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When employing in-car active sound generation (ASG) and active noise cancellation (ANC), the accurate knowledge of the vehicle interior sound pressure distribution in magnitude as well as phase is paramount. Revisiting the ANC concept, relevant boundary conditions in spatial sound fields will be addressed. Moreover, within this study the controllability and observability requirements in case of ASG and ANC were examined in detail. This investigation focuses on sound pressure measurements using a 24 channel microphone array at different heights near the head of the driver. A shaker at the firewall and four loudspeakers of an ordinary in-car sound system have been investigated in order to compare their sound fields. Measurements have been done for different numbers of passengers, with and without a dummy head and real person on the driver seat. Transfer functions have been determined with a log-swept sine technique.

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.

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.

The paper describes a new methodology for a closed loop driving style detection, a vehicle driveability character evaluation and a control unit for an adaptation of the vehicle character according to the driving style. During driving the vehicle character is adapted to the driver, using the potential of modern torque based drive by wire engine control systems of gasoline and diesel engines. The methodology leads to a completely new human - vehicle interaction, the driver creates his own unique vehicle character. The vehicle owner is able to form a mass produced vehicle according to his demands. A typical drawback of globalisation, a loss of identification between owner and product can be avoided by the presented methodology. The basic structure of the evaluation and control strategies are shown as well as objective and subjective results of increased driving pleasure and higher driver identification due to increased sportiness and spontaneity up to 100%.

Future demands regarding emissions, fuel consumption and driveability lead to complex engine and power train control systems. The calibration of the increasing number of free parameters in the ECU's contradicts the demand for reduced time in the power train development cycle. This paper will focus on the automatic, unmanned closed loop optimization of driveability quality on a high dynamic engine test bed. The collaboration of three advanced methods will be presented: Objective real time driveability assessment, to predict the expected feelings of the buyers of the car Automatic computer assisted variation of ECU parameters on the basis of statistical methods like design of experiments (DoE). Thus data are measured in an automated process allowing an optimization based on models (e.g. neural networks).

Apart of other aspects, the interior sound of a passenger car brand has to meet customer expectations. For optimizing the sound of a passenger car, target sounds have first to be established via the operating range of the vehicle. For an effective sound engineering approach an objective description and evaluation of vehicle interior sound is beneficial. Such an objective description guarantees the effective and reproducible implementation of the required brand sound in the vehicle development process. In such a process it is necessary to reduce on the one hand annoying undesired noise aspects and to create on the other hand the relevant and necessary noise parameters to meet the target sounds head on.

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.

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 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.

Best fuel efficiency is one of the core requirements for commercial vehicles in India. Consequently it is a central challenge for commercial vehicle OEMs to optimize the entire powertrain, hence match engine, transmission and rear axle specifications best to the defined application. The very specific real world driving conditions in India (e.g. traffic situations, road conditions, driver behavior, etc.) and the large number of possible commercial powertrain combinations request an efficient and effective development methodology. This paper presents a methodology and tool chain to specify and develop commercial powertrains in a most efficient and effective way. The methodology is based on the measurement of real world driving scenarios, identification of representative Real World Driving Profiles and vehicle system simulation which allows extended analysis of the road topography, the traffic situation as well as the driver behavior.

With the increased number of variants, the preservation of a brand-specific vehicle DNA becomes more and more important. Paired with growing customer expectations, brand DNA can be a crucial point in the decision-making process of buying a new vehicle. Whereas the customer will assess the DNA subjectively during driving by evaluating the vehicle drive quality (“driveability”), most manufacturers are not merely relying on subjective evaluations by having test drivers perform maneuvers with prototype vehicles. Nowadays, the assessment is performed objectively during the vehicle development process. As a supporting measure, the Anstalt für Verbrennungskraftmaschinen List (AVL) has made the objective assessment tool AVL-DRIVE commercially available. Up to now, the AVL-DRIVE ratings had to be manually analyzed and checked for outliers. Low ratings and high deviations to a priori specified target values are a good starting point for the search of outliers.

Modern safety and comfort features must behave country specific to the local environment and traffic conditions in order to gain end consumers’ trust and strengthening OEMs market success respectively. In order to achieve this, a new methodology was developed. In this paper, the approach for designing advanced driving assistance systems (ADAS) with a tailored controller behavior optimized for country specific market expectations like in India is described. Furthermore, the definition of objective performance and calibration targets with automated evaluation of target fulfillment will be deeply discussed. The method is focused on saving time at calibration and validation without compromising the quality of ADAS features. Local market specific driving behavior is investigated and measurement data from real-world driving collected. Data clustering via maneuver detection is performed automatically, which is saving time and effort.

India striving for carbon neutrality influences futures powertrain architecture of commercial vehicles. The use of CO2-free drives as battery electric have been demonstrated for various applications. The productivity still is a challenge due to missing high power charging infrastructure or limited range. This draws the attention to the use of sustainable fuels due to lower refueling times. The hydrogen engine got highest attention in the last couple of years. For markets as the EU the driver for hydrogen is the CO2 emission reduction, whereas for markets as India hydrogen offers the additional opportunity for more independence from fossil imports. Different OEMs all over the world have converted diesel engines to hydrogen operation with strong focus on performance and emission demonstration, so far with limited technology readiness of different key components.