has to be improved. A model-based offline simulation of the monitoring strategies allows consideration of component and sensor tolerances as well as a first calibration optimization in the early development phase. AVL applied and improved a methodology that takes into account this information, which would require a big effort using testbed or vehicle measurements. In many cases a component influence analysis is possible before hardware is available for testbed measurements.

Vehicle driveability evolves more and more as a key decisive factor for marketability and competitiveness of passenger cars, since the final decision of customers to buy a car is usually taken after a more or less intensive test drive. Car manufacturers currently evaluate vehicle driveability with subjective assessments and by having their experienced test drivers fill out form sheets. These assessments are time and cost intensive, limited in repeatability and not objective. The real customer requirements cannot be recognized in detail with this method. This paper describes a completely new approach for an objective and real time evaluation of relevant driveability criteria, for use in a vehicle and on a high dynamic test bed. The vehicle application enables an objective comparison between vehicles and an application as a development tool in many development and calibration phases, where ever fast and objective driveability results are required.

Worldwide OBD legislation has and will be tightened drastically. In the US, OBD II for PC and the introduction of HD OBD for HD vehicles in 2010 will be the next steps. Further challenges have come up with the introduction of active exhaust gas aftertreatment components to meet the lower future emission standards, especially with the implementation of combined DPF-De-NOx-systems for PC and HD engines. Following such an increase in complexity, more comprehensive algorithms and software have to be developed to cope with the legislative requirements for exhaust gas aftertreatment devices. The calibration has to assure the proper functionality of OBD under all driving situations and ambient conditions. The increased complexity can only be mastered when new and efficient tools and methodologies are applied for both algorithm design and calibration. Consequently, OBD requirements have to be taken into account right from the start of engine development.

Today combustion analysis has to be used in every step of the engine development process and is no longer a tool for some specialists but most test bed operators have to deal with combustion analysis (also called Indicating). AVL reacts on the widened area of application and the broad spread of the Indicating measurement technology by introduction of user friendly user interfaces, which make the work during preparation of measurements as well as during measurements itself easier.

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 Advanced Lighting Simulation (ALS) is a development tool for systematically investigating and optimizing the Adaptive Light Control (ALC) system to provide the driver with improved headlamps and light distributions. ALS is based on advanced CA-techniques and modern validation facilities. To improve night time traffic safety the BMW lighting system ALC has been developed and optimized with the help of ALS. ALC improves the headlamp illumination by means of continuous adaptation of the headlamps according to the current driving situation and current environment. BMW has already implemented ALC prototypes in real vehicles to demonstrate the advantages on the real road.

This paper presents new comfort and convenience features in the luxury segment and focuses especially on Comfort Access and iDrive. The Comfort Access System offers the customer the possibility of unlocking the vehicle without active use of a key, of starting the engine and at the end of the journey of locking the car again. The aim of the iDrive concept was to enable intuitive operation of the various functions with simultaneously improved ergonomics. Both, a monitor and a controller with its variable haptic are the concept’s innovation. In addition, this paper also discusses future ECU (Electronic Control Unit) networks for body electronics. The focus is on package-driven ECU network architecture, having many functions developed by different suppliers on a single ECU.

Local air pollution, noise emissions as well as global CO2 reduction and public pressure drive the need for zero emission transport solutions in urban areas. OEMs are currently developing battery electric vehicles with the focus to provide emission free urban transportation combined with lowest total cost of ownership and consequently a positive business case for the end customers. Thereby the main challenges are electric range, product cost, system weight, vehicle packaging and durability. Hence they are the main drivers in current developments. In this paper AVL describes two of its truck and bus solutions - a modular battery concept as well as a concept for an integrated electric axle. Based on the vehicle requirements concept designs for both systems are presented.

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.

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 reduction of CO₂ emissions represents a major goal of governments worldwide. In developed countries, approximately 20% of the CO₂ emissions originate from transport, one third of this from commercial vehicles. CO₂ emission legislation is in place for passenger cars in a number of major markets. For commercial vehicles such legislation was also already partly published or is under discussion. Furthermore the commercial vehicles market is very cost sensitive. Thus the major share of fuel cost in the total cost of ownership of commercial vehicles was already in the past a major driver for the development of efficient drivetrain solutions. These aspects make the use of new powertrain technologies, specifically hybridization, mandatory for future commercial powertrains. While some technologies offer a greater potential for CO₂ reduction than others, they might not represent the overall optimum with regard to the total cost of ownership.

The development process of a combustion engine is now a days strongly influenced by future emission regulations which require further reduction in fuel consumption and precise control of combustion process based on Intake air measurement, during engine development. Intake air flow meters clearly differentiate themselves from typical industrial gas flow meters because of their ability to measure extremely dynamic phenomenon of combustion engine. Thus, high internal data acquisition rate, short response time, ability to measure pulsating and reverse flows with lower measurement uncertainty are the factors that ensures the reliability of the results without being affected by ambient influences, sensor contamination or sensor aging. The AVL developed FLOWSONIX™ is based on ultrasonic transit time measuring principle with broad-band Capacitive Ultrasonic Transducer (CUT) characterized by an excellent air impedance matching strongly distinguishes itself by fulfilling all those requirements.

The potential to reduce the cost of embedded software by standardizing the application behavior for Automotive Body and Comfort domain functions is explored in this paper. AUTOSAR, with its layered architecture and a standard definition of the interfaces for Body and Comfort application functions, has simplified the exchangeability of software components. A further step is to standardize the application behavior, by developing standard specifications for common Body and Comfort functions. The corresponding software components can be freely exchanged between different OEM/Tier-1 users, even if developed independently by multiple suppliers. In practice, individual OEM users may need to maintain some distinction in the functionality. A method of categorizing the specifications as ‘common’ and ‘unique’, and to configure them for individual applications is proposed. This allows feature variability by means of relatively simple adapter functions.

The safety of BEVs in driving, charging and parking condition is essential for the success of electrification in automotive industry as well as key driver of any future development of Li-Ion HV battery. AVL has developed a unique simulation approach in which the multi-physical behavior of the single cell in thermal runaway is modelled and applied to module, pack or vehicle level. In addition and beside this cell behavior, various more physical phenomena during thermal propagation on pack level are considered and predicted by the simulation method: component melting, ignition and flammibilty of venting gas and HV failures.

In studying H2S emissions, it is desirable to have an analytical technique which is rapid, continuous, accurate and easy to use in a laboratory or vehicle exhaust environment. Typically, H2S has been measured using the EPA impinger method with collection times on the order of 1 to 2 minutes. Other techniques have been developed with significantly shorter response times. However, it has been shown that the major release of H2S occurs in less than 20 seconds after a vehicle changes from rich to lean operation. Therefore, it is highly desirable to have an H2S analytical technique with a response time of less than 10 seconds. In this paper, the benefits of use of a chemical ionization mass spectrometer (CIMS) to continuously monitor H2S and SO2, emissions are reported. Using the CIMS technique, the effects of several operating parameters on the release of H2S and SO2 from automotive catalysts were studied.

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.

Increasing demand for utilities like navigation systems or user-defined electronic phonebooks on one hand and sophisticated engine and gear controls on the other hand leads to growing bus load between distributed local control units. This paper shows the benefits and the characteristics of various state of the art data-compression algorithms and their impact on typical automotive multiplex dataclasses. The evaluation and optimization of promising algorithms can be done via a proposed “communications prototyping”-approach. The hardware/software components of such a rapid prototyping package are outlined. Finally, first performance results of suitable data-compression measures are presented.

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.