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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.

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.

Driver errors cause a majority of all car accidents. Forward collision avoidance systems aim at avoiding, or at least mitigating, host vehicle frontal collisions, of which rear-end collisions are one of the most common. This is done by either warning the driver or braking or steering away, respectively, where each action requires its own considerations and design. We here focus on forward collision by braking, and present a general method for calculating the risk for collision. A brake maneuver is activated to mitigate the accident when the probability of collision is one, taking all driver actions into considerations. We describe results from a simulation study using a large number of scenarios, created from extensive accident statistics. We also show some results from an implementation of a forward collision avoidance system in a Volvo V70. The system has been tested in real traffic, and in collision scenarios (with an inflatable car) showing promising results.

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.

Vehicle dynamics development relies on subjective assessments (SA), which is a resource-intensive procedure requiring both expert drivers and vehicles. Furthermore, development projects becoming shorter and more complex, and increasing demands on quality require higher efficiency. Most research in this area has focused on moving from physical to virtual testing. However, SA remains the central method. Less attention has been given to provide better tools for the SA process itself. One promising approach is to introduce computer-tablets to aid data collection, which has proven to be useful in medical studies. Simple software solutions can eliminate the need to transcribe data and generate more flexible and better maintainable questionnaires. Tablets’ technical features envision promising enhancements of SA, which also enable better correlations to objective metrics, a requirement to improve CAE evaluations.

Maintaining the current ratio between certified and the customer-observed fuel consumption even with future required levels poses a considerable challenge. Increasing the efficiency of the driveline enables certified fuel consumption down to a feasible level in the order of 80 g CO₂/km using fossil fuels. Mainly affecting off-cycle fuel consumption, energy amounts used to create good interior climate as well as energy-consuming options and features threaten to further increase. Progressing urbanization will lead to decreasing average vehicle speeds and driving distances. Highly efficient powertrains come with decreased amounts of waste energy traditionally used for interior climate conditioning, thus making necessary a change of auxiliary 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 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.

Many accidents are road departures because of the drivers' lack of attention. This is in many cases due to distraction, drowsiness or intoxication. The Haptic Lane Departure Warning System described here is intended as an active safety system, thus aiming at decreasing the amount of unwanted lane departures. The challenge in the development of such kinds of functions lies in the determination of dangerous situations and the design of appropriate warning/intervention strategies. The system is intended to go unnoticed with the driver and intervenes only in instances where the driver mismanages steering control. Unlike systems which issue an audible sound, the type of warning is a tactile feedback via the steering wheel. This torque is designed in a way that it communicates to the driver the appropriate steering wheel angle required in order to come back in lane.

One way of avoiding crashes or mitigating the consequences of a crash is to apply an autonomous braking system. Quantifying the benefit of such a system in terms of injury reduction is a challenge. At the same time it is a fundamental input into the vehicle development process. This paper describes a method to estimate the effectiveness of reducing speed prior to impact. A holistic view of quantifying the benefit is presented, based on existing real life crash data and basic dynamic theories. It involves a systematic and new way of examining accident data in order to extract information concerning pre-crash situations. One problem area when implementing collision mitigation systems is being able to achieve sufficient target discrimination. The results from the case study highlight frontal impact situations from real world accident data that have the greatest potential in terms of improving accident outcome.

Bushing elasticity is one of the most important compliance factors that significantly influence driving behavior. The deformations of the bushings change the wheel orientations under external forces. Another important factor of bushing compliance is to provide a comfortable driving experience by isolating the vibrations from road irregularities. However, the driving comfort and driving dynamics are often in conflict and need to be balanced in terms of bushing compliance design. Specifically, lateral force steer and brake force steer are closely related to safety and stability and comprises must be minimized. The sensitivity analysis helps engineers to understand the critical bushing for certain compliance attributes, but optimal balancing is complicated to understand. The combination of individual bushing stiffness must be carefully set to achieve an acceptable level of all the attributes.

In 1993 new European legislation regarding side-markers for passenger cars became effective. Volvo requested the TNO-Human Factors Research Institute (HFRI) to investigate the possible safety benefit of this European side-markers configuration. A test panel at TNO- HFRI was used to determine the difference in response time and detection error of drivers, confronted with slides of vehicles with and without the mentioned new vehicle side-marker configuration in several visibility conditions, crossing illumination and different vehicle approach angles. The investigation showed a significant faster vehicle recognition with less detection errors in case the approaching car was equipped with the bright amber side-markers. This improved vehicle conspicuity can be a benefit in crash avoidance, especially when the driver approaches a crossing with complex light environment and reduced visibility.

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.